Paper Info
Title
A Tensor-Based Covariance Differencing Method for Direction Estimation in Bistatic MIMO Radar With Unknown Spatial Colored Noise.
Abstract
In this paper, we investigate into direction estimation in bistatic multiple-input multiple output (MIMO) radar in the presence of unknown spatial colored noise. Taking the stationary property of the spatial colored noise into consideration, a transform-based tensor covariance differencing method is proposed. The spatial colored noise is eliminated by forming the difference of the original and the transformed covariance matrices. To further exploit the inherent multidimensional nature, a fourth-order tensor is constructed, which helps to achieve more accurate subspace estimation. Thereafter, the traditional subspace-based methods are applied for ambiguous direction estimation. Finally, a special matrix is formed to associate the real angles with the targets. The proposed scheme does not bring virtual aperture loss, and it has complexity lower than the existing tensor-based subspace methods. Numerical simulations verify the improvement of our scheme.
Year
DOI
Venue
2017
10.1109/ACCESS.2017.2749404
IEEE ACCESS
Keywords
Field
DocType
Bistatic MIMO radar,direction estimation,spatial colored noise,covariance differencing,Tucker decomposition
Radar,Colors of noise,Subspace topology,Tensor,Matrix (mathematics),Computer science,MIMO,Algorithm,Bistatic radar,Statistics,Distributed computing,Covariance
Journal
Volume
ISSN
Citations 
5
2169-3536
3
PageRank 
References 
Authors
0.38
12
6
Name
Order
Citations
PageRank
Fangqing Wen16813.81
Zi-jing Zhang213515.74
Gong Zhang34216.90
Yu Zhang429498.00
Xinhai Wang530.72
Xinyu Zhang62412.48