北京航空航天大学学报 ›› 2019, Vol. 45 ›› Issue (7): 1435-1443.doi: 10.13700/j.bh.1001-5965.2018.0668

• 论文 • 上一篇    下一篇

自适应关联波门机动群目标跟踪算法

杜明洋1, 毕大平1, 潘继飞1,2, 王渊博3   

  1. 1. 国防科技大学 电子对抗学院, 合肥 230037;
    2. 电子对抗信息处理实验室, 合肥 230037;
    3. 中国人民解放军66026部队, 张家口 075146
  • 收稿日期:2018-11-20 出版日期:2019-07-20 发布日期:2019-07-25
  • 通讯作者: 毕大平 E-mail:bdpeei@163.com
  • 作者简介:杜明洋 男,硕士研究生。主要研究方向:目标跟踪与雷达信号处理;毕大平 男,硕士,教授,博士生导师。主要研究方向:电子对抗侦察和干扰新技术;潘继飞 男,博士,副教授。主要研究方向:雷达对抗技术与信号与信息处理技术;王渊博 男,硕士,工程师。主要研究方向:雷达信号处理技术。
  • 基金资助:
    国家自然科学基金(61671453);安徽省自然科学基金(1608085MF123)

Maneuvering group target tracking algorithm with adaptive correlation gate

DU Mingyang1, BI Daping1, PAN Jifei1,2, WANG Yuanbo3   

  1. 1. College of Electronic Engineering, National University of Defense Technology, Hefei 230037, China;
    2. Laboratory of Electronic Countermeasures Information Processing, Hefei 230037, China;
    3. Unit 66026 of the PLA, Zhangjiakou 075146, China
  • Received:2018-11-20 Online:2019-07-20 Published:2019-07-25
  • Supported by:
    National Natural Science Foundation of China (61671453); Natural Science Foundation of Anhui Province, China (1608085 MF123)

摘要: 为解决中心群跟踪(CGT)算法中由于群机动造成的量测丢失、估计误差增大的问题,提出了一种基于自适应关联波门的机动群目标跟踪算法。首先,将CGT算法与交互式多模型(IMM)算法结合,并利用最新量测信息对IMM算法中的转移概率矩阵进行实时修正。其次,设计了一种用于整体机动和分离机动的自适应关联波门,根据机动时刻模型的新息协方差对其进行自适应调整,确保量测点迹进入波门。仿真结果表明,所提算法一方面减小了传统固定转移概率矩阵带来的估计误差,将优势模型的平均概率由0.58增加到了0.7;另一方面,设计的自适应关联波门有效解决了目标机动带来的有效量测减少的问题,相比于传统波门,目标失跟率减少了30%,具备工程实用性。

关键词: 群目标, 中心群跟踪(CGT), 交互式多模型(IMM), 转移概率, 关联波门

Abstract: A new maneuvering group target tracking algorithm based on adaptive correlation gate for solving measurement loss and increasing estimation error of centroid group tracking (CGT) algorithm when tracking maneuvering group target in clutter is proposed in this paper. First, CGT algorithm is combined with interacting multiple model (IMM) algorithm and the latest measurement information is used to modify the transition probability matrix. Second, a new adaptive correlation gate is designed when tracking overall and split maneuvering by the covariance of model innovation to guarantee valid measurements existing in the gate. The simulation results show that the proposed algorithm decreases the estimated error of traditional IMM algorithm with fixed transition probability matrix and increases the probability of dominant model from 0.58 to 0.7 on the one hand. On the other hand, the loss-target rate of adaptive gate designed in this paper is reduced by 30% compared to traditional gate on account of decreasing valid measurement during target maneuvering. The proposed algorithm has a certain practical value in engineering.

Key words: group target, centroid group tracking (CGT), interacting multiple model (IMM), transition probabilities, correlation gate

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