MUSIC subspace pursuit algorithm for DOA estimation with single snapshot

Ruoshi Cao; Yongbo Zhao; Di Gao

doi:10.1117/12.3023210

28 March 2024 MUSIC subspace pursuit algorithm for DOA estimation with single snapshot

Ruoshi Cao, Yongbo Zhao, Di Gao

Proceedings Volume 13091, Fifteenth International Conference on Signal Processing Systems (ICSPS 2023); 130910B (2024) https://doi.org/10.1117/12.3023210
Event: Fifteenth International Conference on Signal Processing Systems (ICSPS 2023), 2023, Xi’an, China

Abstract

Direction of arrival (DOA) estimation on uniform linear array with single snapshot has always been a hot topic in radar signal processing. The traditional subspace class estimation methods, such as multiple signal classification (MUSIC), and sparse recovery algorithms, such as subspace pursuit (SP) algorithm, are suitable for different situations, meanwhile have certain requirements for observation data and signal-to-noise ratio (SNR). Combining the advantages of these two methods, a novel MUSIC subspace pursuit (MSP) algorithm is proposed in this paper. Firstly, an error evaluation function of the residual signal is constructed. The angles measured by both methods are replaced and selected one by one. And then, the framework of the greedy algorithm is iteratively applied until convergence. In this algorithm, the subspace information of the signal is added to the greedy algorithm, and more conditions are used to improve the angle measurement accuracy with single snapshot. Simulation results illustrate that the proposed MSP algorithm outperforms the SP and MUSIC algorithms at different SNR levels and it keeps the faster reconstruction speed of SP algorithm.

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

Citation Download Citation

Ruoshi Cao, Yongbo Zhao, and Di Gao "MUSIC subspace pursuit algorithm for DOA estimation with single snapshot", Proc. SPIE 13091, Fifteenth International Conference on Signal Processing Systems (ICSPS 2023), 130910B (28 March 2024); https://doi.org/10.1117/12.3023210

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