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一种改进的无迹粒子滤波器在目标跟踪中的应用 被引量：2

An improved unscented particle filter for target tracking in sensor networks
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摘要 提出了利用神经元网络改进的无迹粒子滤波器(unscented particle filter,UPF)方法.该方法利用神经元网络改进粒子滤波的建议分布,修正UPF跟踪中产生的误差,提高滤波性能.仅用角测量的目标跟踪仿真试验证实了神经元网络对UPF的改进效果,能够在合理的时间消耗代价下,提高无线传感网络中目标跟踪精度. A neural network aided unscented particle filter （UPF） was presented to estimate and track a target in wireless sensor networks. A neural network was used to improve the proposal distribution for the particle filter. By means of neural network, UPF could track the target more effectively and accuratly. Simulation results confirm the improvement of the algorithm, and the algorithm can give lower RMSE than usual unscented particle filters with reasonable time cost.
作者 肖延国 余志军 魏建明 邢涛 阴泽杰
机构地区 中国科学技术大学近代物理系 中国科学院上海微系统与信息技术研究所
出处 《中国科学技术大学学报》 CAS CSCD 北大核心 2008年第2期183-188,共6页 JUSTC
基金 中国科学院知识创新工程重要方向项目 总装预研支撑项目(2004)资助
关键词 粒子滤波器 仅有角测量目标跟踪 无线传感网络 particle filter bearings-only tracking wireless sensor network
分类号 TP274 [自动化与计算机技术—检测技术与自动化装置]
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参考文献18

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共引文献30

同被引文献27

  • 1杨小军,潘泉,王睿,张洪才.粒子滤波进展与展望[J].控制理论与应用,2006,23(2):261-267. 被引量：74
  • 2李良群,姬红兵,罗军辉.迭代扩展卡尔曼粒子滤波器[J].西安电子科技大学学报,2007,34(2):233-238. 被引量：60
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  • 10iChen Qi, Bondon P. A new unscented particle filter[J]. International Conference on Acoustics, Speech and Signal Processing, 2008 : 3 417-3 420.

引证文献2

二级引证文献1

中国科学技术大学学报
2008年 第2期

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