A tensor-based subspace approach for bistatic MIMO radar in spatial colored noise.

A tensor-based subspace approach for bistatic MIMO radar in spatial colored noise.
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DOI:
10.3390/s140303897
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发表时间:
2014-02-25
期刊:
Sensors (Basel, Switzerland)
影响因子:
--
通讯作者:
Wang J
Wang J
中科院分区:
其他
文献类型:
--
作者:
Wang X;Wang W;Li X;Wang J

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本文提出了一种新的基于张量的子空间估计方法,用于双基地多输入多输出(MIMO)雷达在空间彩色噪声存在下的出发方向和到达方向估计。首先,利用匹配滤波器的固有结构,将接收到的信号打包成一个三阶测量张量;然后,将测量张量分成两个子张量,并构造一个交叉协方差张量来消除空间彩色噪声。最后,利用交叉协方差张量的高阶奇异值分解(HOSVD)构造信号子空间,通过旋转不变性技术(ESPRIT)算法对信号参数进行估计,得到DOD和DOA,并对其进行自动配对。由于使用了多维固有结构和交叉协方差张量技术,因此该方法比Chen方法、ESPRIT算法和multi-SVD方法具有更好的角度估计性能。仿真结果验证了该方法的有效性和优越性。
In this paper, a new tensor-based subspace approach is proposed to estimate the direction of departure (DOD) and the direction of arrival (DOA) for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise. Firstly, the received signals can be packed into a third-order measurement tensor by exploiting the inherent structure of the matched filter. Then, the measurement tensor can be divided into two sub-tensors, and a cross-covariance tensor is formulated to eliminate the spatial colored noise. Finally, the signal subspace is constructed by utilizing the higher-order singular value decomposition (HOSVD) of the cross-covariance tensor, and the DOD and DOA can be obtained through the estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm, which are paired automatically. Since the multidimensional inherent structure and the cross-covariance tensor technique are used, the proposed method provides better angle estimation performance than Chen's method, the ESPRIT algorithm and the multi-SVD method. Simulation results confirm the effectiveness and the advantage of the proposed method.
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