Volume 48 Issue 9
Oct.  2019
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Zhang Yunpu, Xu Gongguo, Shan Ganlin, Duan Xiusheng. Scheduling approach of mobile radar/infrared radiation control[J]. Infrared and Laser Engineering, 2019, 48(9): 904004-0904004(8). doi: 10.3788/IRLA201948.0904004
Citation: Zhang Yunpu, Xu Gongguo, Shan Ganlin, Duan Xiusheng. Scheduling approach of mobile radar/infrared radiation control[J]. Infrared and Laser Engineering, 2019, 48(9): 904004-0904004(8). doi: 10.3788/IRLA201948.0904004

Scheduling approach of mobile radar/infrared radiation control

doi: 10.3788/IRLA201948.0904004
  • Received Date: 2019-04-05
  • Rev Recd Date: 2019-05-03
  • Publish Date: 2019-09-25
  • To reduce the radiation risk of mobile radar/infrared cooperative tracking, a scheduling approach of mobile radar/infrared radiation control was proposed. Firstly, a target tracking model was established based on the moving state of the platform and the target, and the tracking accuracy was predicted by using the cubature Kalman filter. Secondly, the radar radiation model was established by introducing the radiation effect, and the prediction methods of the radar radiation status and the system radiation cost were given. Then, the objective function of non-myopic scheduling was constructed with tracking accuracy satisfying task requirements as constraints and non-myopic radiation cost minimization as optimization objectives. Finally, a decision tree search algorithm was designed to solve the problem of high computational complexity. The simulation results show that the proposed scheduling approach has better radiation control effect than the myopic scheduling approach. When the decision step is 3, the radiation cost decreases by 26.5%. Compared with the fixed position scheduling approach, the proposed approach can improve the tracking performance and reduce the radiation cost. When tracking low-speed targets, the tracking error and radiation cost are reduced by 29.9% and 30.5%, respectively.
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    [2] Wang Weijia, Bai Peng, Liang Xiaolong, et al. Cooperative tracking algorithm of radar aided optic-electric tracking system[J]. Infrared and Laser Engineering, 2017, 46(12):1217006. (in Chinese)
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    [4] Li Shizhong, Wang Guohong, Wu Wei, et al. Radar/infrared composite guidance tracking under intermittent radar operation[J]. Infrared and Laser Engineering, 2012, 41(6):1405-1410. (in Chinese)
    [5] Qiao Chenglin, Shan Ganlin, Duan Xiusheng, et al. Non-myopic scheduling algorithm of multi-platform active/passive sensors for collaboration tracking[J]. Acta Armamentarii, 2019, 40(1):115-123. (in Chinese)
    [6] Xu Gongguo, Shan Ganlin, Duan Xiusheng. Non-myopic scheduling method of active mobile sensor for target tracking[J]. Chinese Journal of Sensors and Actuators, 2019, 32(2):244-250. (in Chinese)
    [7] Wang X, Hoseinnezhad R, Gostar A K, et al. Multi-sensor control for multi-object Bayes filters[J]. Signal Processing, 2018, 142(1):260-270.
    [8] Chen Hui, Han Chongzhao. Sensor control strategy for maneuvering multi-target tracking[J]. Acta Automatica Sinica, 2016, 42(4):512-523. (in Chinese)
    [9] Lou Ke, Cui Baotong, Li Wen. Target tracking algorithm of mobile sensor networks based on flocking control[J]. Control and Decision, 2013, 28(11):1637-1642, 1649. (in Chinese)
    [10] Krishnamurthy V. Emission management for low probability intercept sensors in network centric warfare[J]. IEEE Transactions on Aerospace and Electronic Systems, 2005, 41(1):133-151.
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    [12] Angley D, Ristic B, Suvorova S, et al. Non-myopic sensor scheduling for multistatic sonobuoy fields[J]. Iet Radar Sonar and Navigation, 2017, 11(12):1770-1775.
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    [14] Zhang Z N, Shan G L. UTS-based foresight optimization of sensor scheduling for low interception risk tracking[J]. International Journal of Adaptive Control Signal Processing, 2015, 28(10):921-931.
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Scheduling approach of mobile radar/infrared radiation control

doi: 10.3788/IRLA201948.0904004
  • 1. Department of Electronic and Optical Engineering,Army Engineering University Shijiazhuang Campus,Shijiazhuang 050003,China;
  • 2. College of Mechanical Engineering,Shijiazhuang Tiedao University,Shijiazhuang 050043,China

Abstract: To reduce the radiation risk of mobile radar/infrared cooperative tracking, a scheduling approach of mobile radar/infrared radiation control was proposed. Firstly, a target tracking model was established based on the moving state of the platform and the target, and the tracking accuracy was predicted by using the cubature Kalman filter. Secondly, the radar radiation model was established by introducing the radiation effect, and the prediction methods of the radar radiation status and the system radiation cost were given. Then, the objective function of non-myopic scheduling was constructed with tracking accuracy satisfying task requirements as constraints and non-myopic radiation cost minimization as optimization objectives. Finally, a decision tree search algorithm was designed to solve the problem of high computational complexity. The simulation results show that the proposed scheduling approach has better radiation control effect than the myopic scheduling approach. When the decision step is 3, the radiation cost decreases by 26.5%. Compared with the fixed position scheduling approach, the proposed approach can improve the tracking performance and reduce the radiation cost. When tracking low-speed targets, the tracking error and radiation cost are reduced by 29.9% and 30.5%, respectively.

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