李为, 李一平, 封锡盛. 基于幅值信息的改进集成概率数据关联算法[J]. 机器人, 2015, 37(5): 513-521. DOI: 10.13973/j.cnki.robot.2015.0513
引用本文: 李为, 李一平, 封锡盛. 基于幅值信息的改进集成概率数据关联算法[J]. 机器人, 2015, 37(5): 513-521. DOI: 10.13973/j.cnki.robot.2015.0513
LI Wei, LI Yiping, FENG Xisheng. Improved Integrated Probabilistic Data Association Algorithm Based on Amplitude Information[J]. ROBOT, 2015, 37(5): 513-521. DOI: 10.13973/j.cnki.robot.2015.0513
Citation: LI Wei, LI Yiping, FENG Xisheng. Improved Integrated Probabilistic Data Association Algorithm Based on Amplitude Information[J]. ROBOT, 2015, 37(5): 513-521. DOI: 10.13973/j.cnki.robot.2015.0513

基于幅值信息的改进集成概率数据关联算法

Improved Integrated Probabilistic Data Association Algorithm Based on Amplitude Information

  • 摘要: 为通过幅值信息进一步提高概率数据关联算法的目标跟踪性能,且考虑到跟踪过程中目标的存在性问题,提出了一种基于幅值信息的集成概率数据关联算法,将幅值似然比引入目标存在概率和关联概率的计算过程中,可以改善集成概率数据关联算法的跟踪性能,提高目标存在性判断的快速性,降低目标丢失概率.最后通过仿真验证了改进算法的有效性.

     

    Abstract: In order to further improve the estimation performance of the PDA (probabilistic data association) algorithm by using AI (amplitude information), an improved IPDA (integrated PDA) algorithm based on AI is proposed, in which the target existence problem in tracking process is considered.The likelihood ratio of amplitude is introduced to compute the probability of target existence and the association probability, which can improve the tracking performance of IPDA algorithm and the rapidity of judging existence for targets, and reduce probability of tracking loss.Finally, simulation results prove the effectiveness of the proposed algorithm.

     

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