计算机科学 ›› 2010, Vol. 37 ›› Issue (5): 206-209.

• 人工智能 • 上一篇    下一篇

基于UIMMS的多站雷达机动目标跟踪研究

赵慧波,潘泉,梁彦,王增福   

  1. (西北工业大学自动化学院 西安710072)
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金重点项目(60634030)资助。

UIMMS of Maneuverable Target Tracking for Multistatic Radar System

ZHAO Hui-bo,PAN Quan,LIANG Yan,WANG Zeng-fu   

  • Online:2018-12-01 Published:2018-12-01

摘要: 针对多站雷达量测机动目标跟踪问题,提出了一种将平滑方法运用于典型的交互式多模型结构的跟踪算法。首先介绍了卡尔曼平滑器(KS),比较了不敏卡尔曼滤波(UKF)和不敏卡尔曼平滑(UKS)两种方法,引入并分析比较了IMMF和IMMS方法。同时,针对目标机动特性以及多雷达量测带来的非线性等问题,构造了多部雷达跟踪机动目标场景,进行了典型方法的比较和新方法的验证,实验结果验证了新方法的有效性。

关键词: 雷达量测,非线性滤波,不敏卡尔曼滤波,不敏卡尔曼平滑,交互式多模型

Abstract: This paper presented the problem of tracking radar measurements of maneuvering target, discussed the kalman smoother, introduced the smooth methods, compared the methods of Unscented Kalman filter with Unscented Kalman smoother, Interacting Multiple Model Filter(IMMF) and Interacting Multiple Model Smoother(IMMF) based on the Multiple Model idea. Meanwhile, for the problem of nonliner based on the radar measurements and the target charicterristic, designed the models of maneuvering target and several radar measurements, compared the classed methods and tested the new methods, experiment results show the effectiveness.

Key words: Radar measurements, Nonlinear filtering, UKF, UKS, Interacting multiple model

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