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针对现有的Simple、Sumple等互相关类算法无法分辨多个信源的问题，结合子空间算法中的超分辨估计——Music算法，提出了基于子空间的子带相位差估计算法——Music-Simple。对Music-Simple算法的合成性能进行了仿真分析并与传统的Music算法进行对比，验证了Music-Simple算法的正确性。结果表明，Music-Simple具有分辨多个信源的能力，可以同时估计出多个信源在多个接收天线处的相位差，显著提升了对包含多个信源信号的合成性能。
Abstract：To solve the problem that existing cross-correlation algorithms such as Simple and Sumple cannot distinguish multiple sources, combined with the super-resolution estimation Music algorithm in the subspace algorithm, a sub-band phase difference estimation algorithm Music-Simple based on subspace is proposed. The synthesis performance of the Music-Simple algorithm is simulated and analyzed and compared with the traditional Music algorithm, which verifies the correctness of the Music-Simple algorithm. The results show that the sub-band phase difference estimation algorithm Music-Simple based on subspace has the ability to distinguish multiple signal sources, and can estimate the phase differences of multiple sources at multiple receiving antennas at the same time, which significantly improves synthesis performance for signals containing multiple sources.
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基本信息:
DOI：
中图分类号:V443.1
引用信息:
[1]毛飞龙,焦义文,马宏等.基于子空间的宽带信号时延差与相位差估计方法[J].无线电工程,2023,53(04):797-806.
基金信息:
北京市科技重大专项(Z181100002918004)~~