相干信号DOA估计的改进Toeplitz算法

Chen Hui, Huang Ben-xiong, Deng Bin, Hou Yaoqin
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引用次数: 9

摘要

本文提出了一种基于互相关矢量Toeplitz重构的CVT算法。CVT方法可以有效地估计相干信号源。CVT利用阵列接收数据的内部关系来实现信号源的去相干。与经典空间平滑算法相比,该算法在相同相位条件下具有更高的估计精度。原因是CVT方法可以完全实现去相干,而空间平滑算法只能实现秩重构。秩重构的产生在修正后的信号协方差矩阵中引入了互相关噪声。而CVT方法可以将相干源的信号协方差矩阵变换成对角矩阵。因此,与空间平滑算法相比,CVT算法具有计算量小、鲁棒性好、估计精度高等优点。理论分析和仿真结果表明,该方法是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A modified Toeplitz algorithm for DOA estimation of coherent signals
A new algorithm based on cross-correlation vector Toeplitz reconstruction, called CVT method, is proposed in this paper. The CVT method can estimate coherent signal source effectively. The CVT utilizes the internal relation of array receiving data to realize signal sources de-coherent. Compared with the classical spatial smoothing algorithms the proposed algorithm has higher estimation precision under the condition of the same phase. The reason is that the CVT method can realize de-coherent completely, but the spatial smoothing algorithms realize rank reconstruction only. The produce of rank reconstruction introduces cross- correlation noise into modified signal covariance matrix. But the CVT method can transform the signal covariance matrix of coherent source into diagonal matrix. Therefore, the CVT algorithm has some advantages of low computational load, better robustness and higher estimation precision than spatial smoothing algorithm. The theoretical analysis and simulation results show that the proposed method is effective.
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