Gunshot acoustic event identification and shooter localization in a WSN of asynchronous multichannel acoustic ground sensors

Gunshot acoustic localization for military and civilian security systems has long been an important topic of research. In recent years the development of Wireless Sensor Network (WSN) systems of independent Unmanned Ground Sensors (UGS) performing distributed cooperative localization has grown in popularity. This paper considers a shooter localization approach based on gunshot Shockwave (SW) and Muzzle Blast (MB) event time and Direction of Arrival (DOA) information. The approach accounts for acoustic events Not-of-Interest (NOI), such as target hit noise, reflections and background noise. UGS perform gunshot acoustic event detection and DOA estimation independently; the information regarding every detected shot instance is sent through the WSN to the fusion node, which performs event identification and calculates the shooter’s position. The paper presents a solution to identifying SW and MB among NOI events at the stage of information fusion. The considered approach treats the information gathered from different UGS separately, and thus does not require precise synchronization between the UGS. For DOA estimation, an algorithm designed for circular microphone arrays is proposed and compared with the SRP-PHAT localization algorithm. It is shown to provide adequate DOA estimates, while being more computationally effective. The proposed shooter localization approach is tested on real signals, acquired during three live shooting experiments. It is shown to succeed in localizing the shooter’s position with a mean accuracy of 0.87 m for 30 shots at the range of 35 m, and just above 7 m for 37 shots at the range of 100 m.