一种用于杂波中机动目标跟踪的自适应关联波门设计方法

靳标 1; 纠博 1; 苏涛 1; 刘宏伟 1; 张龙 1; 2

doi:10.7652/xjtuxb201410006

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一种用于杂波中机动目标跟踪的自适应关联波门设计方法

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- 一种用于杂波中机动目标跟踪的自适应关联波门设计方法
- A Method to Design Adaptive Correlating Gate for Maneuvering Target Tracking in Clutter
- 西安交通大学学报 2014年48卷第10期页码：35-41
- 作者机构：
  
  西安电子科技大学雷达信号处理国家重点实验室,西安,710071
- 作者简介：
- 基金信息：
  
  : 2014-02-26。作者简介: 靳标(1986—),男,博士生;苏涛(通信作者),男,教授,博士生导师。基金项目: 国家自然科学基金资助项目(61271291);教育部新世纪优秀人才支持计划资助项目(NCET-09-0630)
- DOI：10.7652/xjtuxb201410006
  中图分类号： TN953
- 网络首发：2014-10-10，
  
  纸质出版：2014
- 稿件说明：
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靳标 1, 纠博 1, 苏涛 1, 等. 一种用于杂波中机动目标跟踪的自适应关联波门设计方法[J]. 西安交通大学学报, 2014,48(10):35-41.

A Method to Design Adaptive Correlating Gate for Maneuvering Target Tracking in Clutter[J]. 2014, 48(10): 35-41.
靳标 1, 纠博 1, 苏涛 1, 等. 一种用于杂波中机动目标跟踪的自适应关联波门设计方法[J]. 西安交通大学学报, 2014,48(10):35-41. DOI： 10.7652/xjtuxb201410006.

A Method to Design Adaptive Correlating Gate for Maneuvering Target Tracking in Clutter[J]. 2014, 48(10): 35-41. DOI： 10.7652/xjtuxb201410006.

摘要

针对传统关联波门设计方法在应用于机动目标跟踪时容易引起失跟现象的问题

提出一种新的自适应关联波门设计方法。该方法在综合交互多模型概率数据关联算法的基础上进行关联波门设计

当波门内不存在有效量测时

首先以最大机动水平对应的模型误差协方差对关联波门进行适当扩大

确保量测点迹进入波门。然后假定目标的机动能力已知

在目标运动状态的预测范围内利用观测信息寻找最小均方误差意义下的最优波门中心。该方法可以从根本上改善关联概率

从而降低失跟率

提高目标跟踪精度。仿真结果表明

与传统关联波门设计方法相比

该方法的失跟率降低了30%～40%

而且目标机动时的跟踪精度提高了20%～30%。实测数据同样验证了该方法的有效性。

Abstract

A novel method to design adaptive correlating gate is proposed to solve the problem that the traditional correlating gate design method is easy to cause tracking loss when it is applied in the case of tracking a maneuvering target. The correlating gate is designed based on the comprehensive IMM-PDA algorithm. If there are no validated measurements in the correlating gate

the covariance of model errors with maximal maneuvering level is used to appropriatlely enlarge the gate to guarantee validated measurements existing in the gate. Then it is assumed that the target maneuvering ability is known

and the information of measurements is used to find the optimal gate centre among the predictive range of target motion in the sense of minimizing the mean square error. Since the method fundamentally improves the association probability

the tracking loss probability is decreased and the tracking accuracy is improved. Simulation results and comparisons with the traditional correlating gate design methods show that the tracking loss probability of the proposed method is reduced by 30%-40% and the maneuvering tracking accuracy is improved by 20%-30%. The effectiveness of the proposed method is also verified by the raw radar data.

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references

SINGER R A, SEA R G. New results in optimizing surveillance system tracking and data correlation performance in dense multitarget environments[J]. IEEE Transactions on Automatic Control, 1973, 18(6): 571-582.

KIRUBARAJAN T, BAR-SHALOM Y. Probabilistic data association techniques for target tracking in clutter[J]. Proceedings of the IEEE, 2004, 92(3): 536-557.

JIANG X, HARISHAN K, THARMARASA R, et al. Integrated track initialization and maintenance in heavy clutter using probabilistic data association[J]. Signal Processing, 2014, 94(7): 241-250.

何友, 修建娟, 张晶炜, 等. 雷达数据处理及应用[M]. 2版. 北京: 电子工业出版社, 2009: 120-129.

MAZOR E, AVERBUCH A, BAR-SHALOM Y, et al. Interacting multiple model methods in target tracking: a survey[J]. IEEE Transactions on Aerospace and Electronic Systems, 1998, 34(1): 103-123.

SIGALOV D, MICHAELI T, OSHMAN Y. Tracking a splitting target in clutter using the IMM methodology[C]∥Proceedings of the 27th IEEE Convention of Electrical and Electronics Engineers. Piscataway, NJ, USA: IEEE, 2012: 455-462.

WANG J, FAN B, LI Y, et al. A novel interacting multiple model particle filter for maneuvering target tracking in clutter[J]. Progress in Electromagnetics Research, 2013, 35: 177-191.

BLOM H, BLOEM E A. Exact Bayesian filter and joint IMM coupled PDA tracking of maneuvering targets from possibly missing and false measurements[J]. Automatica, 2006, 42(1): 127-135.

MUSICKI D, SUVOROVA S. Tracking in clutter using IMM-IPDA-based algorithm[J]. IEEE Transactions on Aerospace and Electronic Systems, 2008, 44(1): 111-126.

MUSICKI D, SONG T L, KIM T H. Smoothing multi-scan target tracking in clutter[J]. IEEE Transactions on Signal Processing, 2013, 61(19): 4740-4752.

KIRUBARAJAN T, BAR-SHALOM Y, BLAIR W D, et al. IMMPDAF for radar management and tracking benchmark with ECN[J]. IEEE Transactions on Aerospace and Electronic Systems, 1998, 34(4): 1115-1133.

潘泉, 梁彦, 杨峰, 等. 现代目标跟踪与信息融合[M]. 北京: 国防工业出版社, 2009: 73-124.

MUSICKI D, MORELANDE M R. Gate volume estimation for target tracking[C]∥Proceedings of the 7th International Conference on Information Fusion. Mountain View, CA, USA: International Society of Information Fusion, 2004: 455-462.

WANG X Z, CHALLA S, EVANS R. Gating techniques for maneuvering target tracking in clutter[J]. IEEE Transactions on Aerospace and Electronic Systems, 2002, 38(3): 1087-1097.

程婷, 何子述, 李亚星. 一种具有自适应关联门的杂波中机动目标跟踪算法[J]. 电子与信息学报, 2012, 34(4): 865-870.

CHENG Ting, HE Zishu, LI Yaxing. A maneuvering target tracking algorithm with adaptive association gate in clutters[J]. Journal of Electronics Information Technology, 2012, 34(4): 865-870.

WANG M H, WAN Q, YOU Z S. A gate size estimation algorithm for data association filters[J]. Science in China Series: F Information Science, 2008, 51(4): 425-432.

刘宗香, 谢维信, 黄敬雄. 一种用于三维空间杂波环境机动目标跟踪的数据互联方法[J]. 电子与信息学报, 2009, 31(4): 848-852.

LIU Zongxiang, XIE Weixin, HUANG Jingxiong. A data association method for maneuvering target tracking in three-dimensional space under the circumstance of clutter[J]. Journal of Electronics Information Technology, 2009, 31(4): 848-852.

王亚利, 王文海. 基于时变偏差分离估计的杂波下机动目标跟踪[J]. 系统工程与电子技术, 2010, 32(7): 1408-1410.

WANG Yali, WANG Wenhai. Maneuvering target tracking in clutter based on separate bias estimation[J]. Systems Engineering and Electronics, 2010, 32(7): 1408-1410.

SINGIRESU S R. Engineering optimization: theory and practice[M]. 4th ed. Hoboken, NJ, USA: John Wiley Sons, 2009: 229-425.

任嘉伟,贾维敏,陈辉华,等.二进制偏移载波最小均方误差预滤波无模糊跟踪方法.2013,47(4):125-130.[doi:10.7652/xjtuxb201304021]

李世忠,王国宏,白晶,等.压制干扰下雷达网点目标概率多假设跟踪算法.2012,46(10):101-106.[doi:10.7652/xjtuxb 201210018]

司栋森,李增智,王晓旭.采用四象限探测器的智能跟踪定位算法.2012,46(4):13-17.[doi:10.7652/xjtuxb201204003]

王晓,韩崇昭.用于机动目标跟踪的多模型概率假设密度滤波器.2011,45(12):1-5.[doi:10.7652/xjtuxb201112001]

常国宾,许江宁,李安,等.迭代无味卡尔曼滤波的目标跟踪算法.2011,45(12):70-74.[doi:10.7652/xjtuxb201112013]

闫小喜,韩崇昭.应用Dirichlet分布的概率假设密度多目标跟踪.2011,45(2):6-10.[doi:10.7652/xjtuxb201102002]

刘哲,卫军胡,赵军,等.多源二维测角信息的三维动态目标跟踪定位算法.2008,42(4):462-465.[doi:10.7652/xjtuxb 200804018]

巫春玲,韩崇昭.用于弹道目标跟踪的有限差分扩展卡尔曼滤波算法.2008,42(2):143-146.[doi:10.7652/xjtuxb2008 02004]

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