• Electronics Optics & Control
  • Vol. 24, Issue 5, 15 (2017)
XU Gong-guo1, DUAN Xiu-sheng1, XU Hong-hao2, and SHAN Gan-lin1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2017.05.003 Cite this Article
    XU Gong-guo, DUAN Xiu-sheng, XU Hong-hao, SHAN Gan-lin. Multi-sensor Coordinated Allocation Based on Rényi Divergence and Improved QPSO Algorithm[J]. Electronics Optics & Control, 2017, 24(5): 15 Copy Citation Text show less

    Abstract

    Aiming at the multi-sensor management problem in target recognition stage under complex aerial defense combat environment, a new multi-sensor scheduling method is proposed based on Rényi divergence.Firstly, the D-S evidence theory is applied to obtain the Rényi divergence of different sensors matched with different targets.Then, the sensor allocation model based on the maximized total Rényi divergence is established.Besides, the Quantum Particle Swarm Optimization (QPSO) algorithm is improved in order to quickly solve the management model.Finally, the experiments show that the improved algorithm is feasible and effective.
    XU Gong-guo, DUAN Xiu-sheng, XU Hong-hao, SHAN Gan-lin. Multi-sensor Coordinated Allocation Based on Rényi Divergence and Improved QPSO Algorithm[J]. Electronics Optics & Control, 2017, 24(5): 15
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