DOA estimation based on soft sparse representation using weighted variance

Hu Xie; Hongxing Dang; Xiaomin Tan

doi:10.1117/12.3040323

4 September 2024 DOA estimation based on soft sparse representation using weighted variance

Hu Xie, Hongxing Dang, Xiaomin Tan

Proceedings Volume 13259, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024); 1325934 (2024) https://doi.org/10.1117/12.3040323
Event: Fourth International Conference on Automation Control, Algorithm, and Intelligent Bionics (ICAIB 2024), 2024, Yinchuan, China

Abstract

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.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hu Xie, Hongxing Dang, and Xiaomin Tan "DOA estimation based on soft sparse representation using weighted variance", Proc. SPIE 13259, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024), 1325934 (4 September 2024); https://doi.org/10.1117/12.3040323

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