期刊
JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS
卷 28, 期 2, 页码 257-266出版社
SYSTEMS ENGINEERING & ELECTRONICS, EDITORIAL DEPT
DOI: 10.21629/JSEE.2017.02.07
关键词
multiple-input multiple-output radar; angle estimation; mutual coupling; three-way compressive sensing
类别
资金
- National Natural Science Foundation of China [61071163, 61071164, 61471191, 61501233]
- Fundamental Research Funds for the Central Universities [NP2014504]
- Aeronautical Science Foundation [20152052026]
- Electronic & Information School of Yangtze University Innovation Foundation [2016-DXCX-05]
- Priority Academic Program Development of Jiangsu Higher Education Institutions
The problem of angle estimation for bistatic multipleinput multiple-output radar in the present of unknown mutual coupling (MC) is investigated, and a three-way compressive sensing (TWCS) estimation algorithm is developed. To exploit the inherent multi-dimensional structure of received data, a trilinear tensor model is firstly formulated. Then the de-coupling operation is followed. Thereafter, the high-order singular value decomposition is applied to compress the high dimensional tensor to a much smaller one. The estimation of the compressed direction matrices are linked to the compressed trilinear model, and finally two over-complete dictionaries are constructed for angle estimation. Also, Cramer-Rao bounds for angle and MC estimation are derived. The proposed TWCS algorithm is effective from the perspective of estimation accuracy as well as the computational complexity, and it can achieve automatically paired angle estimation. Simulation results show that the proposed method has much better estimation accuracy than the existing algorithms in the low signal-to-noise ratio scenario, and its estimation performance is very close to the parallel factor analysis (PARAFAC) algorithm at the high SNR regions.
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