Non-myopic scheduling algorithm for multi-sensor collaborative detection and tracking

QIAO Cheng-lin1 SHAN Gan-lin1 WANG Yi-chuan2 LIU Heng3

(1.Department of Electronic and Optical Engineering, Shijiazhuang Campus of Army Engineering University, Shijiazhuang, Hebei Province, China 050003)
(2.College of Joint Service, National Defense University, Beijing 100858)
(3.Unit 63870 of PLA, Huayin 714200)

【Abstract】In consideration of the radiation control for target detection and tracking, a non-myopic scheduling algorithm for multi-sensor collaborative detection and tracking is proposed. Firstly, the model of target tracking and radiation control is formulated as a partially observable Markov decision process (POMDP). Then, the detection probability of the new target is calculated by the randomly distributed particles; the non-myopic tracking accuracy is predicted by the posterior Carmér-Rao lower bound (PCRLB); the non-myopic radiation cost is derived by the hidden Markov model (HMM) filter. Finally, the non-myopic optimization function of radiation control constrained by the detection probability of the new target and the tracking accuracy of the existing target is set up. The optimal scheduling sequence is obtained by the branch and bound algorithm based on a greedy search. Simulation results verify the effectiveness of the proposed algorithm.

【Keywords】 sensor scheduling; collaborative detection and tracking; POMDP; branch and bound; PCRLB;


【Funds】 National Defense Pre-research Foundation, China (012015012600A2203)

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This Article


CN: 21-1124/TP

Vol 35, No. 04, Pages 799-806

April 2020


Article Outline


  • 0 Introduction
  • 1 Problem description and system modeling
  • 2 Problem solution
  • 3 Simulation
  • 4 Conclusions
  • References