Journal of Systems Engineering and Electronics ›› 2021, Vol. 32 ›› Issue (2): 437-446.doi: 10.23919/JSEE.2021.000037

• DEFENCE ELECTRONICS TECHNOLOGY • Previous Articles     Next Articles

Automatic radar antenna scan type recognition based on limited penetrable visibility graph

Songtao LIU*(), Zhenshuo LEI(), Yang GE(), Zhenming WEN()   

  1. 1 Department of Information System, Dalian Naval Academy, Dalian 116018, China
  • Received:2020-05-27 Online:2021-04-29 Published:2021-04-29
  • Contact: Songtao LIU;;;
  • About author:|LIU Songtao was born in 1978. He received his B.S. degree in aviation radar, M.S. degree and Ph.D. degree in signal and information processing from Naval Aeronautical Engineering Institute, in 2000, 2003 and 2006, respectively. He joined Dalian Naval Academy in 2006 where he is now an associate professor in the Department of Information System. From 2010 to 2012, he was a postdoctoral researcher at the Postdoctoral Station of Information and Communication Engineering, Dalian University of Technology. He has published over 80 papers in journals and conference proceedings. His research interests include image processing, optoelectronic engi-neering, and electronic countermeasures. E-mail:||LEI Zhenshuo was born in 1996. He received his B.S. degree from the Beijing Jiaotong University, Beijing, China, in 2018. He is currently pursuing his M.S. degree in electronics and information engineering from Dalian Naval Academy. His research interests include electronic countermeasures, and machine learning. E-mail:||GE Yang was born in 1992. She received her B.S. degree in electronic information science and technology from Xi’an University of Technology in 2015. She is currently pursuing her master’s degree in electronics and information engineering from Dalian Naval Academy. Her research interests include electronic countermeasures technology and application. E-mail:||WEN Zhenming was born in 1995. He received his B.S. degree in electronic information engineering from Dalian University of Technology, in 2018. Now he is a postgraduate student of electronics and information engineering in Dalian Naval Academy. He is mainly engaged in the research of multi-sensor target recognition and tracking technology. E-mail:
  • Supported by:
    This work was supported by the China Postdoctoral Science Foundation (2015M572694; 2016T90979);This work was supported by the China Postdoctoral Science Foundation (2015M572694; 2016T90979)


To address the problem of the weak anti-noise and macro-trend extraction abilities of the current methods for identifying radar antenna scan type, a recognition method for radar antenna scan types based on limited penetrable visibility graph (LPVG) is proposed. Firstly, seven types of radar antenna scans are analyzed, which include the circular scan, sector scan, helical scan, raster scan, conical scan, electromechanical hybrid scan and two-dimensional electronic scan. Then, the time series of the pulse amplitude in the radar reconnaissance receiver is converted into an LPVG network, and the feature parameters are extracted. Finally, the recognition result is obtained by using a support vector machine (SVM) classifier. The experimental results show that the recognition accuracy and noise resistance of this new method are improved, where the average recognition accuracy for radar antenna type is at least 90% when the signal-to-noise ratio (SNR) is 5 dB and above.

Key words: antenna scan type, limited penetrable visibility graph (LPVG), support vector machine (SVM), cognitive electronic warfare