Weak Underwater Acoustic Target Detection and Enhancement with BM-SEED Algorithm

Bearing time record (BTR) is widely used in the field of passive sonar information processing for target detecting and tracking. One of its challenges is to obtain high-resolution beamforming power spectral to facilitate the directions estimating of arrivals, namely DOA estimating. This paper proposes a new algorithm framework Block Matching - Subband Extrema Energy Detection (BM-SEED) to supplement the resolution and enhance the weak targets of BTRs. It extracts the peak features of target trajectories within the conventional beamforming (CBF)-based BTRs by using an improved sub-band peak energy detection (SPED) algorithm, and then enhances the weak targets and suppresses the false-alarm targets through time-spatial autocorrelation analysis. Simulations and sea-trial data evaluations demonstrate that the method of this paper can enhance weak targets, eliminate the interferences of false targets and improve the resolution of BTR targets to 1 degree under -20 dB.

Automated summary

This paper proposes a new algorithm framework, BM-SEED, to enhance the resolution and improve the weak target detection capability of BTRs. By using an improved sub-band peak energy detection algorithm, it extracts the peak features of target trajectories in CBF-based BTRs and enhances weak targets through time-spatial autocorrelation analysis. Simulations and sea-trial data evaluations show that this method can improve the resolution of BTR targets to 1 degree with a signal-to-noise ratio of -20 dB.