RFI Source Localization in Microwave Interferometric Radiometry: A Sparse Signal Reconstruction Perspective

2020 ◽  
Vol 58 (6) ◽  
pp. 4006-4017
Author(s):  
Dong Zhu ◽  
Jun Li ◽  
Gang Li
2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Shuang Li ◽  
Wei Liu ◽  
Daqing Zheng ◽  
Shunren Hu ◽  
Wei He

Source localization using sensor array in the near-field is a two-dimensional nonlinear parameter estimation problem which requires jointly estimating the two parameters: direction-of-arrival and range. In this paper, a new source localization method based on sparse signal reconstruction is proposed in the near-field. We first utilize l1-regularized weighted least-squares to find the bearings of sources. Here, the weight is designed by making use of the probability distribution of spatial correlations among symmetric sensors of the array. Meanwhile, a theoretical guidance for choosing a proper regularization parameter is also presented. Then one well-known l1-norm optimization solver is employed to estimate the ranges. The proposed method has a lower variance and higher resolution compared with other methods. Simulation results are given to demonstrate the superior performance of the proposed method.


2021 ◽  
Vol 140 ◽  
pp. 100-112
Author(s):  
You Zhao ◽  
Xiaofeng Liao ◽  
Xing He ◽  
Rongqiang Tang ◽  
Weiwei Deng

2019 ◽  
Vol 26 (10) ◽  
pp. 1541-1545 ◽  
Author(s):  
Yunmei Shi ◽  
Xing-Peng Mao ◽  
Chunlei Zhao ◽  
Yong-Tan Liu

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