Journal of Systems Engineering and Electronics ›› 2009, Vol. 31 ›› Issue (3): 541-544.

• 传感器与信号处理 • 上一篇    下一篇

基于模糊推理的机动目标跟踪

韩红, 陈兆平, 焦李成, 智建纬   

  1. 西安电子科技大学智能信息处理研究所和智能感知与图像理解教育部重点实验室, 陕西, 西安, 710071
  • 收稿日期:2008-01-07 修回日期:2008-03-25 出版日期:2009-03-20 发布日期:2010-01-03
  • 作者简介:韩红(1974- ),女,副教授,主要研究方向为多传感器信息融合,机器视觉.E-mail:zhpchen2008@163.com
  • 基金资助:
    国家“863”高技术研究发展计划基金(2007AA12Z136;2006AA01Z107);国家自然科学基金(60703108);教育部长江学者和创新团队支持计划(IRT0645)资助课题

Maneuvering target tracking based on fuzzy reasoning

HAN Hong, CHEN Zhao-ping, JIAO Li-cheng, ZHI Jian-wei   

  1. Key Lab. of Intelligent Perception and Image Understanding of Ministry of Education of China, Inst. of Intelligent Information Processing, Xidian Univ., Xi’an 710071, China
  • Received:2008-01-07 Revised:2008-03-25 Online:2009-03-20 Published:2010-01-03

摘要: 针对"当前"统计模型算法对目标强机动时跟踪精度下降的问题,提出一种改进算法。该算法在"当前"统计模型的基础上,采用双滤波器并行结构,提取目标的状态信息,使用模糊推理的方法求解调节因子,通过调节因子实时调整滤波器的预测协方差,在保证对目标弱机动跟踪精度的同时,提高了目标发生强机动时的跟踪精度。仿真结果表明目标强机动时,该算法的跟踪精度明显高于"当前"统计模型算法。

Abstract: The performance of the "current" statistical model algorithm gets worse when there is a sudden maneuver.To solve this problem,an improved algorithm is presented.This algorithm is implemented through a pair of parallel adaptive filters together with information fusion technique.By introducing the state information of targets,the output of the fuzzy system can adjust the predicted covariance of the filter adaptively.The simulation results show that the proposed algorithm has better performance when there is a sudden maneuver.

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