Compressive Self-Noise Cancellation in Underwater Acoustics
2022 Sensor Signal Processing for Defence Conference (SSPD)(2022)
Abstract
The purpose of sonar is to detect the stealthy target in shallow water. The main barrier to locating the target is sonar’s self-noise. Existing subspace-based noise suppression methods typically employ eigenanalysis-based methods involving high computational complexity. Recent approaches based on compressed sensing (CS) or sparse representations (SR) are computationally efficient. It is not straightforward to extend existing CS/SR-based methods for self-noise cancellation as, first, the energy of interference is much higher than the target, and second, it also exhibits similar sparsity properties. This work presents a novel method to combine the advantages of a subspace-based noise cancellation approach with low complexity of working with fewer CS measurements. Both target recovery and self-noise cancellation are done in the compressive domain only. Experimental results demonstrate the robustness of the proposed approach for both narrowband and broadband targets at very low signal-to-interference-noise (SINR).
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Key words
Self-noise cancellation,compressed sensing,underwater acoustics,sensor array
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