A Modified Localization Technique for Pinpointing a Gunshot Event Using Acoustic Signals

This paper proposes a method for localizing a gunshot event using four acoustic sensor nodes mounted at the four corners of a rectangular working area. Each of these nodes involves three sensors to acquire acoustic signals of any gunshot inside the working area. The approach analyzes individual signals received by the nodes to identify sound events using false alarm probability and determine their emission directions exploiting a minimum mean square error estimator and the time difference of arrival of the events. The gunshot location is the quadrilateral center of four crossing points resulting from pairs of adjacent event emission directions. For evaluating the proposed method, a signal including ten real gunshots recorded by a nearby acoustic sensor is delayed and attenuated according to a theoretical wave propagation model to create various signal patterns, which simulates signals received by the installed sensor nodes. Furthermore, the Gaussian noise is added to the simulated signals to emulate the influence of wave propagation environment. This article also implements some mechanisms to compute the time difference of arrival for comparison. They are comprised of the first crossing of threshold and signal, maximum amplitude, Akaike’s Information Criterion, and the cross-correlation function. Hence, one of them can be selected for a real application. Experimental results show that the proposed method achieves high accuracy of gunshot localization. © 2020, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.