Target direction estimation using coprime array compressive sensing under non-Gaussian noise

In the direction of arrival (DOA) estimation, the background noise is usually assumed to be Gaussian noise. However, in underwater acoustic environments, the probability density function (PDF) of the noise has a non-Gaussian distribution, which leads to false peaks and background noise in DOA estimation. In this paper, underwater noise that does not follow Gaussian distribution is modeled as an α-stable distribution, and data weighting is used to preprocess the signal. Then compressive sensing method is applied in a coprime array to estimate the DOA of a broadband signal. Simulations are conducted on an 8-element coprime array with improved algorithm, and the results show that the method can accurately estimate DOA while reducing the number of pseudo peaks. The processing results of lake test data show that compressed sensing DOA estimation based on data weighting in coprime arrays can reduce false peaks, enhance target detection capability, and have better effectiveness and practicality.