UAV Swarm Detection: Countering Low-RCS Threats in Modern Warfare

The battlefield has changed. Cheap, autonomous drones flying in coordinated swarms now pose a threat once reserved for advanced missiles. Individually small and hard to see, these unmanned aerial vehicles present a very low radar cross-section, and when they arrive in numbers they can saturate defences. Detecting and tracking multiple low-RCS targets simultaneously is one of the defining challenges of contemporary air defence — and a core problem statement at the BDTS Hyderabad Strategic Colloquium 2026.

The Low-RCS Problem Explained

Radar cross-section measures how detectable an object is to radar. Consumer and military drones are often built from composites and shaped to reflect very little energy back to the sensor. A single small drone may register no larger than a bird. Now multiply that by dozens of coordinated units, each manoeuvring independently, and conventional tracking algorithms quickly lose coherence. Distinguishing genuine threats from clutter and wildlife becomes extraordinarily hard.

Sensing and Signal Processing Solutions

Effective swarm detection blends advanced sensor fusion, high-resolution radar, electro-optical and radio-frequency sensing, and intelligent signal processing. Algorithms must correlate faint returns across time, reject false positives and predict swarm behaviour. This is fertile ground for the AI, machine learning and signal-processing specialists that BDTS actively curates from India's deep-tech startup ecosystem.

Why Hyderabad, Why Now

Hyderabad is a national hub for aerospace, electronics and sensing research. By bringing precision MSMEs, deep-tech startups and Lead System Integrators together on one stage, the BDTS colloquium accelerates indigenous counter-swarm capability. Innovators who solve this problem statement gain direct access to end users, a Technical Action Report to refine their technology for military deployment, and a pathway toward the national defence supply chain.