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Telecommunications and Radio Engineering
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ISSN Imprimir: 0040-2508
ISSN En Línea: 1943-6009

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Telecommunications and Radio Engineering

DOI: 10.1615/TelecomRadEng.v79.i8.60
pages 691-702


J. Wu
AVIC Aeronautical Radio Electronics Research Institute, 432 Guiping St. Shanghai, 200030 China
Y. Zheng
College of Electronic & Information Engineering, Qingdao University, 308 Ningxia St. Qingdao, 266071, China
Z. Sun
College of Electronic & Information Engineering, Qingdao University, 308 Ningxia St. Qingdao, 266071, China
H. Chen
College of Physics and Optoelectronic Engineering, Harbin Engineering University,145 Nantongdajie St. Harbin, 150001 China


Modern air combat is three-dimensional, omnidirectional, networked and informationalized. The rational management of airborne sensors can make warplanes gain more living space in the battlefield. In order to improve the survival chance of the fighter, the active radar time should be reduced, and the passive radar should be used as much as possible while satisfying the tracking accuracy. Therefore, this paper designs a multi-sensor collaborative tracking method based on the target priority discrimination of the information increment and covariance. When the target threat level is high, active radar is used to ensure tracking accuracy, and reduce the use of active radar when the target threat level is low, reducing the possibility of being discovered.


  1. Qiao, C., Shan, G., Duan, X., and Guo, F., (2019) Long-term scheduling method of multi-platform active and passive sensor cooperative tracking, Ordnance Journal, 40(01), pp. 115-123.

  2. Ma, X., (2015) Mathematical model of assignment decision for multi-machine multi-sensor cooperative target tracking under radiation control, Chinese command and control society. Proceedings of the Third China Command and Control Conference (Part 2). Chinese command and control society: Chinese command and control society, pp. 54-58.

  3. Xu, G., Shan, G., Duan, X., Qiao, C., and Wang, H., (2019) Multi-sensor collaborative detection and tracking scheduling method based on Markov decision process, Journal of Electronics and Information Technology, 41(09), pp. 2201-2208.

  4. Gao, G., Li, F., and Wan, K., (2018) Research on Multi-sensor Cooperative Tracking Strategy in Data Packet Loss Environment, System Engineering and Electronic Technology, 40(11), pp. 2450-2458.

  5. Wu, L., Xu, W., Xia, H., Deng, Y., and Zhang, X., (2017) Multi-sensor collaborative detection and tracking based on dynamic alliance, Infrared Technology, 39(11), pp. 996-1000.

  6. Wan, K., Gao, X., Li, B., and Mei, J., (2015) Multi-passive sensor network collaborative anti-stealth detection task planning based on partially observable Markov decision process, Ordnance Journal, 36(04), pp. 731-743.

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