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Sensors 2014, 14(3), 3897-3907; doi:10.3390/s140303897

A Tensor-Based Subspace Approach for Bistatic MIMO Radar in Spatial Colored Noise

College of Automation, Harbin Engineering University, No. 145 Nantong Street, Harbin 150001, China
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Received: 1 December 2013 / Revised: 16 February 2014 / Accepted: 18 February 2014 / Published: 25 February 2014
(This article belongs to the Section Physical Sensors)
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Abstract

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. View Full-Text
Keywords: MIMO radar; DOD and DOA estimation; spatial colored noise; higher-order singular value decomposition MIMO radar; DOD and DOA estimation; spatial colored noise; higher-order singular value decomposition
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Wang, X.; Wang, W.; Li, X.; Wang, J. A Tensor-Based Subspace Approach for Bistatic MIMO Radar in Spatial Colored Noise. Sensors 2014, 14, 3897-3907.

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