The Solid State Physics Laboratory (SSPL), a laboratory under DRDO, has invited Indian industry participation for the design and development of an indigenous Acoustic-Based Drone Detection System (ADD System) through an Expression of Interest (EoI).

The proposed system is intended to provide a passive means of detecting and identifying approaching drones by analysing their unique acoustic signatures. Unlike conventional detection solutions that rely primarily on radar or radio-frequency monitoring, the system will utilise sound-based sensing to recognise unmanned aerial vehicles.

Under the concept outlined by SSPL, incoming drone sounds will be captured using high-sensitivity microphones integrated with suitably designed parabolic reflectors. These reflectors are expected to enhance the collection of acoustic signals from greater distances, improving the system's ability to identify aerial threats.

The acquired signals will then be digitised through a Data Acquisition System (DAQ) before being processed by an advanced analytical platform. The processing architecture will incorporate Artificial Intelligence (AI) and Machine Learning (ML) algorithms capable of distinguishing drone acoustic signatures from background environmental noise and other airborne objects.

The initiative forms part of India's broader push towards strengthening indigenous counter-drone technologies as the use of unmanned systems continues to expand across military, security and civilian domains.

Acoustic detection systems can complement existing radar, electro-optical and radio-frequency sensors, particularly in scenarios where drones operate with a reduced electronic footprint or in cluttered environments.

By seeking collaboration with domestic vendors, DRDO aims to accelerate the development of a home-grown capability while expanding industry participation in advanced surveillance and defence technologies. The project also aligns with wider efforts to enhance self-reliance in critical defence systems and reduce dependence on imported counter-drone solutions.

The Acoustic-Based Drone Detection System is expected to leverage AI-enabled signal processing to improve detection accuracy, classification performance and real-time threat assessment, providing security forces with an additional layer of protection against emerging drone threats.

Agencies