Direction Finding by Time-Modulated Linear Array

2018 ◽  
Vol 66 (7) ◽  
pp. 3642-3652 ◽  
Author(s):  
Chong He ◽  
Anjie Cao ◽  
Jingfeng Chen ◽  
Xianling Liang ◽  
Weiren Zhu ◽  
...  
2018 ◽  
Vol 143 (3) ◽  
pp. 1872-1872
Author(s):  
Yang Song ◽  
Kainam T. Wong ◽  
Salman Khan ◽  
Mohammad Asaduzzaman Khan

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 426 ◽  
Author(s):  
Peng Chen  ◽  
Zhimin Chen ◽  
Xuan Zhang ◽  
Linxi Liu

The imperfect array degrades the direction finding performance. In this paper, we investigate the direction finding problem in uniform linear array (ULA) system with unknown mutual coupling effect between antennas. By exploiting the target sparsity in the spatial domain, the sparse Bayesian learning (SBL)-based model is proposed and converts the direction finding problem into a sparse reconstruction problem. In the sparse-based model, the off-grid errors are introduced by discretizing the direction area into grids. Therefore, an off-grid SBL model with mutual coupling vector is proposed to overcome both the mutual coupling and the off-grid effect. With the distribution assumptions of unknown parameters including the noise variance, the off-grid vector, the received signals and the mutual coupling vector, a novel direction finding method based on SBL with unknown mutual coupling effect named DFSMC is proposed, where an expectation-maximum (EM)-based step is adopted by deriving the estimation expressions for all the unknown parameters theoretically. Simulation results show that the proposed DFSMC method can outperform state-of-the-art direction finding methods significantly in the array system with unknown mutual coupling effect.


1964 ◽  
Vol 12 (3) ◽  
pp. 248-256 ◽  
Author(s):  
N. Burtnyk ◽  
C. McLeish ◽  
J. Wolfe

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