Intelligent Distributed Acoustic Data Collection and Analysis System for Large-Caliber Weapons Activity Detection

This paper introduces a intelligent system for real-time collection and analysis of acoustic data along the front line to detect and classify various large-caliber weapons used by the enemy. Each weapon produces a distinct acoustic signature, traditionally identified by experienced combatants. The proposed system uses artificial intelligence (AI) tools to automate this process by identifying types of weapons, tracking their location and movement, providing real-time warnings of potential threats, and predicting the point and time of impact. A method based on time difference of arrival (TDOA) was developed to accurately determine firing points by analyzing acoustic arrival times from multiple devices. This significantly improves the precision of locating firing positions, ensuring faster response. The system relies on a distributed network of acoustic-collecting devices and multi-layer data processing to deliver accurate and comprehensive insights. As the network grows and more data is gathered, the system's functionality and accuracy will be enhanced, offering better situational awareness and improving battlefield decision-making.