J4 ›› 2011, Vol. 38 ›› Issue (2): 72-76+128.doi: 10.3969/j.issn.1001-2400.2011.02.013

• 研究论文 • 上一篇    下一篇

一种模糊推理强机动目标跟踪新算法

杨金龙;姬红兵;樊振华   

  1. (西安电子科技大学 电子工程学院,陕西 西安  710071)
  • 收稿日期:2010-01-29 出版日期:2011-04-20 发布日期:2011-05-26
  • 作者简介:杨金龙(1981-),男,西安电子科技大学博士研究生,E-mail: yjlgedeng@163.com.
  • 基金资助:

    国家自然科学基金资助项目(60871074)

Novel algorithm for high maneuvering target tracking based on fuzzy reasoning MIE

YANG Jinlong;JI Hongbing;FAN Zhenhua   

  1. (School of Electronic Engineering, Xidian Univ., Xi'an  710071, China)
  • Received:2010-01-29 Online:2011-04-20 Published:2011-05-26

摘要:

针对机动目标状态估计算法对强机动目标跟踪性能下降,甚至发散的问题,在机动目标状态估计算法基础上引入模糊推理多重修正因子,提出一种新的强机动目标自适应跟踪算法.采用残差统计距离和目标机动加速度的2-范数作为模糊输入量,自适应地计算出多重修正因子来实时调节预测协方差.该算法保留了对一般匀速或弱机动目标的高精度跟踪性能,同时增强了滤波器对强机动目标的自适应跟踪能力.仿真结果表明,新算法提高了对强机动目标的估计精度,加快了跟踪的收敛速度.

关键词: 目标跟踪, 模糊推理, 机动目标状态估计, 修正因子

Abstract:

When tracking high maneuvering targets, the sudden changes of target states may cause serious decline and even divergence in the performance of conventional modified input estimation(MIE) algorithms. Taking this into account, this paper presents a novel adaptive tracking algorithm for high maneuvering targets. Fuzzy multiple modified factors are introduced on the basis of the MIE algorithm. Using the statistics residuals distance and the 2-norm of the acceleration vector as the input of the fuzzy controller, multiple modified factors are self-adapatively worked out to adjust predicted covariance, and the tracking capacity of this algorithm towards high maneuvering targets is improved. This algorithm also keeps a good performance for general uniform or low maneuvering targets. Simulation results obtained show the effectiveness of this algorithm. Compared with the constant factor MIE algorithm, this algorithm can lead to a higher estimation accuracy and a faster convergence speed.

Key words: target tracking, fuzzy reasoning, modified input estimation, modified factors