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Covariance differencing-based matrix decomposition for coherent sources localisation in bi-static multiple-input–multiple-output radar

机译:基于协方差差分的矩阵分解用于双静态多输入多输出雷达中相干源定位

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摘要

In this study, a covariance differencing-based matrix decomposition algorithm is proposed for locating coherent sources under spatially coloured noise in bi-static multiple-input–multiple-output (MIMO) radar. The method contains three steps. First, the covariance differencing technique is employed to eliminate sensor noise, especially the spatially coloured noise. Second, a block Toeplitz or block Hankel matrix is constructed for decorrelation with the covariance differenced matrix. The forward-only, backward-only and combined forward-backward block Toeplitz/Hankel matrix constructions are defined, respectively. Third, unitary estimation of signal parameters by rotational invariance techniques (ESPRIT) algorithm is applied to estimate directions-of-departure (DODs) and directions-of-arrival (DOAs) of sources. The proposed algorithm offers several advantages. First, it is more robust and provides better estimation performance than other methods. Then, the coloured noise problem is overcome in a simple and effective way. Further, the computational load is comparatively low. Simulation results demonstrate the validity of the proposed algorithm.
机译:在这项研究中,提出了一种基于协方差差分的矩阵分解算法,以在双静态多输入多输出(MIMO)雷达中在空间彩色噪声下定位相干源。该方法包含三个步骤。首先,采用协方差差分技术来消除传感器噪声,尤其是空间彩色噪声。其次,构造块Toeplitz或块汉克尔矩阵以与协方差差分矩阵去相关。分别定义了仅向前,仅向后和组合的向前-向后块Toeplitz / Hankel矩阵构造。第三,通过旋转不变技术(ESPRIT)算法对信号参数进行统一估计,以估计源的出发方向(DOD)和到达方向(DOA)。所提出的算法具有几个优点。首先,它比其他方法更健壮,并提供更好的估计性能。然后,以简单有效的方式克服了有色噪声问题。此外,计算负荷相对较低。仿真结果证明了该算法的有效性。

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