基于距离分级聚类的机载雷达航迹抗差关联算法

doi:10.3969/j.issn.0372-2112.2018.06.029

电子学报 ›› 2018, Vol. 46 ›› Issue (6): 1475-1481.DOI: 10.3969/j.issn.0372-2112.2018.06.029

基于距离分级聚类的机载雷达航迹抗差关联算法

齐林, 熊伟, 何友

海军航空大学信息融合研究所, 山东烟台 264001

收稿日期:2016-12-09 修回日期:2017-06-15 出版日期:2018-06-25
- 通讯作者:
- 齐林
- 作者简介:
- 熊伟,男,1977年1月出生于江西.现为海军航空大学信息融合研究所教授、博士生导师,研究方向为多源信息融合、指挥自动化等.E-mail:xiongweimail@tom.com;何友,男,1956年10月出生于吉林磐石.中国工程院院士,现为海军航空大学信息融合研究所教授、博士生导师.获国家科技进步奖二等奖3项,国家级教学成果一等奖、二等奖各1项,在国内外发表学术论文100余篇.研究方向雷达自适应检测、多源信息融合、系统仿真与作战模拟、大数据技术等.E-mail:heyou_f@126.com
- 基金资助:
- 国家重点基础研究发展规划 (973计划）项目 (No.61331401）; 国家自然科学基金 (No.61471383，No.61531020，No.61471379，No.61102166，No.91538201）

Anti-bias Track-to-Track Association Algorithm for Aircraft Platforms Based on Distance Hierarchical Clustering

QI Lin, XIONG Wei, HE You

Institute of Information Fusion, Naval Aeronautical University, Yantai, Shandong 264001, China

Received:2016-12-09 Revised:2017-06-15 Online:2018-06-25 Published:2018-06-25
- Corresponding author:
- QI Lin
- Supported by:
- Program of National Program on Key Basic Research Project (973 Program) (No.61331401); National Natural Science Foundation of China (No.61471383, No.61531020, No.61471379, No.61102166, No.91538201)

摘要/Abstract

摘要： 针对目标密集分布、系统误差时变、传感器上报目标不一致等复杂环境下的机载雷达航迹关联问题，本文基于高斯随机矢量统计特性推导出一种基于距离分级聚类的机载雷达航迹抗差关联算法.文中首先推导运动平台等价量测方程，基于等价量测的一阶泰勒级数展开得到全局直角坐标系中状态估计分解方程，基于真实状态对消得到航迹距离矢量并基于距离矢量分级聚类提取同源航迹关联对.文中分别设置了目标密集、随机误差、系统误差适应性实验验证算法性能，仿真结果表明本文算法的关联准确性和环境适应性相比经典的基于参照拓扑特征的航迹关联算法（RET）有较大幅度的提升.

关键词: 航迹关联, 时变系统误差, 等价量测方程, 距离矢量, 分级聚类

Abstract: To address track-to-track association problem for aircraft platforms in complex condition,where targets are distributed closely,sensor biases are time-varied,and different sensors report different targets,an anti-bias track-to-track association algorithm based on distance hierarchical clustering is proposed according to the statistical characteristics of Gaussian random vectors.Equivalent measurement equation for moving platform is firstly derived,linear relationship between state estimates and real states,sensor biases,measurement errors is established based on Taylor series expansion,distance vector is obtained based on real state cancellation,and homologous tracks are extracted based on distance vectors hierarchical clustering.Adaptability experiments are established based on three factors including different targets densities,random errors and sensor biases.Monte Carlo simulations demonstrate significant improvements of association accuracy and complex condition adaptability of the proposed algorithm compared with the classical algorithm based on the reference topology feature (RET).

Key words: track-to-track association, time-varied sensor biases, equivalent measurement equation, distance vectors, hierarchical clustering

中图分类号:

TN953

齐林, 熊伟, 何友. 基于距离分级聚类的机载雷达航迹抗差关联算法[J]. 电子学报, 2018, 46(6): 1475-1481.

QI Lin, XIONG Wei, HE You . Anti-bias Track-to-Track Association Algorithm for Aircraft Platforms Based on Distance Hierarchical Clustering[J]. Acta Electronica Sinica, 2018, 46(6): 1475-1481.

参考文献

[1] Bar-shalom Y,Fortmann T E.Tracking and Data Association[M].Orlando:Academic Press INC,1988.
[2] 何友,王国宏,关欣.信息融合理论及应用[M].北京:电子工业出版社,2010. He Y,Wang G H,Guan X.Information Fusion Theory with Applications[M].Beijing:Publishing House of Electronics Industry,2010.(in Chinese)
[3] Okello N,Ristic B.Maximum likelihood registration for multiple dissimilar sensors[J].IEEE Transactions on Aerospace and Electronic Systems,2003,39(3):1074-1083.
[4] Lin X D,Bar-shalom Y,Kirubarajan T.Exact multi-sensor dynamic bias estimation with local tracks[J].IEEE Transactions on Aerospace and Electronic Systems,2004,40(2):576-590.
[5] Zheng Z W,Zhu Y S.New least squares registration algorithm for data fusion[J].IEEE Transactions on Aerospace and Electronic Systems,2004,40(4):1410-1416.
[6] 石玥,王钺,王树刚,等.基于目标参照拓扑的模糊航迹关联方法[J].国防科技大学学报,2006,28(4):105-109. Shi Y,Wang Y,Wang S G,et al.Fuzzy data association based on target topology of reference[J].Journal of National University of Defense Technology,2006,28(4):105-109.(in Chinese)
[7] Tian W,Wang Y,Shan X M,et al.Track-to-track association for biased data based on the reference topology feature[J].IEEE Signal Processing Letters,2014,21(4):449-453.
[8] Zhu H Y,Han S Y.Track-to-track association based on structural similarity in the presence of sensor biases[J].Journal of Applied Mathematics,2014,2014(1):1-8.
[9] Zhu H Y,Wang W,Wang C.Robust track-to-track association in the presence of sensor biases and missed detections[J].Information Fusion,2016,27:33-40.
[10] 何友,宋强,熊伟.基于傅里叶变换的航迹对准关联算法[J].航空学报,2010,31(2):356-362. He Y,Song Q,Xiong W.A track registration-correlation algorithm based on Fourier transform[J].Acta Aeronautica et Astronautica Sinica,2010,31(2):356-362.(in Chinese)
[11] 何友,宋强,熊伟.基于相位相关的航迹对准关联技术[J].电子学报,2010,38(12):2718-2723. He Y,Song Q,Xiong W.Track alignment-correlation technique based on phase correlation[J].Acta Electronica Sinica,2010,38(12):2718-2723.(in Chinese)
[12] Zhu H Y,Wang C.Joint track-to-track association and sensor registration at the track level[J].Digital Signal Processing,2015,41:48-59.
[13] Li Z,Chen S,Leung H,et al.Joint data association,registration,and fusion using EM-KF[J].IEEE Transactions on Aerospace and Electronic Systems,2010,46(2):496-507.
[14] Zhu H,Leung H,Yuen K.A joint data association,registration,and fusion approach for distributed tracking[J].Information Sciences,2015,324:186-196.
[15] Huang D L,Leung H,Bosse E.A pseudo-measurement approach to simultaneous registration and track fusion[J].IEEE Transactions on Aerospace and Electronic Systems,2012,48(3):2315-2331.
[16] Okello N N,Challa S.Joint sensor registration and track-to-track fusion for distributed trackers[J].IEEE Transactions on Aerospace and Electronic Systems,2004,40(3):808-823.
[17] Zhu H Y,Chen S.Track fusion in the presence of sensor biases[J].IET Signal Processing,2014,8(9):958-967.
[18] Fisher D.Iterative optimization and simplification of hierarchical clustering[J].Journal of Artificial Intelligence Research,1996,4:147-179.
[19] Karypis G,Han E H,Kumar V.Chameleon:A hierarchical clustering algorithm using dynamic modeling[J].IEEE Transactions on Computer,1999,32(8):68-75.
[20] Qi L,Dong K,Liu Y,et al.Anti-bias track-to-track assocition algorithm based on distance detection[J].IET Radar Sonar & Navigation,2017,11(2):269-276.
[21] 齐林,崔亚奇,熊伟,王聪.基于距离检测的自动识别系统和对海雷达航迹抗差关联算法[J].电子与信息学报,2015,37(8):1855-1861. Qi L,Cui Y Q,Xiong W.Anti-bias association algorithm for automatic identification system and radar based on bias detection[J].Journal of Electronics & Information Technology,2015,37(8):1855-1861.(in Chinese)

基于距离分级聚类的机载雷达航迹抗差关联算法

Anti-bias Track-to-Track Association Algorithm for Aircraft Platforms Based on Distance Hierarchical Clustering

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 8

编辑推荐

Metrics

[1]	崔亚奇, 何友, 唐田田, 熊伟. 一种深度学习航迹关联方法[J]. 电子学报, 2022, 50(3): 759-763.
[2]	王晓华, 邹杰, 李立, 梁彦. 基于TBM双层融合架构的航路属性异常检测[J]. 电子学报, 2017, 45(3): 577-583.
[3]	刘颢, 陈世友, 汪学东, 张必银. 一种自适应航迹关联算法[J]. 电子学报, 2013, 41(12): 2416-2421.
[4]	郭蕴华, 袁成. 一种异步航迹关联的变异蚁群算法[J]. 电子学报, 2012, 40(11): 2200-2205.
[5]	陈世友;肖厚;刘颢. 航迹关联不确定度的表示[J]. 电子学报, 2011, 39(7): 1589-1593.
[6]	赵欣;姬红兵;杨柏胜. 基于随机集的RBPF多目标关联跟踪算法[J]. 电子学报, 2011, 39(3): 505-510.
[7]	何友;宋强;熊伟. 基于相位相关的航迹对准关联技术[J]. 电子学报, 2010, 38(12): 2718-2723.
[8]	左东广;韩崇昭;魏瑞轩;郑林. 相关噪声情况下航迹的关联及融合算法[J]. 电子学报, 2002, 30(8): 1117-1120.