A Differential Evolution Algorithm with Neighbor-hood Mutation for DOA Estimation

• URL: http://arxiv.org/abs/2507.06020v2
• Date: Sat, 26 Jul 2025 11:56:02 GMT
• Title: A Differential Evolution Algorithm with Neighbor-hood Mutation for DOA Estimation
• Authors: Bo Zhou, Kaijie Xu, Yinghui Quan, Mengdao Xing,
• Abstract summary: Two-dimensional (2D) Multiple Signal Classification algorithm is a powerful technique for high-resolution direction-of-arrival (DOA) estimation in array signal processing.<n>We reformulate the peak-finding process as a multimodal optimization prob-lem, and propose a Differential Evolu-tion algorithm with Neighborhood Mutation (DE-NM) to efficiently lo-cate multiple spectral peaks.
• Score: 11.842677286643609
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Two-dimensional (2D) Multiple Signal Classification algorithm is a powerful technique for high-resolution direction-of-arrival (DOA) estimation in array signal processing. However, the exhaustive search over the 2D an-gular domain leads to high computa-tional cost, limiting its applicability in real-time scenarios. In this work, we reformulate the peak-finding process as a multimodal optimization prob-lem, and propose a Differential Evolu-tion algorithm with Neighborhood Mutation (DE-NM) to efficiently lo-cate multiple spectral peaks without requiring dense grid sampling. Simu-lation results demonstrate that the proposed method achieves comparable estimation accuracy to the traditional grid search, while significantly reduc-ing computation time. This strategy presents a promising solution for real-time, high-resolution DOA estimation in practical applications. The imple-mentation code is available at https://github.com/zzb-nice/DOA_multimodel_optimize.

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