基于区间密度的宽带ISSM相干DOA估计方法

    A Coherent DOA Estimation Method for Wideband ISSM Based on Interval Density

    • 摘要: 在低信噪比情况下,非相干信号子空间方法(ISSM)中波达方向(DOA)的估计精度容易受到不同频点DOA角度估计误差结果数据的干扰影响,而且无法解决宽带相干信号的DOA估计问题。为了解决ISSM的缺陷,文中在ISSM基础上进一步研究改进,提出了一种新的宽带相干DOA估计方法。首先,利用ISSM得到不同频点下的频率互谱密度矩阵,并对其进行解相干处理;然后,利用子空间类DOA算法计算得出各个频点的DOA估计结果;最后,利用区间密度方法对所有频点的DOA估计结果进行融合得到最终的DOA估计结果。仿真分析表明,所提方法不仅能够有效解决宽带相干信号的估计问题,还能够在低信噪比下有着更优的估计性能和更高的估计精度,且易于工程实现。

       

      Abstract: The estimation accuracy of direction of arrival (DOA) in the incoherent signal subspace method (ISSM) under low signal-to-noise ratio condition is susceptible to the interference from data containing estimation errors of DOA angles at different frequency points. Furthermore, the ISSM method cannot solve the DOA estimation problem of broadband coherent signals. To overcome the limitations of the method, a novel broadband coherent DOA estimation method by building upon and refining the existing ISSM approach is proposed in this paper. Firstly, the frequency cross-spectral density matrix of different frequency points is obtained by the ISSM method, and the de-coherence processing is carried out. Then, the subspace DOA algorithm is used to calculate the DOA estimation results of each frequency point. Finally, the interval density method is used to fuse the DOA estimation results of all frequency points to obtain the final DOA estimation result. The simulation results show that the proposed method, which is easy to implement in engineering, not only can effectively solve the estimation problem of wideband coherent signal, but also has better estimation performance and higher estimation accuracy under low signal-to-noise ratio.

       

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