Intensity filtering of acoustic sensor signals for multi-target tracking

Abstract

This paper addresses tracking of closely spaced moving vehicles by using passive acoustic signals. A multiple signal classification algorithm has been applied to estimate the bearing of targets from acoustic sensor signals. Field data from several sensor arrays have been used to reduce estimation variance in intensity filtering, which is performed on the bearing data with a sequential Monte Carlo method. Performance of the algorithm in terms of estimation of number of targets and their tracks will be presented using actual field data.