West Asia War Dossier: Dashboards https://takshashila.org.in/pages/trackers/westasianwar/ Live dashboards tracking Iran and West Asia from Takshashila quarto-1.8.25 Sun, 26 Apr 2026 18:30:00 GMT Bhumika Sevkani https://takshashila.org.in/content/blogs/20260427-coal-gasification-in-india.html document.addEventListener("DOMContentLoaded", function () { const titleBlock = document.getElementById("title-block-header"); const contentBlock = document.getElementById("quarto-content"); const hasTitle = titleBlock && titleBlock.querySelector("h1"); if (titleBlock && !hasTitle) { titleBlock.remove(); return; } // Strip " | Day N of Operation ..." suffix from bulletin titles if (hasTitle) { hasTitle.textContent = hasTitle.textContent.replace(/\s*\|\s*Day\s*\d+.*/i, '').trim(); } if (titleBlock && contentBlock) { contentBlock.parentNode.insertBefore(titleBlock, contentBlock); } });

The energy supply shocks have re-surfaced the debate around coal gasification in fuel import dependent countries. The process converts coal into a mixture of carbon monoxide, hydrogen, carbon dioxide, and methane, commonly known as Syngas, and can be used for power generation, fuels, and chemical production. After looking at China’s successful adoption of coal gasification, India is also considering accelerating the domestic adoption of the technology for meeting the country’s long-term energy security needs. To accelerate adoption, the government launched a ₹8,500 crore viability gap funding (VGF) scheme in January 2024 to support coal and lignite gasification projects across public and private sectors. Some early industrial applications are already underway with Jindal Steel’s plant in Angul, Odisha, using coal-based syngas for direct reduced iron (DRI) production, offering a potential substitute for natural gas in steelmaking. However, besides the high capital intensity of coal gasification plants, India also lacks indigenous technologies and supply chains for large-scale adoption. These capabilities are required to meet the specific requirements of India’s high-ash coal and localised supply chains could reduce the costs of projects. Some progress in this direction has been Bharat Heavy Electricals Limited’s (BHEL) development of pressurised fluidised bed gasification (PFBG) technology suited to high-ash (>40%) Indian coal, while Thermax has demonstrated methanol production from such coal without pre-treatment. These innovations are critical, given the limitations of imported technologies. Most imported technologies are suitable for coal with ash contents below 25%. With significant upfront investments required, the technology will be reliant on policy support until the establishment of market linkages that can help producers become commercially feasible. Some analysis suggests that Syngas produced from coal could be up to 20 times cheaper than imported natural gas, and it can be highly competitive if the technology achieves economies of scale. End-use sectors such as fertilisers and petrochemicals that are reliant on imported feedstocks as well as hard to abate sectors like steel and cement could benefit from coal gasification, resulting in cleaner use of the fuel if coupled with carbon capture. China is a dominant global producer of several key inputs for fertilisers and chemicals, utilising syngas for their production. Specifically, the country uses syngas to produce Urea (China accounts for 40% of the global production), Methanol (70% of it produced using syngas), and Ammonia (90% produced using syngas) which is an essential input for DAP. While the technology is promising, and can contribute to India’s energy security in the long term, its costs need to be assessed against the import bills that can be reduced by using Syngas, and the momentum needs to be sustained beyond energy crises for coal gasification to be widely adopted and reach commercial viability.

]]> West Asia Energy Security https://takshashila.org.in/content/blogs/20260427-coal-gasification-in-india.html Sun, 26 Apr 2026 18:30:00 GMT Bharath Reddy Shobhankita Reddy https://takshashila.org.in/content/publications/20260423-West-Asian-War-Impact-On-Artificial-Intelligence.html document.addEventListener("DOMContentLoaded", function () { const titleBlock = document.getElementById("title-block-header"); const contentBlock = document.getElementById("quarto-content"); const hasTitle = titleBlock && titleBlock.querySelector("h1"); if (titleBlock && !hasTitle) { titleBlock.remove(); return; } // Strip " | Day N of Operation ..." suffix from bulletin titles if (hasTitle) { hasTitle.textContent = hasTitle.textContent.replace(/\s*\|\s*Day\s*\d+.*/i, '').trim(); } if (titleBlock && contentBlock) { contentBlock.parentNode.insertBefore(titleBlock, contentBlock); } });

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Executive Summary

This report finds that the war in West Asia exposes fragilities in the global AI supply chain that impact the national AI strategies of most countries, including India. The impact can be analysed along three dimensions.

First, the AI stack extends beyond data, models, compute and energy prioritised in the national strategies of most states. Disruptions in helium and bromine supplies, and energy flows because of the effective closure of the Strait of Hormuz, have short-term impacts on the world’s production of advanced semiconductor chips and high bandwidth memory that is concentrated in Korea and Taiwan, and used for AI training and inference.

Second, AI infrastructure has entered the theatre of conflict in two ways simultaneously. The Islamic Revolutionary Guard Corps designated AWS and Oracle facilities in the UAE and Bahrain as “legitimate targets”, marking the first confirmed kinetic strikes on commercial cloud infrastructure in history. At the same time, the battlefield use of AI-enabled decision-support systems such as Lavender, Gospel, and Maven by Israeli and American forces generated targets at combat speed. This raises questions about whether meaningful human control is possible. AI is now both an object and an instrument of war.

Third, a protracted war risks elevated energy prices, rising input and insurance costs, and stagflation pressures that could stress the AI investment cycle at its historical peak. Geopolitical uncertainty is likely to accelerate market concentration in a few firms with deep pockets, furthering the divide and raising costs of access and adoption for emerging economies.

For India, a few implications follow. Frontier AI’s emergence as an instrument of US foreign policy argues for higher defence AI R&D expenditure and diplomatic advocacy for “meaningful human control” in lethal autonomous weapons systems. Risks of capital flight from emerging markets and rising costs necessitate frugal innovation and supporting open-tech alternatives. On the positive side, India may benefit from positioning itself as a data centre hub as an alternative to the Gulf. But reforms that unlock private-sector participation in the generation, transmission, and distribution of energy and provide an effective path for clean energy transition would be key to activating the required levers.

Introduction

India’s primary concerns vis-a-vis the war in West Asia pertain to its 9 million strong diaspora, their safety and associated remittance flows as well as energy dependencies from the region. This paper moves away from these important, pressing issues and studies a quieter set of second and third order impacts that the war has revealed and accelerated in the global artificial intelligence development and diffusion.

The paper is divided into four sections - supply chain fragilities; the dual role of AI infrastructure in the war - as a subject of kinetic strikes and as an instrument of warfighting through decision-support systems; the war’s effects on the AI investment landscape; and finally, implications for India.

Supply Chain Fragility

The primary building blocks of the AI stack include data, models, compute, and energy. In addition to these, infrastructure, investments, talent and the regulatory ecosystem have been the focus for building a resilient AI supply chain. Most national AI policies, including India’s AI Mission, target one of these different building blocks. However, the Iran war has revealed that the global supply chains of the technology are more complex and often go down to the input materials involved.

Input Materials

Consider helium, which is extremely useful in magnetic resonance imaging machines, semiconductor manufacturing and aerospace applications. Thanks to its excellent thermal conductivity and inertness, it serves as a coolant for maintaining a stable environment during the semiconductor fabrication process. Its supply chains are fairly concentrated, dominated by the US, Russia and Qatar. Being one of the lightest gases, it leaks over time, making stockpiling expensive and technically demanding.

QatarEnergy declared force majeure in March 2026 following strikes on key facilities in Ras Laffan Industrial City. This has effectively taken 30% of global capacity of helium, produced as a byproduct of LNG refining, offline 1. However, the element is one of several inputs, and high-tech industries command enough purchasing power to secure supply at elevated prices and from other sources, even as other buyers get squeezed. Bromine is another input in the semiconductor etching process whose supply is being crunched by the war and leading to a price surge – two-thirds of the world’s bromine comes from Israel and Jordan 2. While the Iran war is unlikely to trigger a helium crisis, short-term disruptions are already underway while prices respond and alternative sources are being explored. This exposes the fragility of technology supply chains to geopolitical risks.

Energy

A more significant disruption has been caused by the energy crisis triggered by the war. South Korean firms like Samsung Electronics and SK Hynix account for nearly 80 per cent of the global high-bandwidth memory (HBM) and 70 per cent of the dynamic random access memory (DRAM) market 3. The country is heavily dependent on fossil fuels for its energy needs, with 70 per cent imported from West Asia through the Strait of Hormuz 4. A similar story plays out in Taiwan, where 90 per cent of the world’s most advanced semiconductors are manufactured 5. While supply has not been affected yet, the sustained high input costs are putting pressure on profit margins and could accelerate efforts to raise chip prices.

Timing these risks is the real tax for end users. They cannot hedge against an unknown reopening date, so they pay for dual-sourcing, strategic stockpiles, forward contracts at wartime surge prices. Insurance premia for passage through the Strait of Hormuz, which were a small line item prior to the war, have skyrocketed with states stepping up to insure losses and provide naval escorts 6. As resilience takes precedence over efficiency, firms with weaker balance sheets will fold sooner, concentrating the market in hyperscalers that can absorb the increased costs.

AI Infrastructure Becomes Part of the Theatre of Conflict

AI Use in the War

In the past few years, AI has transitioned from a supportive role in military operations to a primary driver of mass target identification and kinetic execution. The speed of this transition has outpaced the development of international humanitarian law – a classic pacing problem, where rapid, exponential advancements in tech outpace the slow, incremental development of laws, regulations, and social structures designed to manage them.

Israel has invested heavily in integrating AI into their decision support systems (DSS), with systems such as Lavender, which shortlists individuals for targeting based on suspected affiliation with armed groups; The Gospel (Habsora), which generates target lists of buildings and structures; and Where’s Daddy?, which tracks individuals’ locations ahead of a potential strike by tracking their phones 7. The US is also extensively using DSS such as Palantir’s Maven Smart System to analyse surveillance data, create targeting lists and enable target-prioritisation 8.

These systems expedite the decision-making process by processing vast amounts of data – Israel’s Lavender DSS was reportedly used to generate over 37,000 targets in the opening weeks of the Gaza war, and the US was able to hit over 1000 targets within the first 24 hours of the Iran war 9. However, it risks the collapse of human control as officers defer to machine suggestions because they cannot process the information at machine speeds. The human in the loop becomes ceremonial.

AI Infrastructure Seen as a Legitimate Target

While firms such as Palantir and Corsight AI are the vendors for the AI-based DSS, there are several other tech companies that provide the enabling infrastructure. These include big-tech companies such as Amazon, Anthropic, Google, Microsoft, and OpenAI 10 .

In a confrontation with militarily outmatched adversaries, Iran has resorted to tactics that exert political and economic pressure. In an unprecedented move, the Islamic Revolutionary Guard Corps (IRGC) designated Amazon Web Services and Oracle’s facilities in UAE and Bahrain as “legitimate targets” because they hosted military applications and proceeded with the first confirmed military strikes on commercial cloud data centres in history 11.

The strikes themselves caused minor disruptions to operations, as cloud data has redundancies built in. However, they set a precedent for a new category of infrastructure in need of military protection from kinetic strikes, in addition to cyber threats. For the US, there are several implications for policy, such as establishing a credible deterrence, intel sharing with industry or serving as a backup insurer for such risks 12.

West Asia as an AI Hub?

The Gulf Cooperation Council states, particularly Qatar, the United Arab Emirates, and Saudi Arabia, are making a strategic push to diversify their economies beyond oil towards emerging technologies such as AI. To position themselves as a regional hub, some of the states have proposed the idea of digital embassies, where foreign governments and companies can govern their data under their own terms regardless of the location of the datacentres 13. The Gulf states are an attractive destination for data centres due to their inexpensive energy, favourable geography relative to other emerging markets and access to capital from sovereign wealth funds.

The dynamics of the AI race between the US and China are a key determinant of who gets access to the building blocks of frontier AI. Saudi Arabia, Qatar and the Emirates, having signed access-for-investment deals with the US 14. They get access to state-of-the-art AI chips in exchange for investments with US partners. Further, the Pax Silica, which is a US initiative that aims to secure the AI supply chain among a strategic bloc of allies and partners, has Qatar and the United Arab Emirates as signatories 15.

For the Gulf states, the intent to partner with the likes of Google, Microsoft, OpenAI and others could also be seen as a way to lock in a security guarantee from the US 16. However, the emerging precedent of attacks targeting AI infrastructure means that data centres, energy facilities, and sub-sea cables connecting the region to the global internet are now vulnerable targets. Given the high costs, including long-term power contracts, land agreements, and fibre connectivity, invested in already operational facilities, it’s unlikely that hyperscalers will relocate built capacity. But the marginal investment decision for new capacity rollouts would factor in this added geopolitical risk, alongside other location-evaluation metrics such as tax incentives and power-grid stability.

Investment Under Stress

Fragile Pre-War Baseline

The war arrived at the peak of the largest and most concentrated capital expenditure cycle in the history of the technology sector. The five US frontier AI labs and hyperscalers — Amazon, Microsoft, Alphabet, Meta, and Oracle — had committed between USD 660 billion and USD 770 billion of capex in 2026, roughly three-quarters of it directed at AI infrastructure 17. The scale of the investments by US companies exceeds that of monumental past capital expenditures, such as the Manhattan Project, the moon landing, or the broadband buildout. Aggregate hyperscaler capex had risen from USD 256 billion in 2024 to USD 443 billion in 2025, growing at an annualised rate of roughly 72 per cent since the second quarter of 2023 18.

Notably, this buildout is being funded through debt, and not internal cash generation and is yet to be tested through a credit cycle. Hyperscalers raised USD 121 billion in new debt in 2025 19. In February 2026, Alphabet Inc. issued a rare 100-year bond (century bond) primarily meant to finance AI infrastructure that was oversubscribed 10 times. Critics have raised concerns about the aggressive accounting practices employed by these firms, such as extending the “useful life” of AI assets, despite the rapid obsolescence of high-end GPUs 20. The important question is whether the eventual adoption, diffusion and revenue from AI services will scale fast enough to cover these recurring depreciation charges.

AI Investments

In the scenario of a prolonged war, including the Gulf countries participating, the world may be headed for stagflation pressures like those of the 1970s: high energy prices contributing to global inflation while economic activity stagnates. This is likely to have an impact on the profitability of frontier AI labs and hyperscalers. Returns on AI investments now need to price in greater geopolitical and market concentration risks. This is likely to stretch the timelines between investment and return, even leading to valuation compressions for AI companies and concentrating market power in favour of companies with deeper pockets. A potential capital redistribution away from emerging markets can threaten access, diffusion and developmental goals in these societies.

Globally, whether AI adoption timelines will be compressed for productivity gains or stretched due to a declining global GDP growth rate remains to be seen.

Implications for India

AI Sovereignty and Defence AI Policy

The India AI mission has built baseline domestic capabilities through support for indigenous large language models, with applications in agriculture, healthcare and education being the focus. However, to a large extent, Indians access frontier AI through two channels: proprietary models mostly from US labs (Anthropic, Google, OpenAI) and open weight models from Chinese and US labs (Z.ai, Alibaba, DeepSeek, Google, NVIDIA, OpenAI) 21.

The Iran war and related events in the past few months have highlighted the sovereignty risks. The US and Israel have used frontier AI capabilities on the battlefield to enable decision-making at combat pace. Meanwhile, the Pentagon-Anthropic standoff shows that the US-state can get AI companies to comply with their demands – when Anthropic drew red lines on surveillance and autonomous weapons, it was designated a “supply chain risk” and OpenAI, Google and xAI accepted the “all lawful use” standard. This highlights the fact that frontier AI can be a tool of US foreign policy. Most of the frontier AI companies are American and currently restrict access of military applications to the US and the country’s closest allies.

The importance of increasing defence R&D expenditure is evident – it is currently a small share of the 2% GDP defence budget. India should also push diplomatically for “meaningful human control” in lethal autonomous weapons systems and AI-enabled targeting. On the civilian side, India should pursue plurilateral efforts with partners such as the EU, Japan and Korea to achieve shared sovereignty 22. This can be done by supporting open-tech alternatives where concentration is highest. Some examples include support for open standard instruction set architectures such as RISC-V, open source alternatives to NVIDIA’s proprietary programming platform CUDA, open-source model development, and harmonised evaluation.

Infrastructure and Supply Chain Resilience

The war highlights risks to AI infrastructure. The resilience measures that are likely to follow add capex and opex costs across the AI stack that will eventually be borne by end-users.

  • Iran reportedly threatening to cut Red Sea cables during the war 23 was the second stress test on India’s digital backbone in recent months. The Red Sea cable cuts in September 2025 caused internet shutdowns and latency across large parts of the country. Over 60% of India’s internet traffic transits through West Asia and lands at Mumbai 24. The other landing points at Chennai and Kochi have a smaller presence, making it a critical vulnerability. Addressing it requires terrestrial backbone redundancy, landing diversification and indigenous repair capabilities – India currently depends on foreign cable-repair fleets – to be built up.

  • The Iranian strikes on AWS facilities in the UAE and Bahrain, and the IRGC’s “legitimate target” framing, establish a precedent that data centres could be military targets. For hyperscalers, this makes geopolitical risk a site-selection criterion alongside power, water, land and state policies.

  • The short-term disruptions caused by the war expanded the perception of the AI supply chain to include materials few considered strategic – Helium, Bromine and energy from West Asia are crucial inputs for semiconductor manufacturing in East Asia. Building on Beijing’s weaponisation of its processing dominance in several minerals, including gallium, germanium, graphite, and other rare earths in its trade war with the US, the war in West Asia is likely to further the diversification imperative.

Economic and Strategic Factors

The economic fallout of the war will impact AI development and diffusion in several ways, depending on how prolonged the conflict lasts. A prolonged war with sustained high energy prices could contribute to global inflation and stagnation of economic activity. Some of the different dimensions of this impact are described below.

  • Rising costs will favour better-resourced companies that can sustain longer timelines between investment and return. Building resilience against supply chain risks passes on the increased costs of energy, semiconductors and insurance to the companies building AI infrastructure. With demand already outpacing supply, investments into fabs by companies such as TSMC won’t yield chips until a few years later – those with deeper pockets will be able to lock-in multi-year allocations while new entrants face restricted access at spot prices.

  • Global equity capital that was chasing returns in emerging markets or second-tier AI labs might move to safer assets in uncertain scenarios. The increase in oil prices also leads to weakening of emerging market currencies such as the Indian rupee due to higher costs of oil imports and capital outflows seeking the dollar as a safe haven. Since most AI capex is US dollar-denominated, it inflates the bill of materials significantly.

  • The GCC states, with their access to capital, energy and favourable location had positioned themselves as a key pillar for the diffusion of the American AI stack. With the attacks on data centres in the Gulf, capital allocation now needs to factor in geopolitical risks due to security guarantees, insurance, and location diversification. This opens up an opportunity for India to be an alternative data centre hub to the Gulf. India’s national data centre policy already offers a 20-year tax holiday, along with states offering other incentives related to access to land, energy and water. The Indian electricity system has major problems that limit private-sector participation and the transition to greener energy sources. Centralised planning controls resource allocation, which might not respond to market demands; transmission and distribution losses due to theft also add pressure to the finances; and there is no effective path for clean energy transition 25. Reforms to India’s electricity sector aimed at increasing private-sector participation are under consideration 26 but a much-needed comprehensive overhaul faces political economy pressures. In addition, safety would be a key factor in relocation decisions for AI researchers and their families. Depending on how long the war stretches, talent flows to the Gulf could be impacted.

  • Constraints on access to capital might lead to increased pressures for frugal innovation. DeepSeek and other Chinese open weight models are gaining popularity across Africa, aided by strategic partnerships with firms such as Huawei 27. The widespread adoption of competing ecosystems might be a better outcome for most countries than one dominated by a few big tech companies from a single country.

  • Lastly, one of the spillover effects of this war may be that the impact of generative AI on the workforce and the broader economy, unfolding simultaneously with the effects of the war, is difficult to mitigate. On the heels of the aftereffects of a global pandemic and supply chain readjustments forced by the tariff wars, the war in Iran might serve as an additional confounding variable, making it harder to gauge AI’s true impact.

Footnotes

  1. Béchard, Deni Ellis. “The AI Boom Is Dangerously Dependent on Helium.” Scientific American, March 18, 2026. Link↩︎

  2. Kharpal, Arjun, and Dylan Butts. “How the Iran War and Rising Energy Prices Are Threatening Semiconductor Demand.” CNBC, March 10, 2026. Link↩︎

  3. Trueman, Charlotte. “Samsung and SK Hynix to Scale Up Memory Production Capacity in 2026 to Meet AI Demand.” Data Center Dynamics. January 2026. Link↩︎

  4. Sharma, Abhishek. “The Hormuz Crisis and South Korea’s Energy–Alliance Nexus.” Observer Research Foundation, April 13, 2026. Link↩︎

  5. Li, Kevin. “The Iran War Tests Taiwan’s Energy Resilience.” Atlantic Council, March 19, 2026. Link↩︎

  6. Humairah, Laila. “Hormuz Becomes World’s Most Expensive Waterway after 300% Surge in Risk Premiums.” Euronews, March 16, 2026. Link↩︎

  7. Serhan, Yasmeen. “How Israel Uses AI in Gaza–And What It Might Mean for the Future of Warfare.” Time, December 18, 2024, Link↩︎

  8. Mohammed, Noor. “The Proliferation of AI-Enabled Military Technology in the Middle East.” International Institute for Strategic Studies, April 2026. Link↩︎

  9. ibid.↩︎

  10. ibid.↩︎

  11. Al Jazeera Staff. “Iran Declares US-Israeli Economic, Banking Interests in Region Are Targets.” Al Jazeera, March 11, 2026. Link↩︎

  12. Harding, Emily. “Data Is Now the Front Line of Warfare.” Center for Strategic and International Studies, March 19, 2026. Link↩︎

  13. G42. “G42 Introduces Digital Embassies and Greenshield to Make AI Sovereignty Portable.” Press release, January 20, 2026. Link↩︎

  14. Yacoubian, Mona, and Samuel Zabin. “If Compute Is the New Oil, War in the Gulf Significantly Raises the Stakes.” Center for Strategic and International Studies, February 27, 2026. Link↩︎

  15. U.S. Department of State. “Pax Silica.” Under Secretary for Economic Affairs. Accessed April 20, 2026. Link↩︎

  16. Cook, Steven A. “For the Gulf States, Investment in AI Is Partly About U.S. Protection.” Foreign Policy, February 23, 2026. Link↩︎

  17. Srivastava, Prakhar, and Anirban Sen. “Big Tech to Invest about $650 Billion in AI in 2026, Bridgewater Says.” Reuters, February 23, 2026. Link↩︎

  18. Juniewicz, Isabel. “Hyperscaler Capex Has Quadrupled since GPT-4’s Release.” Epoch AI, February 26, 2026. Link↩︎

  19. Bair, Theodore Jr., and Bryan Steele. “Record-Breaking AI-Related Debt Issuance in 2025.” Global Macro Views (blog). Mellon Investments Corporation, December 2025. Link↩︎

  20. Tiger Newspress. “Michael Burry Sounds Alarm on $176B Depreciation Gap among Tech Giants.” Tiger Brokers, November 12, 2025. Link↩︎

  21. Artificial Analysis. “LLM Leaderboard — Comparison of over 100 AI Models from OpenAI, Google, DeepSeek & Others.” Accessed April 20, 2026. Link↩︎

  22. Sharma, Lokendra, Abhishek Kadiyala, Arindam Goswami, Ashwin Prasad, and Nitin Pai. “India Must Architect Sectoral Plurilateral Blocs to Overcome Geopolitical Coercion.” Takshashila Institution, January 2026. Link↩︎

  23. TOI Tech Desk. “Iran Reportedly Threatening to Cut Red Sea Cables: What It Means for Internet Users across the World, Including India.” Times of India, March 2026. Link↩︎

  24. Communications Today. “Undersea Cable Risks in West Asia — What It Means for India’s Connectivity.” March 2026. Link↩︎

  25. Shah, Ajay, and Susan Thomas. “Electricity Cost Recovery and the Political Imagination: A Comparison between Private and Public Distribution in India’s Biggest Cities.” The Leap Blog, November 2, 2025. Link↩︎

  26. Ministry of Power. “Draft National Electricity Policy (NEP), 2026 Released for Public Consultation with Stakeholders.” Press release. Press Information Bureau, January 21, 2026. Link↩︎

  27. Microsoft Corporate Blogs. “Global AI Adoption in 2025 — A Widening Digital Divide.” Microsoft, January 8, 2026. Link↩︎

]]> Artificial Intelligence High Tech Geopolitics Iran https://takshashila.org.in/content/publications/20260423-West-Asian-War-Impact-On-Artificial-Intelligence.html Wed, 22 Apr 2026 18:30:00 GMT Why The Blockade Is Trump’s Best Card https://takshashila.org.in/ Geostrategy United States West Asia Iran https://takshashila.org.in/ Tue, 21 Apr 2026 18:30:00 GMT Pakistan's Ever-Running Saudi 'Lifeline' Has Its Limits https://takshashila.org.in/ Geostrategy Pakistan West Asia https://takshashila.org.in/ Sun, 19 Apr 2026 18:30:00 GMT Anushka Saxena https://takshashila.org.in/content/publications/Shahed-Iran-Drone-Strategy-14042026.html document.addEventListener("DOMContentLoaded", function () { const titleBlock = document.getElementById("title-block-header"); const contentBlock = document.getElementById("quarto-content"); const hasTitle = titleBlock && titleBlock.querySelector("h1"); if (titleBlock && !hasTitle) { titleBlock.remove(); return; } // Strip " | Day N of Operation ..." suffix from bulletin titles if (hasTitle) { hasTitle.textContent = hasTitle.textContent.replace(/\s*\|\s*Day\s*\d+.*/i, '').trim(); } if (titleBlock && contentBlock) { contentBlock.parentNode.insertBefore(titleBlock, contentBlock); } });

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Executive Summary

This Issue Brief finds that:

  • The Shahed is representative of the accessible proliferation of precision strike capability. Iran has been able to engineer a low-cost UAV and produce it en masse. This UAV has been able to perform nearly as well as much more expensive systems. The Shahed challenges traditional cost-benefit calculations in air defence and enables sustained attritional campaigns against more powerful adversaries.

  • Drone technology diffusion is accelerating. Many realities, ranging from Russia’s domestic Shahed production and the US’s production of LUCAS copies of Shahed, to the transfer of drone technology to and from China as a hub, and proliferation to non-state actors, are pointing to a global drone arms race underway. The Shahed template is now being adopted, reverse-engineered, and exported globally to reshape military calculus akin to Iran in its 2026 war with the US and Israel.

  • Global sanctions have failed to constrain Shahed’s supply lines. Despite being heavily sanctioned, Iran has built a fully operational Shahed ecosystem using 80 per cent American components sourced through shell companies, Chinese re-export hubs, and exploiting dual-use trade loopholes. Tehran epitomises why turnkey equipment sanctions fail to address component-level free flow.

Introduction

The US-Israel war on Iran, starting February 28, 2026, and spilling over both in terms of geographic scope and intended outcomes, has spotlighted, among other crucial aspects, Tehran’s attritional capabilities against a much-too superior adversary. Its use of uncrewed aerial systems, or ‘drones’, in this regard, has emerged as key in both, explaining Tehran’s strategy, and epitomising the revolution in the global means and methods of warfighting in an era of network-centric, beyond-visual-range, and asymmetric warfare.

Most of Iran’s target strikes in West Asia so far have deployed a combination of surveillance and reconnaissance, combat, and attack drones. Notable incidents of Tehran’s drone use between February 28, and April 8, when a temporary ceasefire was announced, are as follows:1

  • On March 1, a Shahed-type drone struck RAF Akrotiri in Cyprus, hitting a hangar, and leading to the partial evacuation of stationed troops. RAF Akrotiri is a British sovereign base on a NATO country’s territory – roughly 1,700 km from Iran’s western launch areas. On the same day, Iranian drones also struck Camp Buehring – a major US training and logistical base in Kuwait – damaging US Chinook helicopters and causing the fatalities of 6 soldiers, as well as the French Navy’s Al Salam Base (Camp De La Paix) in the UAE, but no casualties were reported.

  • In Bahrain in particular, on February 28, and then on March 8 and 9, three major sites were targeted by Iranian drones – first, the US Navy’s Fifth Fleet HQ in Manama, then a water desalination plant (which sustained damage), and finally, a petroleum oil refinery operated by BAPCO (which caught fire, and declared force majeure). In terms of commercial activity, too, the activities of Amazon Web Services Bahrain were disrupted twice by Iranian drone strikes, as a result of which, on March 23, Amazon announced that it is planning to shift operations out.

  • Iranian drones hit a fuel depot at one of the busiest airports in the world – the Dubai International (DXB) – on March 16, causing a massive fire and a halting of flights and operations. Two days before the same, in Al Kharj, Saudi Arabia, on March 14, an Iranian drone strike destroyed at least 5 US refuelling aircraft based at the Prince Sultan Air Base.

This Issue Brief studies the characteristics of an Iranian ‘Shahed’ drone – a class of one-way attack (OWA) drones developed by Shahed Aviation Industries and manufactured by the state-owned Iran Aircraft Manufacturing Industries Corporation or HESA. It examines Iran’s domestic production and export model in the military drone sector, as detailed in reports and public accounts. The brief concludes with a preliminary assessment of supply chain integration pathways and the techniques Iran employs in procuring global drone equipment.

Types of Shahed

‘Shahed’ is a class or family of propeller-driven cruise missiles, designed to be OWA munitions that fly toward pre-programmed coordinates using satellite navigation and inertial sensors (See Table 1). They cost anywhere between US$ 20,000 and US$ 50,000 to produce, with some export variants sold to Russia (and renamed the ‘Geran’ class) likely2 costing around US$ 80,000. The export price ranges3 from US$ 100,000 to US$ 290,000. In principle, they should be irrecoverable as they are expected to explode upon reaching target, but their fuselages and internal components have often been recovered in whole or part, especially from the Ukrainian battleground since 2022, but also from Iraq following the Baghdad clashes in 2021, and the UAV attack on Kurds in northern Iraq in 2022, which was publicly claimed by Tehran. This has enabled4 the US not only to study their make and model but also to replicate them in the form of the US Central Command’s own Low-Cost Uncrewed Combat Attack System (or ‘LUCAS’) drone.

Table 1

Types of Shahed Drones

Variant Length Wingspan Weight Warhead Range Speed Key Feature Engine/Power
Shahed-107 2.5m 3m ~26 kg ~15 kg ~1,500 km 120-185 km/h Loitering munition + reconnaissance Chinese DLE 111 gasoline engine
Shahed-131 2.6m 2.2m ~900 kg ~20 kg ~900 km ~185 km/h Smaller, shorter-range predecessor Wankel rotary engine (Chinese MDR-208, reverse-engineered from British AR-371)
Shahed-136 3.5m 2.5m ~200 kg ~50 kg 1,500-2,500 km 185+ km/h Most popular variant; OWA munition MD-550 two-stroke, four-piston engine (reverse-engineered from German Limbach L550)
Shahed-238 3.5m ~3m ~380 kg ~50 kg ~2,000 km ~520 km/h (cruise) High-speed; turbojet engine; diverse guidance versions (IR/optical, radar-homing, inertial+GPS) Czech-made TJ150 turbojet
Shahed-149 ‘Gaza’ 10m 21m 3,000+ kg ~500 kg (across 8-13 hardpoints) 4,000+ km 350 km/h HALE drone for strike missions; real-time target acquisition Russian Klimov TV3-117 Turboprop

In addition to the benefits of cost, design philosophy, and attrition capabilities, the Shaheds’ launch profile adds to these advantages. This is because the IRGC can fire them from portable rails or racks on trucks, with a small pulse rocket booster on the bottom,5 which first pushes the drone to attain cruise speed, and is subsequently jettisoned. The portability of the launch frame and drone assembly enables the entire system to be mounted on the back of any civilian or military truck. Hence, the ‘Rocket-Assisted Take Off’ (RATO) provides the necessary energy for take-off, while the rail-mounted trucks can recede post-launch and remain mobile or underground, providing a significant edge in launch stealth over missile battery systems that are relatively immobile.

Composition of The Family

The Shahed-136 is the most popular variant of the class to emerge in 2026. It is6 ~3.5 metres long with a 2.5-metre wingspan, flies at a speed of over 185 km/h, weighs roughly 200 kg, and carries a warhead estimated at 50 kg in the nose. The range estimates for the same vary from 1,500 to 2,500 km, depending on the configuration. Its airframe and body build is a most interesting feature, in that there are various accounts of what actually goes in, but the nature of the lightweight, easily manufactured and scalable speaks to Tehran’s philosophy of producing a good-enough drone.

The airframe proper is built from composite materials with fiber-glass delta wings containing honeycomb structural fillers. Later versions incorporate carbon fiber reinforcement in the wings and fuselage. When the UK-based Conflict Armament Research studied captured Russian variants in 2023, they found7 “major differences in the airframe construction,” including a fuselage now made of fiber-glass over woven carbon fiber rather than lightweight honeycomb. Analysts examining another Russian-assembled unit described8 it as a dense foam9 material covered by a grey or dark, charcoal-coloured fiber-glass. Some sources10 also mention “balsa wood” in the Shahed-136, which may refer to its use as a honeycomb core filler, given that balsa is a common core material in composite sandwich panels in the aerospace industry. This composite material absorbs or scatters radar signals more effectively than metal-bodied airframes, resulting in better radar evasion.

A Delta-Wing drone design with a characteristic triangular wing shape outperforms a rectangular or swept-wing drone design by providing greater natural mid-flight stability at high speeds, easier manufacturing, and reduced infrastructure (as it removes the need for supporting ribs or a separate horizontal stabiliser tail). Of course, a delta-wing design is not perfect, as it experiences high drag at low speeds and is not ideal for loitering or high-endurance operations.

Then, there is the Shahed-131, which is a smaller, shorter-range predecessor of the 136. The 131 is used11 by the Houthis, a Tehran-backed militia group, in the 2019 east-west oil pipeline attack in Saudi Arabia. Its length and wingspan stand at ~2.6 m and ~2.2 m respectively, its weight at 900 kg, and the weight of the warhead in its cone can go12 up to ~20 kg.

The key similarities between the 131 and 136 are three-fold – they both have a delta wing design; they both carry similar types of warheads in their nose, which include high-explosive fragmentation (HE-FRAG), thermobaric (vacuum) explosives, and shaped-charge warheads; and they both use Global Navigation Satellite Systems (GNSS) as they cannot be remotely controlled. For that purpose, both their right wings host a ‘Puck-4’ GNSS antenna for high precision.

HE-FRAG is the most common Shahed warhead. The explosive charge is surrounded by a metal casing, sometimes with pre-formed fragments, such as tungsten balls, embedded in it (as Russia added to later Geran-2 variants). When the explosive detonates, it shatters the casing outward at enormous velocity, sending hundreds or thousands of metal fragments in all directions like a giant shotgun blast. The blast wave itself, in addition to the fragments, causes significant damage to targets. The Thermobaric (Vacuum) Explosives work in two stages. The first charge disperses a cloud of fuel – usually a fine aerosol of metal powder (often aluminium) mixed with an organic fuel – into the air around the point of impact. A fraction of a second later, a secondary charge ignites that cloud. Finally, shaped-charge explosives are lined with a concave metal cone, usually made of copper. When the explosive detonates, it collapses the metal cone inward at tremendous velocity, forming a superplastic jet of molten metal moving at roughly 7-8 km/s (about 25 times the speed of sound).

The key differences between the two are their powerhouses and vertical wing stabilisers. On the latter front, while the 131’s wing stabiliser only extends upward from the delta wings, the 136’s wing stabilisers extend both upward and downward. On the former front, the Shahed-131 operates on a ‘Wankel’ rotary engine, which provides just the right amount of power for its small size, and has a range of ~900 km. It is reportedly13 reverse-engineered from the Chinese MDR-208 Wankel engine developed by the company Micropilot UAV Control System Ltd, which in turn is reverse-engineered from the British AR-371 engine. It is important to note that there is a heavy hand of the Mado Company (Oje Parvaz Mado Nafar Company) behind these reverse-engineering and drone engine design endeavours.

The 136 is powered by the MD-550 two-stroke, four-piston engine, reverse-engineered from the German-designed Limbach L550 motor. The technology was reportedly14 obtained by Iran when it captured a German-made LIMBACH FLUGMOTOREN L-550 aircraft engine in 2006. The MD-550 is more fuel-efficient than a rotary engine, is air-cooled and drives a two-bladed propeller, and creates a buzzing sound, earning15 it the nickname, “the Moped,” from the Ukrainians. The Russian Garpiya A1 Kamikaze drone, which Moscow has created for itself as an alternative to reduce dependence on the ‘Gerans’, also uses a similar four-cylinder, two-stroke piston engine, reportedly16 manufactured in and/ or resold by China’s Micropilot. The firm may have either purchased the technology from the Iranians, or adopted17 it from the Xiamen-Limbach manufacturing facility in Fujian.

Three other noteworthy variants are the Shahed-107, the Shahed-238, and the Shahed-149 ‘Gaza’. The 107 is a loitering munition with possible reconnaissance capability, approximately 2.5m long, with a 3m wingspan, a warhead capability of ~15 kg, and an estimated range of 1,500 km. It is reportedly18 powered by a Chinese two‑stroke DLE 111 gasoline engine, and was deployed widely by both Russia against Ukraine, and the Islamic Revolutionary Guard Corps (IRGC) against Israel in the 12-day war of June 2025. The 238 is a newer variant that uses a turbojet engine (the Czech-made TJ150), dramatically increasing the cruising speed to around 520 km/h, compared to the standard 180 km/h. A most fascinating feature of the 238 is its diverse set of versions19 – while one carries an infrared/optical guidance system, another has radar-homing guidance. A third, baseline version uses autonomous inertial navigation, followed by satellite guidance for mid-course updates, and with terminal guidance relying on inertial continuation or, in advanced variants, onboard seekers. Its ‘Geran-3’ model is in use by Russia, and, by some estimates,20 the 238 may have an export price of up to US$ 1.4 million. For comparison, a relevant counterpart would be the IAI Harop, whose per-unit cost exceeds US$ 1 million.

The Shahed-149 ‘Gaza’, which has a wingspan of 21m and a larger payload of 500 kg across 8-13 hardpoints, is the most recent addition to the family, unveiled in 2021. It is not a kamikaze, but a High-Altitude, Long-Endurance (HALE) drone designed for strike missions. With a range of over 4,000 km, an endurance of up to 35 hours, and a maximum speed of 350 km/h, it is powered by the Russian Klimov TV3-117 Turboprop engine. Two main features of the ‘Gaza’ have been touted21 by the IRGC in Iranian media – its Synthetic Aperture Radar (SAR) and electro-optical/infrared (EO/IR) systems, which enable real-time target acquisition and assessment.

Aboard the ‘Gaza’, the EO/IR system functions as the drone’s primary “eyes,” combining high-resolution daylight cameras with thermal imaging sensors in a stabilised gimbal turret (a ball-shaped sensor unit mounted below the drone’s nose) to enable continuous surveillance and targeting in both day and night conditions. This allows operators to detect, identify, and track targets based on visual and heat signatures, even through darkness or partial concealment.

The Lifecycle

There are three main players in the production and consumption lifecycle of a Shahed done in Iran. Firstly, there are the state-owned designers and producers. The backbone of this infrastructure is comprised of HESA and Qods Aviation Industries (QAI). HESA, based in Isfahan, is responsible for the Ababil series and the assembly of the Shahed-136, while QAI manages the Mohajer-6 and other surveillance-heavy platforms. Vitally, the IRGC Aerospace Force operates its own industrial arm, Shahed Aviation Industries, which is credited with designing the delta-winged Shahed series.

These official entities have been engaged with drone-related research and development since the 1980s, when Iran first began using UAVs, starting with the war with Iraq in 1985. Tehran’s losses against the US Navy during Operation Praying Mantis22 of 1988 particularly catalysed their focus on asymmetric capabilities. Subsequently, Iran captured a US RQ-170 ‘Sentinel’ in 2011 and began building its internal UAS production ecosystem. Based on estimates, Iran has, since February 28, used over23 2,000 Shahed drones in its strikes across West Asia. Tehran possesses a stockpile of about 80,000 ready-to-deploy Shaheds, with a daily production capacity of 400 drones.24 As for the Russia-based assembly and production, Ukrainian estimates25 suggest a capacity of up to 5,000 Shaheds per month.

Herein came the role of the second important actor – private companies and IRGC-affiliated individuals. One, for example, is the Mado Company,26 established in 2013 and specialising in reverse-engineering and manufacturing drone engines, drawing inspiration from Western and Asian designs. Then, there are individuals on the board of IRGC’s financial arm, the ‘Cooperative Foundation/ Bonyad Taavon Sepah’, as well as the banks (Ansar and Mehr) and conglomerates (Khatam al-Anbiya Construction and Etemad-e-Mobin) associated with it. Bonyad is widely sanctioned27 by the West, but it continues to identify and finance individuals and companies that can form knowledge bases for the Shahed’s manufacturing process. A classic example28 is the private R&D firm, Paravar Pars Company, which enabled the design and production of one of the first iterations of the Shahed, the 171, as inspired by the ‘Sentinel’.

Emerging from within the Shahed manufacturing facility in Russia are investigative reports29 explaining the process and structure. The factory is divided into several specialised departments. The metal shaping department is where the carbon fiber or fiber-glass webs are first cut. These are then moved to the bonding department, where the fuselage and wing shells are formed. Once the airframe is cured and painted, it moves to the final assembly line. Here, the electronics suite, fuel system, mechanical actuators for the control surfaces, and engine are integrated. The final stage is the installation of the warhead, located in the nose just behind the aerodynamic cone.

Thirdly, there are the import destinations and consumers of Iran’s Shaheds, which ultimately fund a complex lifecycle and supply chain (See Table 2). Tehran has transferred drone technology to Russia and China, as well as IRGC-backed groupings such as Hezbollah, Houthis, and Iraqi militias. Beyond the Shahed, Venezuela30 has been assembling the Mohajer-2 (branded as the ANSU-100) and the QAI Mohajer-6 since the mid-2000s, while Ethiopia and Sudan have used Iranian drones to strike rebel groups. Tajikistan31 also hosts a dedicated Ababil-2 production facility inaugurated by Iran in 2022. Thus, close integration among military recipients, the Iranian government, and manufacturers has enabled the mobilisation of lessons from many operational use cases and, ultimately, the rapid evolution of the Shahed class.

Table 2

Export Customers and Adopted Proliferation

Recipient Relationship to Iran Drone Model(s) Notes
Russia State-level technology transfer Shahed-136 (renamed ‘Geran’), Shahed-238 (‘Geran-3’), Shahed-107 Domestic production in Alabuga Special Economic Zone, Tatarstan; capacity 5,000/month
China Technology transfer (drone tech, BeiDou satellite access) Multiple variants Hub for procurement networks; re-export of components; possible domestic production/reverse-engineering
Hezbollah IRGC-backed militia Shahed variants Non-state actor; used in conflict with Israel (June 2025, 12-day war)
Houthis Tehran-backed militia Shahed-131 Used in 2019 east-west oil pipeline attack in Saudi Arabia
Iraqi Militias IRGC-affiliated groups Shahed variants Various groups receiving transfer for strikes
Venezuela State-level cooperation Mohajer-2 (ANSU-100), Mohajer-6 Assembling Iranian drones domestically since 2000s
Ethiopia Military procurement Iranian drones (unspecified variants) Used to strike rebel groups
Sudan Military procurement Iranian drones (unspecified variants) Used to strike rebel groups
Tajikistan State-level technology transfer Ababil-2 Dedicated production facility inaugurated by Iran since 2022
United States Reverse-engineering (from captured specimens) Shahed variants (studied) Produced own LUCAS (Low-Cost Uncrewed Combat Attack System) copy

A Global Web of Components and Supply Lines

Despite being one of the most sanctioned countries on Earth, Iran has built the Shaheds using a globalised supply chain of commercially available, dual-use components.

Pathways of Integration

These components are brought into an Iranian Shahed’s supply chain and life cycle through four primary pathways, or a parallel combination thereof:

  1. Shell/ Front Companies: This is the most well-documented route. In one case32 unsealed by the US Department of Justice, two Iranian nationals running the company Rah Roshd falsely purported to represent companies based in the UAE and Belgium, using a spoofed e-mail address containing a misspelt version of a legitimate company’s name to procure US-made servo motors and electronic components. They used at least three shell companies based in the UAE to pay a China-based company, with payments processed through US-based correspondent bank accounts. Similar companies have since sprung up in Hong Kong and Turkey as well. In this light, the US Treasury designated,33 in November 2025, as many as 32 individuals and entities across Iran, the UAE, Turkey, China, Hong Kong, India, Germany, and Ukraine to disrupt Tehran’s “Transnational Missile and UAV Procurement Networks.”

  2. Chinese Distributors and Re-Export Hubs: While many parts originate in the US, Europe, and Japan, procurement networks frequently34 route them through Chinese distributors or trading companies before they reach Iranian manufacturers. In this light, in February 2025, the US Treasury sanctioned35 six companies based in Hong Kong and China for their involvement in procuring components for Tehran’s drone and ballistic missile programmes, that too, on behalf of another Office of Foreign Assets Control-designated Iran-based firm – the Pishtazan Kavosh Gostar Boshra (PKGB).

  3. Exploiting dual-use ambiguity and commercial availability: This is the most structurally difficult pathway to stop, as most of Shahed’s components are commercially available off-the-shelf. Electronics, for example, that are sold globally for civilian applications, by say, Texas Instruments or Winbond. Further, of the roughly 50 different types36 of German Infineon transistors that power Shaheds, many, such as the IPB031N08N5,37 are available for sale on eBay for as little as US$ 20.38 Other common circumvention techniques include mislabelling goods or providing incorrect end-user details. This was the case, per an investigation by the Australian Government’s Department of Foreign Affairs and Trade, on a satellite navigation antenna found in a Shahed, which was labelled “Agricultural equipment parts” in Chinese and English.39

  4. Direct state-level technology transfer and reverse engineering: This is the pathway that builds the highest-quality indigenous capability but has the longest risk-reward runway. In terms40 of direct ToT, China gave Iran access to its BeiDou satellite navigation system in 2021, while Russia transferred drone technology and production know-how to Iran. On the reverse-engineering front, Mado company has produced its own engines based on British and German ones, while many American and Israeli drones, such as the Boeing ScanEagle,41 the RQ-170 ‘Sentinel’,42 and likely also the IAI ‘Harpy’,43 have been captured, studied, and replicated in part by Tehran since 2011.

Case Findings

An internal document leaked from the Alabuga Special Economic Zone near Yelabuga, Tatarstan, Russia’s main Shahed-manufacturing facility, revealed that approximately 140 electronic and connector components are used in each Shahed-136, with about 80 per cent44 of those originating from American manufacturers. Then, a Ukrainian intelligence teardown of a captured drone, as made public by CNN,45 found that 40 out of 52 components were made by 13 different American companies. These included Texas Instruments microcontrollers, voltage regulators, and digital signal processors; a Hemisphere GNSS GPS module for Position-Navigation-Timing (PNT); NXP microprocessors; and components from Analog Devices and Onsemi.

Further, another analysis from the ‘Trap Aggressor’ project, in partnership with the Ukraine-based ‘Independent Anti-Corruption Commission’ (NAKO),46 found that Servo drives came from American Hitec USA Group, batteries from Japanese Panasonic, ceramic chip antennas from Canadian Tallysman, the power supply board made from German and Chinese components (the former included the ‘Infineon’ transistors, while the latter included voltage regulators), and the control unit was produced by Russian plant Zapadpribor.47

Servo drives/ motors function as control systems that manage48 a drone’s rotational speed, the force it produces, and its direction. For drone applications, these components are fundamental to achieving the precision required for flight operations. A servo drive continuously monitors the motor’s current state and makes real-time adjustments to match the desired output. In drones, this means the drive receives commands about where a motor should spin or how fast it should turn, checks the actual performance, and corrects any deviation.

Most interestingly, the breakdown conducted by the ‘War Sanctions’49 project of the Ukrainian Defence Ministry’s Main Directorate of Intelligence on a Shahed-107 (See Table 3), reveals a diverse set of components from across the globe. In terms of microcontrollers, the 107 possesses two – one from the China-based manufacturer GigaDevice, and another from Switzerland’s STMicroelectronics. Also coming from China and Switzerland, respectively, are the Toggle Switch, produced by Zhejiang Renew Electronics, and the GNSS module, produced by U-Blox. From the US-based Analog Devices come four other components – a low-noise, 3-axis MEMS accelerometer (which is a specialised sensor designed for high-precision vibration, tilt, and inertial sensing), two Radio-Frequency transceivers, and a buck regulator (needed to power critical electronics like flight controllers, receivers, cameras, and GPS modules). Japan and Taiwan’s manufacturers, Murata and Winbond Electronics, respectively, contribute an electromagnetic filter and a flash memory (for storing essential, permanent data on board). Both the DLE 111 engine, and its ignition system (model A-02), came from China’s Mile Haoxiang Technology Co. Ltd.

Table 3

31 Components of Shahed-107 (As identified by GUR Ukraine on the ‘War Sanctions’ Portal)

Component Type Component Name / Model Manufacturer Country of Origin Notes
CAN Transceiver VP230 TI39M OACYJ Texas Instruments USA Communication bus interface
Line Driver MB3238I 3BK G4 C5PR Texas Instruments USA Signal conditioning
Digital Signal Processor TMS320 F28335PGFA G4 A – 39C505W G4 Texas Instruments USA Core processing unit
Servo Drive Unidentified Not identified Unknown Flight control actuation
Engine Ignition System Model A-02 Mile Haoxiang Technology Co., Ltd (DLE) China Spark timing control
Two-Stroke Petrol Engine DLE 111 Mile Haoxiang Technology Co., Ltd (DLE) China 2-cylinder, air-cooled propulsion
IMU Module SN#: 46-320 Not identified Unknown Inertial measurement unit
Transceiver (RF) ANALOG DEVICES AD9365BBCZ #2415 Analog Devices USA Radio-frequency communication; Production date: April (week 15) 2024
Electromagnetic Interference Filter MURATA BNX023 Murata Japan EMI suppression
Buck Regulator ADP5054 ACPZ #2124 5872838 PHIL Analog Devices USA Voltage step-down; Production date: June (week 24) 2021
Microcontroller (ARM) ARM model unspecified STMicroelectronics Switzerland Primary processor
Toggle Switch RT-S6-22B Zhejiang Renew Electronics China System control
Low-Noise 3-Axis MEMS Accelerometer ADXL357B #2226 844088 Analog Devices USA High-precision inertial sensing; Production date: June (week 26) 2022
Microcontroller GD32F103 TBU6 GDUT028 DS2312 GigaDevice China Secondary processor; Production date: March (12th week) 2023
GNSS Module M8030-KT B3000A 08586206 2249A3 U-blox Switzerland Satellite positioning; Production date: December (week 49) 2022
Flash Memory WINBOND 25Q16JVIQ 2311 6223 AM900ZZ Winbond Electronics Corporation Taiwan Data storage; Production date: March (week 11) 2023
Pressure Sensor TE 561101BA03 229055472 TE Connectivity Ireland Altitude/pressure measurement
RS-232 Transceiver MAXIM MAX3221E EAE2225 Maxim Integrated Products (Analog Devices) USA Serial communication; Production date: June (week 25) 2022
Voltage Regulator GN LF33A GK8X3404 STMicroelectronics Switzerland Power conditioning
Microcontroller (ARM) STM32F405 RGT6 CQ24A VG CHN GQ 402 11 STMicroelectronics Switzerland ARM Cortex-M4 processor
Linear Voltage Regulator GN 78M09 B GK4FM305 STMicroelectronics Switzerland 9V fixed output
SMAJ30CA Protection Diode YK 3H1YB Littelfuse, Inc. USA Transient voltage suppression
Rectifier V20PW45C M209A General Semiconductor (Vishay) USA Diode rectification
Connector 9001-15481C00A Oupiin Enterprise Co., Ltd Taiwan Circuit interconnection
MOSFET FR5305 P350G CK 29 International Rectifier (Infineon Technologies) USA Power switching
16-bit Transceiver LVT16245B BF557 02 UnG0707B NXP Semiconductors Netherlands Logic signal translation
Relay G6K-2F-Y 24 VDC CHINA OMRON Japan Electromechanical switch
Optocoupler H11G1 031Q Fairchild Semiconductor (ON Semiconductor) USA Isolation coupling
Voltage Regulator PS767D301 18T AXE2 Texas Instruments USA Dual-output regulation
Precision Instrumentation Amplifier AD8422 ARZ Analog Devices USA Signal amplification

These are just a few of the many diverse components identified by the Directorate in the 107. In terms of the findings from Shahed-136, most memory chips, RF transceivers, digital signal processors and microcircuits come from either Texas Instruments, Xilinx Inc. (AMD), or Analog Devices’ ‘Maxim Integrated Products’ – all US-based firms. The project also informed50 most recently, and perhaps most strikingly, that an Nvidia Jetson Orin Nano Developer Kit was found inside the 136’s MS001 variant (See Table 4). It is an AI-based computer module capable of performing 67 trillion operations per second, and is commercially available for a price of US$ 249.51

Table 4

75+ Components of Shahed-136/ Geran-2-MS001 (As identified by GUR Ukraine on the ‘War Sanctions’ Portal)

Core Processing & Control

Component Type Component Name / Model Manufacturer Country of Origin Notes
Schmitt-Trigger (Memory) ATMEL207 24C1024W S127 Atmel (Microchip Technology) USA Configuration memory storage
Programmable Logic Device (PLD) XC6SLZ45 CSC484DIV2217 0670311A 21 TAIWAN Xilinx Inc. (AMD) USA FPGA for logic implementation; Production date: May (17 week) 2022
Digital Signal Processor A1GHZ DSP TMS 320C6455CTZ S721-26ZYCG7 2005 TI CTZ G1 Texas Instruments USA High-performance signal processing
Microcontroller 32-bit STM32G070CBT6 GQ20X259R CHN GQ 226 STMicroelectronics Switzerland ARM Cortex-M0+ processor
Microcontroller 32-bit STM32F103C8T6 99092 0493 MYS 99 149 STMicroelectronics Switzerland ARM Cortex-M3 processor
Digital Signal Processor TMS320 F28335PGFA CA-2AAFTMW G4 Texas Instruments USA Flight control signal processing
Microcontroller (Unspecified ARM) ARM model - exact type not fully marked STMicroelectronics Switzerland General control processor

Memory & Storage

Component Type Component Name / Model Manufacturer Country of Origin Notes
Memory Chip (DRAM) IMH22 D9MDR Micron Technology USA Working memory for processing
Memory Chip (Flash) FL512SAVFR1 2500006 A 11 SPANSION Spansion (Cypress Semiconductor, Infineon Technologies) USA Non-volatile storage
Memory Chip (EEPROM) ATMLH835 64DM CN 183548K Atmel (Microchip Technology) USA Configuration/firmware storage

Power Management & Regulation

Component Type Component Name / Model Manufacturer Country of Origin Notes
Voltage Stabilizer AMS1117 1.8 2128 Monolithic Power Systems USA 1.8V output; Production date: July (28 week) 2021
Voltage Stabilizer AMS1117 3.3 2220 Advanced Monolithic Systems Inc. USA 3.3V output; Production date: May (20 week) 2022
Linear Regulator 314 3370 B33992 Linear Technology Corporation (Analog Devices) USA Voltage regulation
Linear Stabilizer 311 1763 Linear Technology Corporation (Analog Devices) USA Power supply conditioning
DC/DC Module 2605Y Umodule №87323 2233 Linear Technology Corporation (Analog Devices) USA Isolated power conversion; Production date: August (33 week) 2022
Linear Regulator S15 H100 GE227303 STMicroelectronics Switzerland Fixed voltage output
Linear Voltage Regulator GN LF33A GK8X3404 STMicroelectronics Switzerland 3.3V regulation
Step-down Converter 5450 TI 0B4 ZE9RG4 Texas Instruments USA Buck topology power supply

Signal Conditioning & Communication

Component Type Component Name / Model Manufacturer Country of Origin Notes
Transceiver (RF) AXSEM AX5042-1 0938AB Axsem AG (ON Semiconductor) Switzerland Sub-GHz transceiver
Transceiver (Serial) ADM3307 EARUZ #2015 Analog Devices USA RS-232 to 3.3V translator; Production date: April (15 week) 2020
Linear Driver B367 ARUZ #017 Analog Devices USA Line driver for signal transmission
RS-232 Driver GF589 ST3232B CHN248 STMicroelectronics Switzerland Multi-channel serial driver
10/100 Ethernet Transceiver LAN8742A SMSC 8742A-i 319D6TA B-TW Microchip Technology Inc. USA Ethernet PHY for data link
CAN Bus Transceiver VP230 28M AOG9G4 Texas Instruments USA CAN protocol communication
16-bit Transceiver LVT16245B BF557 02 UnG0707B NXP Semiconductors Netherlands Logic-level translation

Analog & Mixed-Signal

Component Type Component Name / Model Manufacturer Country of Origin Notes
Microcircuit MF243EI 2AK G4 A1D4 Texas Instruments USA Mixed-signal IC
Microcircuit MxFE Analog Devices USA RF transceiver IC
Transistor 031N08N5 GAH218 Infineon Technologies Germany N-channel MOSFET; power switching
Transistor FDS6675BZ GMAASI ON Semiconductor (ONSEMI) USA P-channel MOSFET
Transistor FR5305 P227D FH 56 International Rectifier (Infineon Technologies) USA Power MOSFET
MOSFET Driver TC4428E 0A 1904 3C5 Microchip Technology Inc. USA MOSFET gate driver

Logic & Digital Gates

Component Type Component Name / Model Manufacturer Country of Origin Notes
Assembly of Inverters 26AF04M HCT04 G4 Texas Instruments USA Hex inverter logic gates
10-channel General-Purpose FET Bus Switch SN74CB3T3384 KS384 13K G4 C7SQ Texas Instruments USA Analog multiplexer/switch
Comparator 6562E 305C3K Microchip Technology Inc. USA Analog comparator

Data Conversion

Component Type Component Name / Model Manufacturer Country of Origin Notes
Analog-to-Digital Converter (24-bit) ADS122U 87K G4 A8R8 Texas Instruments USA High-resolution ADC

Sensing & Measurement

Component Type Component Name / Model Manufacturer Country of Origin Notes
10/100BASE-T Transformer HX1188NL 2322 M CHINA Pulse Electronics Corporation USA Ethernet isolation transformer; Production date: June (22 week) 2023

Computer Module (Advanced Variant)

Component Type Component Name / Model Manufacturer Country of Origin Notes
AI Computer Module NVIDIA Jetson Orin Nano Developer Kit Nvidia USA 67 trillion operations/second; Machine vision capable; Commercial price ~USD 249

External/ Subsystem Components

Component Type Component Name / Model Manufacturer Country of Origin Notes
Video Stream Capture Unit EZCAP USB3.0 AHD Video Capture Shenzhen ForwardVideo Technology Co., Ltd China Real-time video recording (MS001 variant)
Data Transmission Unit TX-RSD-902-A3 Manufacturer not specified Unknown Datalink subsystem
VHF Data Link Unit VDL-RSD-943F-A3 Manufacturer not specified Unknown VHF frequency data transmission

Systems-Level Components (Iranian-Designated)

Component Type Component Name / Model Manufacturer Country of Origin Notes
Satellite Receiver NASIR Unidentified Iran GNSS receiver unit
Inertial Navigation System SADRA Unidentified Iran INS/IMU integration
Air Pressure Measuring Unit AIRDATA COMPUTER (ADC) Unidentified Iran Altitude/airspeed measurement
Power Distribution Unit (PDU) Not named Unidentified Iran Electrical power management
Flight Controller Not named Unidentified Iran Navigation & flight control computer

While the Jetson Orin is capable of providing “machine vision” by allowing the drone to make decisions based on a pre-loaded, live feed processed using AI/ML, as editions of the 136/Geran-2 have evolved, the Russian series ‘E’ has shifted from a fire-and-forget to a remotely piloted drone. This series hosts another52 critical Chinese component – the TS130C-01 optical camera produced by Chengdu Honpho Technologies. This forward-facing, visible-light camera in the nose transmits a live video feed to an operator, enabling them to take a call on completion of the kill chain.

A New War Reality

The emergence and persistence of the Shahed drone offer vital lessons for India and the broader international community. To begin with, the drone’s success lies not in technological sophistication but in the building of an ecosystem and an economy. At US$ 20,000-50,000 per unit, with reported production capacities of 400 per day in Iran and 5,000 per month in Russia, this platform challenges the traditional logic of air defence.

For India, which faces two potential adversaries with technologically-frontier capabilities and production advantages, the missile defence architecture requires urgent rethinking to tackle saturation, kamikaze and swarm attack scenarios. In this regard, while the hard-kill ‘Bhargavastra’ system,53 equipped with micro-missiles, is a valuable addition to the Indian armed forces, a soft-kill system is also necessary to deploy a wide spectrum of electromagnetic and cyber capabilities to bring drones down.

Secondly, Iran’s feats in dual-use component deployment and reverse-engineering processes, despite widespread UN-backed as well as unilateral Western sanctions, are major lessons. For India, there is a notable takeaway – that domestic indigenous capability in critical components is non-negotiable.

Of course, there is a bureaucratic outcome of eminence in Tehran’s use of its history and experience. The closed-feedback loops between buyers and sellers of its drones, the quick adaptation from operational experiences, and the impetus provided by the ever-hanging sword of American or Israeli strikes – pushed the Supreme National Security Council and the IRGC to take urgent measures to scale drone operations and production. All of it is also prompted by a history of engagement in conflict with Iraq, Israel, and the US. India must find the motivation to adapt to the changing rules of warfare without necessarily needing a crisis.

Acknowledgements: The author is grateful to Aditya Ramanathan for his valuable research guidance and feedback.

Footnotes

  1. Anushka Saxena, “Tracking Iran War Weapons & Attacks Daily,” GitHub, n.d., Link.↩︎

  2. Justin Bronk and Jack Watling, “Mass Precision Strike: Designing UAV Complexes for Land Forces,” RUSI and Wilson Center Report, April 2024, Link.↩︎

  3. “Shahed 136 Drone Engine,” Scribd, 2026, Link.↩︎

  4. “Military Power Publications: UAV Book,” US Defense Intelligence Agency, August 2023, Link.↩︎

  5. “Shahed-136 Suicide Drone: Iranian Loitering Munition,” Iran Press, December 17, 2022, Link.↩︎

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  9. John Hardie on X, July 21, 2023, Link.↩︎

  10. Seevali Abeysekera, “Shahed-136: Iran’s Cheap Drone That Changed Warfare,” Eurasia Review, March 31, 2026, Link.↩︎

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  13. “Private Companies Propelling Iran’s Drone Industry,” Iranian Watch, November 29, 2023, Link.↩︎

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  15. IndiaToday on X, March 21, 2026, Link.↩︎

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  18. “Defence Intelligence Releases Data on Russia’s Active Use of Shahed-107 Drones,” Odessa Journal, November 25, 2025, Link.↩︎

  19. Vadim Kushnikov, “Iran Officially Unveils Shahed-238,” Militarnyi, November 20, 2023, Link.↩︎

  20. Evgeny Antonov, “Shahed-238 Export Price and Capabilities,” Re-Russia Analytics, July 17, 2025, Link.↩︎

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  22. “Operation Praying Mantis,” US Naval History and Heritage Command, September 20, 2023, Link.↩︎

  23. Dominika Kunertova, “The Iran Conflict Edges the World Closer to a New Drone Arms Race,” Bulletin of Atomic Scientists, March 17, 2026, Link.↩︎

  24. Robin Pagnamenta, “The Boom in Remote-Controlled Death,” The Observer, March 5, 2026, Link.↩︎

  25. Russia Mass Produces Shahed Drones Without Iran, Uses Chinese Parts,” The New Voice of Ukraine, March 5, 2026, Link.↩︎

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  40. Kimberly Donovan and Emily Ezratty, “From Drones to Rocket Fuel: China and Russia Are Helping Iran Through Supply Chains,” Atlantic Council Dispatches, March 25, 2026, Link.↩︎

  41. “Iran Claims Capture of US Drone,” Al Jazeera, December 4, 2012, Link.↩︎

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]]> Defence Geostrategy Iran https://takshashila.org.in/content/publications/Shahed-Iran-Drone-Strategy-14042026.html Mon, 13 Apr 2026 18:30:00 GMT Trump is Blockading the System America Built https://takshashila.org.in/ Geostrategy United States Iran https://takshashila.org.in/ Mon, 13 Apr 2026 18:30:00 GMT Was Iran About to Get Nuked? https://takshashila.org.in/ Iran West Asia https://takshashila.org.in/ Mon, 13 Apr 2026 18:30:00 GMT Narayan Ramachandran https://takshashila.org.in/content/blogs/20260410-Toll-Baaje-Toll.html document.addEventListener("DOMContentLoaded", function () { const titleBlock = document.getElementById("title-block-header"); const contentBlock = document.getElementById("quarto-content"); const hasTitle = titleBlock && titleBlock.querySelector("h1"); if (titleBlock && !hasTitle) { titleBlock.remove(); return; } // Strip " | Day N of Operation ..." suffix from bulletin titles if (hasTitle) { hasTitle.textContent = hasTitle.textContent.replace(/\s*\|\s*Day\s*\d+.*/i, '').trim(); } if (titleBlock && contentBlock) { contentBlock.parentNode.insertBefore(titleBlock, contentBlock); } });

This catchy tune from a quarter century ago has infected my brain. The contemporized lyrics would read “Dumb Dumb Toll Baaje, Toll Baaje, Toll”.

See, now it has infected you too.

And so, after 2,400 sorties, 3,000 strikes, the downing of an “undetectable” F‑15E, the loss of a KC‑135 Stratotanker, 1,200 confirmed targets destroyed, 2 carrier groups, 13 destroyers and 45,000 personnel deployed, and $30 billion in expenditure, we’re left with $100 oil and a $1 toll.

Iran seeks to impose this toll on each barrel of oil that transits the Strait of Hormuz. A Very Large Crude Carrier’s (VLCC’s) capacity varies slightly by ship but most modern ships carry about 300,000 metric tonnes of crude oil which is equivalent to between 1.8 and 2.2 million barrels of crude oil. The reason for this range is that the actual carrying capacity depends on whether the crude oil is “light” or “sour”. The terms light and sour describe two different qualities of crude oil – density and sulphur content. These are important determinants of refining cost, yield and market value.

And so, a typical tanker would have to pay approximately $2 million of toll to transit the Strait of Hormuz. To put that in perspective, the insurance cost of transit from the Persian Gulf to Mumbai under normal circumstances is about $400,000. This is typically made up of three components 1) Hull and Machinery insurance 2) Protection and Indemnity insurance and 3) War-risk insurance. Yes, even before the current crisis every ship was paying a certain amount of insurance for the risk that the Strait of Hormuz could be shut down. Even in normal times, the war-risk component is the highest of the three components of insurance cost. The total insurance cost during normal times is about $400,000. The war-risk insurance cost either shoots up or is unavailable during times of conflict. When available, additional war-risk insurance today is about 8-10x of normal at about $1,000,000. Extreme war-risk moments could raise costs further upto about $10,000,000. These are quite rare and situation specific.

For a normal voyage costs beyond insurance include those for fuel, ports, crew and charter hire. These costs including that for insurance are about $1 to $1.2mm per Persian Gulf voyage.

The toll charges that could amount to $2 million are therefore a meaningful addition to costs of voyage that could result in a tripling of total costs from the normal. If the toll does stay, it will most likely be passed on to the crude oil cost per barrel.

An interesting twist to this is that Iran is seeking to levy this toll in Crypto currency. This sets up a complexity in the mechanics of payment for institutional companies that may not be used to paying any vendors in crypto. The toll fee could also be very volatile unless the cryto used is some form of stablecoin. It is interesting that even when the country seeks to go beyond the dollar, the structural pricing is stated in dollar terms.

Hungama, Hungama, Ho Gaya Hangama

Toll Baaje Toll.

]]> Iran Geoeconomics https://takshashila.org.in/content/blogs/20260410-Toll-Baaje-Toll.html Thu, 09 Apr 2026 18:30:00 GMT Three Things May Happen At The End Of The 14-Day Ceasefire (Or Earlier) https://takshashila.org.in/ Geostrategy United States Iran https://takshashila.org.in/ Thu, 09 Apr 2026 18:30:00 GMT Brig Anil Raman https://takshashila.org.in/content/blogs/US-IRAN-A2-AD.html document.addEventListener("DOMContentLoaded", function () { const titleBlock = document.getElementById("title-block-header"); const contentBlock = document.getElementById("quarto-content"); const hasTitle = titleBlock && titleBlock.querySelector("h1"); if (titleBlock && !hasTitle) { titleBlock.remove(); return; } // Strip " | Day N of Operation ..." suffix from bulletin titles if (hasTitle) { hasTitle.textContent = hasTitle.textContent.replace(/\s*\|\s*Day\s*\d+.*/i, '').trim(); } if (titleBlock && contentBlock) { contentBlock.parentNode.insertBefore(titleBlock, contentBlock); } });

In past wars, commanders worried about what would happen after crossing the line of departure. In Operation Epic Fury, the line of departure itself became contested before a single Marine crossed it. Shipping lanes were closed, Gulf partners were under pressure, and a Houthi missile had already underscored the point. The path to the battlefield had become the battlefield. That is not an accident of geography. It is the product of deliberate design. My piece published this week in War on the Rocks makes the case that Iran has done something analytically underappreciated: it has adapted the operational logic of China’s anti-access, area denial strategy to its own resource constraints and extended it through proxy forces across two of the world’s most critical maritime chokepoints. The result is a denial architecture that is incomplete by Chinese standards but sufficient for Iran’s strategic purposes, and one that existing scholarship on A2/AD has not fully grappled with.

Not China, But Not Improvised Either The foundational literature on anti-access, area denial established the PLA’s approach as the analytical benchmark: an integrated, high-end, all-domain system-of-systems architecture seeking comprehensive exclusion. Gunzinger and Dougherty’s Outside-In (2012) correctly identified that Iran would pursue something structurally different, an asymmetric hybrid mixing advanced technology with guerrilla tactics. What the current conflict has revealed is that the reality is more architecturally coherent than even that framing anticipated. Iran has built a three-layer denial architecture. Each layer is distinct. Each is imperfect. Together, they compound to something that has materially degraded the U.S. ability to project decisive force into the Persian Gulf theater.

Layer One: Strike the Base Before the Fight Begins The most upstream form of anti-access strikes the infrastructure from which operations begin. Iranian missile and drone strikes have systematically targeted U.S. military installations across the Gulf: Port Shuaiba and Ali Al Salem Air Base in Kuwait, the early-warning radar at Al Udeid in Qatar, fleet communications at Fifth Fleet headquarters in Bahrain, and Prince Sultan Air Base in Saudi Arabia, struck repeatedly, wounding over 300 American servicemembers and killing 13 across the campaign. The target selection is analytically precise. These are attacks on command nodes, fuel infrastructure, refueling aircraft, and early-warning systems, the sustainment architecture on which U.S. power projection depends. The basing infrastructure of U.S. Central Command was designed for a threat environment that no longer exists. Iran’s campaign has converted that inherited geography from a strategic advantage into a sustained vulnerability. Every capability degraded at the base layer means a weakened force reaching the chokepoint, and arriving further degraded in the inner theater.

Layer Two: Dual Chokepoints and the Denial Arc Iran’s outer anti-access layer operates across two interlocking straits. The Strait of Hormuz, formally declared closed to enemy nations, is the primary instrument. At 33 kilometers at its narrowest navigable point, coastal missile batteries can hold virtually all transit traffic at risk simultaneously. Iran’s mine inventory extends this: once laid, clearance consumes time regardless of whether any individual mine detonates. The Bab el-Mandeb is the second instrument. Houthi operations since late 2023 have demonstrated that sustained disruption is operationally achievable with Iranian-derived systems, with the Toofan and Tankil anti-ship ballistic missiles engaging vessels at ranges exceeding 1,500 kilometers. Hormuz constrains entry into the Gulf. Bab el-Mandeb constrains the approach to Hormuz. Force planners must account for both simultaneously, because there is no single point of failure to concentrate against. The attempted strike on Diego Garcia extends this logic to the Indian Ocean itself, reaching for an anti-access envelope covering the primary power-projection node for all U.S. naval operations across the Arabian Sea approach to the Gulf. That such a strike was attempted at all, almost certainly enabled by external targeting intelligence, establishes a key analytical point: the outer boundary of Iran’s anti-access envelope is defined by what Russia and China can see, and what Iran can reach with their coordinates.

Layer Three: Area Denial Inside the Gulf Within the Persian Gulf itself, geography substitutes for much of the intelligence burden that limited Iranian surveillance cannot carry. A carrier strike group in the open Pacific requires space-based surveillance and real-time data fusion to track. Inside waters averaging 50 meters depth, with maximum width of roughly 340 kilometers, overlooked by Iranian coastal positions on multiple axes, it presents a fundamentally different problem. The compression dramatically reduces the detection and tracking burden. The IRGC Navy, organized explicitly around asymmetric denial, fast attack craft, shallow-water submarines, mine warfare, swarming tactics, and mobile coastal missile batteries, is a combined-arms denial system. Iranian strikes on Bubiyan Island, Kuwait’s northernmost maritime position, targeting amphibious assets and landing craft with Ghadr cruise missiles and one-way attack drones, demonstrate area denial in its most operationally precise form: direct engagement of the instruments of forward maneuver. The area denial layer accumulates cost regardless of whether individual engagements succeed. A cleared mine consumed time. A defeated swarm depleted interceptors. A missed drone maintained the risk premium. In a geographically compressed theater where Iran holds the interior lines, friction is itself the strategic effect.

The Missile Foundation and the External Augmentation Underlying all three layers is a missile arsenal, mobile, solid-fueled, increasingly precise, and resistant to suppression by airpower alone, that constitutes the operational foundation of the entire architecture. Achieving air superiority over Iran does not silence coastal missile batteries or neutralize mobile launchers dispersed across mountainous terrain and hardened tunnel networks. Suppression requires persistent ISR to locate relocating launchers and repeated rapid strikes before they move, while pre-launched rounds continue to their targets regardless. The external enablement dimension is equally significant. Russian satellite imagery via the Kanopus-V/Khayyam constellation provides optical and radar data Iran’s own constellation cannot match. Chinese electronic warfare support and encrypted BeiDou navigation have reshaped Iran’s battlefield awareness. Regional human intelligence networks across Gulf states, Iraq, Lebanon, and Yemen provide targeting context that partially substitutes for persistent electronic surveillance. Collectively this raises Iran’s effective targeting capability well above its indigenous ceiling, enough to make the anti-access layer episodically precise and politically consequential.

The Strategic Logic: Exhaustion, Not Control Iran’s strategy depends on ensuring that the cost of operating within the battlespace rises continuously across all three layers simultaneously, and that the timeline for decisive resolution extends beyond what U.S. political will can sustain. With oil above $110 per barrel, stock markets declining, and an administration that has already extended its Hormuz deadline multiple times, the economic and political pressure is registering exactly where Iran intended. The three-layer structure matters for how responses are calibrated. Suppressing area denial within the Gulf does not resolve the chokepoint problem. Clearing the chokepoints does not restore degraded basing infrastructure. Striking Houthi missile capacity reduces Red Sea pressure without dismantling the architecture, because the architecture is a set of strategic relationships, a targetable system only in part. The United States can still reach the fight. The question Iran is betting on is whether it can get there fast enough, with enough left, to conclude it.

]]> Iran United States Geostrategy https://takshashila.org.in/content/blogs/US-IRAN-A2-AD.html Wed, 08 Apr 2026 18:30:00 GMT