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An Improved Direction Finding Algorithm Based on Toeplitz Approximation

机译:基于Toeplitz逼近的改进测向算法。

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摘要

In this paper, a novel direction of arrival (DOA) estimation algorithm called the Toeplitz fourth order cumulants multiple signal classification method (TFOC-MUSIC) algorithm is proposed through combining a fast MUSIC-like algorithm termed the modified fourth order cumulants MUSIC (MFOC-MUSIC) algorithm and Toeplitz approximation. In the proposed algorithm, the redundant information in the cumulants is removed. Besides, the computational complexity is reduced due to the decreased dimension of the fourth-order cumulants matrix, which is equal to the number of the virtual array elements. That is, the effective array aperture of a physical array remains unchanged. However, due to finite sampling snapshots, there exists an estimation error of the reduced-rank FOC matrix and thus the capacity of DOA estimation degrades. In order to improve the estimation performance, Toeplitz approximation is introduced to recover the Toeplitz structure of the reduced-dimension FOC matrix just like the ideal one which has the Toeplitz structure possessing optimal estimated results. The theoretical formulas of the proposed algorithm are derived, and the simulations results are presented. From the simulations, in comparison with the MFOC-MUSIC algorithm, it is concluded that the TFOC-MUSIC algorithm yields an excellent performance in both spatially-white noise and in spatially-color noise environments.
机译:本文通过结合一种称为修正四阶累积量MUSIC(MFOC-)的类似于MUSIC的快速算法,提出了一种新颖的到达方向(DOA)估计算法,称为Toeplitz四阶累积量多信号分类方法(TFOC-MUSIC)算法。 MUSIC)算法和Toeplitz近似。在提出的算法中,去除了累积量中的冗余信息。此外,由于四阶累积量矩阵的尺寸减小,因此降低了计算复杂度,该尺寸等于虚拟阵列元素的数量。即,物理阵列的有效阵列孔径保持不变。然而,由于有限的采样快照,存在降级FOC矩阵的估计误差,因此DOA估计的能力降低。为了提高估计性能,引入Toeplitz近似来恢复降维FOC矩阵的Toeplitz结构,就像具有Toeplitz结构的最优估计结果的理想矩阵一样。推导了该算法的理论公式,并给出了仿真结果。通过仿真,与MFOC-MUSIC算法相比,可以得出结论,TFOC-MUSIC算法在空间白噪声和空间色噪声环境中均具有出色的性能。

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