DOA estimation based on soft sparse representation using weighted variance
hu xie, Hongxing Dang, Xiaomin Tan · 2024
An estimation method for the direction of arrival (DOA) is proposed on the basis of a sparse representation method which tends to minimize the weighted variance. We relaxes the rigid constraints that the desirable sparse solution should have the minimum number of nonzero elements and provide a new diversity measure of sparsity which termed as soft sparsity. The often-used re-weighted iteration technique is exploited to find the new-defined sparse solution. More importantly, this method can find and estimate the DOA of the relatively weak sources. Experimental results validate the good performance of the proposed method.