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  • 标题:Underdetermined DOA Estimation Based on Target Space Diversity
  • 本地全文:下载
  • 作者:Chen Miao ; Hui Tang ; Yue Ma
  • 期刊名称:IAENG International Journal of Computer Science
  • 印刷版ISSN:1819-656X
  • 电子版ISSN:1819-9224
  • 出版年度:2021
  • 卷号:48
  • 期号:1
  • 语种:English
  • 出版社:IAENG - International Association of Engineers
  • 摘要:In the underdetermined DOA scenario, the performance of the conventional direction of arrival (DOA) estimation algorithms often degrades greatly, in the worst case, these algorithms even fail to estimate the direction of targets. To overcome this problem, an underdetermined DOA estimation based on target space partitioning is proposed. Firstly, the IF signal of the LFMCW radar is processed by two-dimensional FFT to get target distribution information. And then the range-velocity target space is divided into several subspaces according to the targets’ distribution. In the process of partitioning, ensure that every subspace meets the overdetermined conditions. Now, various classic DOA estimation algorithms can be used. The multiple signal classification (MUSIC) algorithm is applied in this paper. Simulation results show that the method well solved the underdetermined DOA estimation problem. Under certain conditions, the distance, speed, and angle of the target can also be estimated simultaneously.
  • 关键词:LFMCW;Underdetermined DOA;the MUSIC algorithm
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