Wideband DOA Estimation Algorithms for Multiple Target Detection and Tracking Using Unattended Acoustic Sensors

摘要

The problem of detection, tracking and localization of multiple wideband sources (ground vehicles) using unattended passive acoustic sensors is considered in this paper. Existing methods typically fail to detect, resolve and track multiple closely spaced sources in tight formations, especially in the presence of clutter and wind noise. In this paper, several existing wideband direction of arrival (DOA) estimation algorithms are extended and applied to this problem. A modified version of the Steered Covariance Matrix (STCM) algorithm is presented that uses a two-step search process. To overcome the problems of existing DOA estimation methods, new wideband versions of the narrowband Capon beamforming method are proposed that use various algorithms for combining power spectra from different frequency bins. These methods are then implemented and benchmarked on a real acoustic signature data set that contains multiple ground targets moving in tight formations.