• ELECTRONICS TECHNOLOGY •

### Fast BSC-based algorithm for near-field signal localization via uniform circular array

Xiaolong SU1(), Zhen LIU1,*(), Bin SUN2(), Yang WANG2(), Xin CHEN1(), Xiang LI1()

1. 1 College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China
2 Beijing Institute of Tracking and Telecommunication Technology, Beijing 100094, China
• Received:2020-06-24 Accepted:2022-02-22 Online:2022-05-06 Published:2022-05-06
• Contact: Zhen LIU E-mail:suxiaolong_nudt@163.com;zhen_liu@nudt.edu.cn;sunbin_nudt@163.com;wyang1004@163.com;chenxin10@nudt.edu.cn;lixiang01@vip.sina.com
• About author:|SU Xiaolong was born in 1994. He received his B.S. degree from Central South University, Changsha, China, in 2016 and M.S. degree from the National University of Defense Technology (NUDT), Changsha, China, in 2018. He is currently pursuing his Ph.D. degree with the College of Electronic Science and Technology, NUDT. His research interests include array signal processing and deep learning. E-mail: suxiaolong_nudt@163.com||LIU Zhen was born in 1983. He received his B.S. degree from Zhejiang University, Hangzhou, China, in 2006, and Ph.D. degree from the National University of Defense Technology (NUDT), Changsha, China, in 2013. He is currently a professor with the College of Electronic Science and Technology, NUDT. His research interests include radar target recognition and countermeasures, array signal processing, and machine learning. E-mail: zhen_liu@nudt.edu.cn||SUN Bin was born in 1984. He received his B.S. degree in electrical information engineering from Zhejiang University, Hangzhou, in 2007, and Ph.D. degree in information and communication engineering from the National University of Defense Technology, Changsha, in 2014. He is an assistant professor of radar system engineering at Beijing Institute of Tracking and Telecommution Technology. His research interests include MIMO radar, radar resignal management, and statistical signal processing. E-mail: sunbin_nudt@163.com||WANG Yang was born in 1980. She received her B.S. degree in electrical information engineering from Northwestern Polytechnical University, Xi’an, in 2003, and M.S. degree in information and communication engineering from Beijing Institute of Tracking and Telecommution Technology, Beijing, in 2006. She is an assistant professor of radar system engineering at Beijing Institute of Tracking and Telecommution Technology. Her research interests include design of phased array radar system, and radar signal processing. E-mail: wyang1004@163.com||CHEN Xin was born in 1992. He received his B.S. and M.S. degrees from the National University of Defense Technology, Changsha, China, in 2010 and 2014, respectively. He is currently pursuing his Ph.D. degree with the College of Electronic Science and Technology. His research interests include radar signal processing and array signal processing. E-mail: chenxin10@nudt.edu.cn||LI Xiang was born in 1967. He received his B.S. degree from Xidian University, Xi’an, China, in 1989 and Ph.D. degree from the National University of Defense Technology (NUDT), Changsha, China, in 1998. He is a professor with the College of Electronic Science and Technology, NUDT. His research interests include signal processing, automation target recognition, and deep learning. E-mail: lixiang01@vip.sina.com
• Supported by:
This work was supported by the National Natural Science Foundation of China (61921001; 62022091) and the Natural Science Foundation of Hunan Province (2017JJ3368).

Abstract:

In this paper, we propose a beam space coversion (BSC)-based approach to achieve a single near-field signal localization under uniform circular array (UCA). By employing the centro-symmetric geometry of UCA, we apply BSC to extract the two-dimensional (2-D) angles of near-field signal in the Vandermonde form, which allows for azimuth and elevation angle estimation by utilizing the improved estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm. By substituting the calculated 2-D angles into the direction vector of near-field signal, the range parameter can be consequently obtained by the 1-D multiple signal classification (MUSIC) method. Simulations demonstrate that the proposed algorithm can achieve a single near-field signal localization, which can provide satisfactory performance and reduce computational complexity.