Two Dimensional Joint ISAR Imaging Algorithm Based on Matrix Completion

Author(s):  
Jian-fei Ren ◽  
Le Kang ◽  
Xiao-fei Lu ◽  
Yijun Chen ◽  
Ying Luo
2019 ◽  
Vol 13 (3) ◽  
pp. 445-455 ◽  
Author(s):  
Zeng Chuangzhan ◽  
Zhu Weigang ◽  
Jia Xin

Sensors ◽  
2018 ◽  
Vol 18 (6) ◽  
pp. 1741 ◽  
Author(s):  
Haiyun Xu ◽  
Yankui Zhang ◽  
Bin Ba ◽  
Daming Wang ◽  
Xiangzhi Li

Sensors ◽  
2017 ◽  
Vol 17 (3) ◽  
pp. 542 ◽  
Author(s):  
Xinfei Lu ◽  
Jie Xia ◽  
Zhiping Yin ◽  
Weidong Chen

2003 ◽  
Vol 86 (7) ◽  
pp. 1-10 ◽  
Author(s):  
Kazuhiko Yamamoto ◽  
Masafumi Iwamoto ◽  
Takahiko Fujisaka ◽  
Tetsuo Kirimoto

2016 ◽  
Vol 2016 ◽  
pp. 1-6
Author(s):  
Wenhao Zeng ◽  
Hongtao Li ◽  
Xiaohua Zhu ◽  
Chaoyu Wang

To improve the performance of two-dimensional direction-of-arrival (2D DOA) estimation in sparse array, this paper presents a Fixed Point Continuation Polynomial Roots (FPC-ROOT) algorithm. Firstly, a signal model for DOA estimation is established based on matrix completion and it can be proved that the proposed model meets Null Space Property (NSP). Secondly, left and right singular vectors of received signals matrix are achieved using the matrix completion algorithm. Finally, 2D DOA estimation can be acquired through solving the polynomial roots. The proposed algorithm can achieve high accuracy of 2D DOA estimation in sparse array, without solving autocorrelation matrix of received signals and scanning of two-dimensional spectral peak. Besides, it decreases the number of antennas and lowers computational complexity and meanwhile avoids the angle ambiguity problem. Computer simulations demonstrate that the proposed FPC-ROOT algorithm can obtain the 2D DOA estimation precisely in sparse array.


Sign in / Sign up

Export Citation Format

Share Document