Wideband sparse spatial spectrum estimation using matrix filter with nulling in a strong interference environment

摘要

Wideband direction of arrival (DOA) estimation using a sensor array plays a fundamental role in passive sonar signal processing. Although sparsity-based DOA estimation methods can attain high resolution in the condition of few snapshots and low signal-to-noise ratio, the localization accuracy is seriously affected by strong interferences. In this paper, a matrix filter with nulling (MFN) is used to pass weak targets in sector-of-interest (passband) while attenuating the out-of-sector (stop-band) interferences by forming deep nulls toward the directions of interferences adaptively. Then, a method based on sparse spectrum fitting (SpSF) and MFN is proposed to localize closely spaced wideband signals in a strong interference environment. In comparison with the minimum variance distortionless response and SpSF, the proposed method achieves higher localization accuracy, which is verified by simulation and experimental results. (C) 2018 Acoustical Society of America.