Underwater wideband coherent signals DOA estimation using sparse representation and deconvolution

Abstract

The beamforming-based direction of arrival (DOA) estimation method is widely used because of its advantages of robustness, which requires large array aperture to ensure high spatial resolution. The deconvolution beam-forming method has high-resolution DOA estimation without increasing the array aperture. However, it is based on the assumption of incoherent narrowband signals. When the signals are coherent, the high cross-term sidelobes result in large estimation errors. In this paper, a new sparse deconvolution beamforming is proposed to estimate the DOA of wideband coherent signals. First, extending the deconvolution beamforming method to the wideband case by matrix transformation. Second, solving the problem that the traditional deconvolution algorithm is not applicable to coherent signals by sparse representation. Numerical simulations and underwater experiments are presented to verify the effectiveness of the proposed method. The results show that even at low Signal-to-Noise Ratio (SNR) and blind environment parameters, the proposed method can obtain better performance compared with other coherent signals DOA estimation algorithms.