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

Abstract

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 (stopband) 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.