数字海洋与水下攻防2026，Vol.9Issue(2)：142-150,9.DOI:10.19838/j.issn.2096-5753.2026.02.003
有限快拍条件下的MMV-OMP波达方向估计算法
MMV-OMP DOA Estimation Algorithm under Limited Snapshot Conditions
摘要
Abstract
To address the performance degradation of direction of arrival(DOA)estimation under snapshot-limited conditions in underwater acoustic environments,a sparse reconstruction method based on the multiple measurement vector(MMV)model is investigated.An extended MMV-orthogonal matching pursuit(OMP)algorithm is developed by jointly processing multi-snapshot observations and exploiting the joint sparsity of signals to achieve iterative support set refinement,thereby improving DOA estimation accuracy under low signal-to-noise ratio(SNR)conditions.Comparative simulations are conducted under varying SNR levels,and the performance is quantitatively evaluated using root mean square error(RMSE)and detection probability(DP).The results show that,with 10 snapshots and an SNR of-4 dB,the proposed algorithm improves the detection probability by approximately 2.2%and reduces the RMSE by about 1.01° compared with benchmark methods,while maintaining low computational complexity.Experimental validation based on anechoic water tank data demonstrates that the proposed algorithm produces continuous and stable DOA estimation trajectories with well-focused spectral peaks,enabling effective tracking of target direction variations.The results indicate that MMV-OMP achieves high estimation accuracy and strong noise robustness under snapshot-limited conditions,and exhibits promising potential for practical applications.关键词
水下DOA估计/快拍数受限场景/压缩感知/多快拍联合估计Key words
underwater DOA estimation/snapshot-limited scenario/compressed sensing/joint estimation of multiple snapshots分类
通用工业技术引用本文复制引用
姚添译,潘光,高若滨,于洋,袁瑀聪,闫晨红,许金鹏..有限快拍条件下的MMV-OMP波达方向估计算法[J].数字海洋与水下攻防,2026,9(2):142-150,9.基金项目
国家重点研发计划"集群组网总体设计"(2021YFC2803000,2021YFC2803001) （2021YFC2803000,2021YFC2803001）
国家留学基金管理委员会"国家建设高水平大学公派研究生项目"(202406290713). （202406290713）
