Passive Localization of Mixed Near-Field and Far-Field Sources Without Eigendecomposition via Uniform Circular Array

2020 ◽  
Vol 39 (10) ◽  
pp. 5298-5317
Author(s):  
Xiaolong Su ◽  
Zhen Liu ◽  
Tianpeng Liu ◽  
Bo Peng ◽  
Xin Chen ◽  
...  
Sensors ◽  
2018 ◽  
Vol 18 (5) ◽  
pp. 1432 ◽  
Author(s):  
Xiaolong Su ◽  
Zhen Liu ◽  
Xin Chen ◽  
Xiang Li

2019 ◽  
Vol 157 ◽  
pp. 119-130 ◽  
Author(s):  
Amir Masoud Molaei ◽  
Bijan Zakeri ◽  
Seyed Mehdi Hosseini Andargoli

Electronics ◽  
2019 ◽  
Vol 8 (5) ◽  
pp. 525 ◽  
Author(s):  
Kai Wang ◽  
Ling Wang ◽  
Jian Xie ◽  
Yuexian Wang ◽  
Zhanolin Zhang

In classification and localization of mixed far-field and near-field sources, the unknown mutual coupling degrades the performance of most high-resolution algorithms. In practice, the assumption of an ideal receiving sensor array is rarely satisfied. This paper proposes an effective algorithm of mixed sources identification using uniform circular array under unknown mutual coupling. Firstly, according to rank reduction and joint space–time processing, the directions of arrival of far-field sources is estimated directly without mutual coupling elimination. Addition, the joint space–time processing can improve the estimation results in the case of low signal noise ratio of incoming signal sources and small number of snapshots. Then, these estimates are adopted to reconstruct the mutual coupling matrix. Finally, both direction and range parameters of near-field sources are obtained through spatial search after mutual coupling effects and far-field components elimination. The proposed algorithm is described in detail, and its behavior is illustrated by numerical examples.


Sensors ◽  
2015 ◽  
Vol 15 (2) ◽  
pp. 3834-3853 ◽  
Author(s):  
Jian Xie ◽  
Haihong Tao ◽  
Xuan Rao ◽  
Jia Su

2016 ◽  
Vol 52 (20) ◽  
pp. 1690-1692 ◽  
Author(s):  
Bing Xue ◽  
Guangyou Fang ◽  
Yicai Ji
Keyword(s):  

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