Journal of Systems Engineering and Electronics ›› 2022, Vol. 33 ›› Issue (3): 585-593.doi: 10.23919/JSEE.2022.000056

• DEFENCE ELECTRONICS TECHNOLOGY • Previous Articles     Next Articles

An interference suppression algorithm for cognitive bistatic airborne radars

Deping XIA1,2,*(), Liang ZHANG1,2(), Tao WU2(), Wenjun HU2()   

  1. 1 National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China
    2 Nanjing Research Institute of Electronics Technology, Nanjing 210039, China
  • Received:2021-03-17 Online:2022-06-18 Published:2022-06-24
  • Contact: Deping XIA E-mail:xiadeping@cetc.com.cn;zhangliang@cetc.com.cn;wutao12@cetc.com.cn;huwenjun@cetc.com.cn
  • About author:|XIA Deping was born in 1977. He received his B.S. degree in electrical engineering from Harbin Engineering University in 2000 and M.S. degree in signal and information processing from Nanjing University of Science and Technology in 2009. He is currently a Ph.D. candidate of National Laboratory of Radar Signal Processing in Xidian University. He is a senior expert of Chinese Electronics Technology Corporation. His research interests include adaptive signal processing and polarization information processing. E-mail: xiadeping@cetc.com.cn||ZHANG Liang was born in 1966. He received his B.S. degree in electrical engineering from Wuhan University in 1988 and Ph.D degree in National Laboratory of Radar Signal Processing from Xidian University in 2000. Since 2015, he has been a chief scientist of Chinese Electronics Technology Corporation and a adjunct professor at Xidian University. His current research interests include radar system design and signal processing technology. E-mail: zhangliang@cetc.com.cn||WU Tao was born in 1975. He received his B.E. degree in electrical engineering from Nanjing University of Science and Technology in 1997. He is a senior expert of Chinese Electronics Technology Corporation. He is a senior member of Nanjing Research Institute of Electronic Technology. His research interest is systems engineering of radar. E-mail: wutao12@cetc.com.cn||HU Wenjun was born in 1984. He received his M.S. degree from Nanjing Research Institute of Electronics Technology, Nanjing, China, in 2008. His major work is communication and information system. He works as a senior engineer currently in Nanjing Research Institute of Electronics Technology. His research interest is radar system design. E-mail: huwenjun@cetc.com.cn

Abstract:

Interference suppression is a challenge for radar researchers, especially when mainlobe and sidelobe interference coexist. We present a comprehensive anti-interference approach based on a cognitive bistatic airborne radar. The risk of interception is reduced by lowering the launch energy of the radar transmitting terminal in the direction of interference; mainlobe and sidelobe interferences are suppressed via cooperation between the two radars. The interference received by a single radar is extracted from the overall radar signal using multiple signal classification (MUSIC), and the interference is cross-located using two different azimuthal angles. Neural networks allowing good, non-linear non-parametric approximations are used to predict the location of interference, and this information is then used to preset the transmitting notch antenna to reduce the likelihood of interception. To simultaneously suppress mainlobe and sidelobe interferences, a blocking matrix is used to mask mainlobe interference based on azimuthal information, and an adaptive process is used to suppress sidelobe interference. Mainlobe interference is eliminated using the data received by the two radars. Simulation verifies the performance of the model.

Key words: interference suppression, cognitive bistatic airborne radar, neural network, blocking matrix