• DEFENCE ELECTRONICS TECHNOLOGY •

### Research on LPI radar signal detection and parameter estimation technology

Tao WAN*(), Kaili JIANG(), Jingyi LIAO(), Tingting JIA(), Bin TANG()

1. 1 School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
• Received:2020-07-11 Online:2021-06-18 Published:2021-07-26
• Contact: Tao WAN E-mail:taowan.uestc0939@foxmail.com;jiangkelly@foxmail.com;LiaoJingyi@std.uestc.edu.cn;18804431003@163.com;bint@uestc.edu.cn
• About author:|WAN Tao was born in 1995. He received his B.S. degree from Harbin University of Commerce in 2017, Harbin, China. He is currently pursuing his Ph.D. degree with University of Electronic Science and Technology of China. He is interested in electronic reconnaissance and is mainly engaged in electronic countermeasures, signal processing and machine learning. E-mail: taowan.uestc0939@foxmail.com||JIANG Kaili was born in 1991. She received her B.S. degree from University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 2013. Currently, she is working toward her Ph.D. degree in the School of Information and Communication Engineering, UESTC. Her research interests include wideband spectrum sensing, sparse/compressive sensing and radar signal processing. E-mail: jiangkelly@foxmail.com||LIAO Jingyi was born in 1996. She received her B.S. degree from University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 2018. She is currently pursuing her M.S. degree with the School of Information and Communication Engineering, UESTC. Her research interest includes LPI radar signal detection and classification. E-mail: LiaoJingyi@std.uestc.edu.cn||JIA Tingting was born in 1994. She received her B.S. degree from Kunming University of Science and Technology, Kunming, China, in 2017. She is currently pursuing her M.S. degree with University of Electronic Science and Technology of China. Her research interests include LPI radar signal detection and parameter estimation. E-mail: 18804431003@163.com||TANG Bin was born in 1963. He is a professor of University of Electronic Science and Technology of China. His research interests include complex/combination modulation LPI and new system radar reconnaissance and interference technology, adaptive radar reconnaissance and interference technology, networked radar countermeasure technology, broadband/ultra-wideband radar digital reconnaissance receiving and interference technology. E-mail: bint@uestc.edu.cn
• Supported by:
This work was supported by the National Defence Pre-research Foundation of China (30502010103)

Abstract:

Modern radar signals mostly use low probability of intercept (LPI) waveforms, which have short pulses in the time domain, multicomponent properties, frequency hopping, combined modulation waveforms and other characteristics, making the detection and estimation of LPI radar signals extremely difficult, and leading to highly required significant research on perception technology in the battlefield environment. This paper proposes a visibility graphs (VG)-based multicomponent signals detection method and a modulation waveforms parameter estimation algorithm based on the time-frequency representation (TFR). On the one hand, the frequency domain VG is used to set the dynamic threshold for detecting the multicomponent LPI radar waveforms. On the other hand, the signal is projected into the time and frequency domains by the TFR method for estimating its symbol width and instantaneous frequency (IF). Simulation performance shows that, compared with the most advanced methods, the algorithm proposed in this paper has a valuable advantage. Meanwhile, the calculation cost of the algorithm is quite low, and it is achievable in the future battlefield.