Zhao Lin, Xu Jian, Ding Jicheng, Liu Aimeng, Li Liang
College of Automation, Harbin Engineering University, Harbin, Heilongjiang, China.
PLoS One. 2017 Jul 27;12(7):e0181838. doi: 10.1371/journal.pone.0181838. eCollection 2017.
Multipath signal is often considered an interference that must be removed. The coherence between multipath and direct component makes it difficult to use conventional direction-of-arrival (DOA) estimation methods in a smart antenna system. This study demonstrates a new multipath signal DOA estimation technique. Unlike the common methods, without decoherence preprocessing, the proposed algorithm first apply a complex fast independent component analysis (cFastICA) algorithm to obtain the steering vectors with multipath information that corresponds to each source signal. Then, according to the special structure of the obtained steering vectors and spatial sparsity of the multipath signal components, the algorithm uses the solution of the sparse signal reconstruction problem in the compressive sensing (CS) theory, and the DOA estimation of the multipath signal is translated into an l1 norm minimization problem. Finally, we search the space spectrums to acquire the DOAs for each direct component and multipath component. Comparative simulation tests and analysis prove the effectiveness of the proposed algorithm in estimation accuracy in underdetermined conditions.
多径信号通常被视为必须消除的干扰。多径与直达分量之间的相干性使得在智能天线系统中难以使用传统的到达方向（DOA）估计方法。本研究展示了一种新的多径信号DOA估计技术。与常用方法不同，该算法无需去相干预处理，首先应用复数快速独立分量分析（cFastICA）算法来获取与每个源信号对应的包含多径信息的导向矢量。然后，根据所获得的导向矢量的特殊结构以及多径信号分量的空间稀疏性，该算法利用压缩感知（CS）理论中稀疏信号重构问题的解，将多径信号的DOA估计转化为l1范数最小化问题。最后，搜索空间谱以获取每个直达分量和多径分量的DOA。对比仿真测试与分析证明了该算法在欠定条件下估计精度方面的有效性。
