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SOURCE: IDRW.ORG

The Indian Army is turning to private sector ingenuity to enhance the anti-drone capabilities of its T-90 Bhishma main battle tanks, a critical component of its armored fleet. With over 1,200 T-90s in service and hundreds more in production, the Army aims to integrate an autonomous anti-drone system into the tanks’ existing remotely operated 12.7 mm anti-aircraft gun (AAG), currently operated manually by the tank commander. This ambitious upgrade seeks to counter the rising threat of low-speed aerial targets, such as drones, by leveraging advanced technology to achieve 360-degree autonomous detection, recognition, and identification (DRI) of targets, alongside the development of specialized fragmentation rounds.

The T-90’s current setup includes a 12.7 mm NSV heavy machine gun mounted on the turret, remotely controlled via the commander’s TKN-4S Agat-M sight, part of the 1A45 fire control system (FCS). While this configuration, indigenized and improved by Indian firms over its Russian origins, allows the commander to observe and engage aerial threats, the process remains manual—relying on human detection, aiming, and firing. This limitation has become a liability in modern warfare, where drones and loitering munitions, as demonstrated in conflicts like Ukraine, pose a persistent and agile threat to armored units. The Army now envisions a fully autonomous solution to transform the T-90 into a drone-repelling powerhouse.

The proposed system would integrate with the existing 12.7 mm AAG, enabling 360-degree coverage to detect, recognize, and identify low-speed aerial targets without constant human intervention. Key requirements include an AI-based algorithm for target DRI and tracking, with a detection range of 5,000 meters, recognition range of 3,000 meters, and identification range of 2,000 meters. Once a threat is identified, the system would alert the tank crew, allowing the commander to authorize engagement or override the system as needed. This autonomous capability aims to reduce reaction time, enhance situational awareness, and free the crew to focus on primary combat tasks.

A critical element of the upgrade is the development of new fragmentation rounds tailored for anti-drone roles, compatible with the 12.7 mm AAG. Unlike standard armor-piercing or high-explosive rounds, these fragmentation munitions would disperse shrapnel upon detonation, increasing the probability of neutralizing small, agile targets like drones. A safety arming feature—likely a proximity fuse or timed detonation mechanism—would ensure the rounds activate only at a safe distance from the tank, protecting the vehicle and nearby friendly forces. This innovation mirrors global trends, such as India’s recent efforts to upgrade Soviet-era ZU-23 and Schilka systems with proximity-fused anti-drone ammunition.

This upgrade addresses a glaring vulnerability exposed in modern conflicts: tanks’ susceptibility to drones and top-attack munitions. While the T-90 Bhishma Mk-3 boasts advanced Kontakt-5 explosive reactive armor and a digital ballistic computer, its passive defenses fall short against aerial threats. The Army’s broader modernization efforts, including plans for Active Protection Systems (APS) like Rafael’s Trophy, indicate a multi-layered approach, but the autonomous AAG solution offers a faster, cost-effective interim fix. With detection out to 5,000 meters, the system could engage drones well before they deploy weapons like the Javelin or FPV munitions seen in Ukraine.

The technical demands are steep. The AI algorithm must distinguish drones from friendly aircraft or clutter (e.g., birds) across a 360-degree field, a task requiring robust machine learning trained on diverse aerial signatures. The 3,000-meter recognition and 2,000-meter identification ranges suggest reliance on high-resolution EO/IR sensors, potentially paired with a lightweight radar akin to the EL/M-2133 used in Trophy APS. Integrating this with the T-90’s existing FCS, while ensuring power and weight constraints are met, will test private sector innovation.

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