电子学报 ›› 2016, Vol. 44 ›› Issue (7): 1656-1661.DOI: 10.3969/j.issn.0372-2112.2016.07.020

• 学术论文 • 上一篇    下一篇

极坐标系下可处理多普勒量测的BLUE跟踪算法

李丹1, 王炜2   

  1. 1. 武汉理工大学理学院, 湖北武汉 430070;
    2. 海军工程大学理学院, 湖北武汉 430033
  • 收稿日期:2014-12-29 修回日期:2015-10-10 出版日期:2016-07-25 发布日期:2016-07-25
  • 作者简介:李丹 女,1980年5月出生,湖北随州人.2015年在武汉理工大学获博士学位.武汉理工大学理学院教师,主要从事统计学、信息处理方面的研究.E-mail:lidan0520@163.com
  • 基金资助:

    国家自然科学基金(No.11571133,No.51307128);中央高校基本科研业务费专项资金(No.2015IA005);海军工程大学自然科学基金(No.HJGSK2014G121)

The BLUE Tracking Algorithm with the Doppler Measurements in the Polar Coordinates

LI Dan1, WANG Wei2   

  1. 1. School of Science, Wuhan University of Science and Technology, Wuhan, Hubei 430070, China;
    2. School of Science, Naval University of Engineering, Wuhan, Hubei 430033, China
  • Received:2014-12-29 Revised:2015-10-10 Online:2016-07-25 Published:2016-07-25

摘要:

事实已表明包含目标速度信息的多普勒量测具有有效提高目标状态估计精度的潜力.该文在直角坐标系下提出两种可使用转换多普勒量测(即距离量测与多普勒量测的乘积)的滤波器,一种借助了构造的多普勒伪状态,另一种没有借助多普勒伪状态.从理论上讲,它们都是在最佳线性无偏估计准则下的最优线性无偏滤波器,并且避免了量测转换方法的根本缺陷.通过将近似处理后的两种新型最优线性滤波器与目前几种流行的方法进行仿真比较,验证了所提出的滤波器的优越性.

关键词: 目标跟踪, 多普勒, 最佳线性无偏估计, 量测转换

Abstract:

In fact,the Doppler measurement containing information of target velocity has the potential capability of improving the tracking performance.Two filters are proposed which can use converted Doppler measurements (i.e.the product of the range measurements and Doppler measurements) in the Cartesian coordinates.One filter uses the Doppler pseudo-states;another doesn't use the Doppler pseudo-states.These novel filters are theoretically optimal in the rule of the best linear unbiased estimation in the Cartesian coordinates,and they are free from the fundamental limitations of the measurement-conversion approach.Based on simulation experiments,the approximate,recursive implementations of these two novel filters are compared with those obtained by five state-of-the-art conversion techniques recently.Simulation results demonstrate the effectiveness of the proposed two filters.

Key words: target tracking, Doppler, best linear unbiased estimation (BLUE), converted measurement

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