集中式多雷达系统跟踪技术研究
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摘要
在信息融合的目标跟踪领域，集中式跟踪系统因其具有跟踪精度高、航迹起始速度快的优点占有极其重要的地位。虽然集中式跟踪系统有着系统结构复杂、计算负担重的缺点，但是根据一系列先进的传感器综合概念却有着强大的生命力。本文对集中式多雷达系统的跟踪算法在各个组成模块上进行了深入研究，主要研究内容如下：
1．系统地研究了信息融合的基本理论，对信息融合的目的、意义、基本原理、主要研究内容、历史与现状、应用等方面有了总体的概念；根据论文研究内容，特别对集中式多雷达系统的特点、关键问题进行了分析。
2．从空间校准、时间校准和点迹合并三方面，对集中式多雷达系统的点迹处理进行了重点研究；通过点迹处理将集中式多雷达系统的跟踪转换为单雷达多目标跟踪问题。论文详细地研究了应用模式识别中的聚类思想进行点迹合并的算法，有效地减低了状态估计的计算负荷。研究了聚类半径的选取并通过仿真验证了参数的合理性；提出了正确聚类概率这个概念，用以评价某种聚类准则下的聚类质量。
3．对单雷达的多目标跟踪理论(卡尔曼滤波、机动目标模型、航迹起始与终结、跟踪门的形成和互联算法)进行了系统的研究，以此作为点迹处理之后集中式多雷达系统跟踪技术的基础。
4．建立了空间校准、时间校准、点迹合并、航迹起始与终结、跟踪门判断和互联算法六个模块的算法模型；通过数字仿真，探讨了某些模块对跟踪结果的影响并给出相应的仿真结果。最后对分布式系统与集中式系统进行了对比研究。
In the target-tracking field of information fusion, centralized-system take a important role because of it's good tracking-precision and rapid track-origination. Centralized-system have complex structure and need a great deal of calculations,But by a series of advanced senseor integrated conception,it have strong vitality. All modules in the tracking algorithm of multi-radar centralized-system be studied in this paper.The main work are outlined as followed:
Firstly,the basic theory of information-fusion is systemly studied. The data-fusion's intention,significance, basic principle,content,evolution and application are systemly researched.Based on the main content,the trait and key-matter of multi-radar centralized-system are analyzed.
Secondly, By studying the space-calibration,time- calibration and spot-track'unite, the spot-track of multi-radar centralized-system be importantly discussed how to deal with and the tracking problem of multi-radar centralized-system be turned single radar multi-target tracking matter.In the spot-track'unite,the clustering idear of mode-identify is used to settle the problem and the calculation load is be reduced. The selection of clustering radius is studied and the rationality of parameter is validated.The notion of right-clustering-probability is put forward and is used to evaluate the clustering quality of some clustering rule.
Thirdly,the theory of single radar multi-target tracking (kalman filter algorithm ,dynamic target model, track's origination and expiration,the form of tracking-door and association algorithm)is dicussed,which is turned the basis of multi-radar centralized-system's tracking algorithm.
Finally,the algorithm model of six modules(space-calibration, time-calibration,spot-track'unite, track's origination and expiration, the form of tracking-door and association algorithm) are founded.The effect of some modules to tracking result are studied and their intimated results are gained. The intimation result
of centralized-system and distributed-system are compared in the end.
1．系统地研究了信息融合的基本理论，对信息融合的目的、意义、基本原理、主要研究内容、历史与现状、应用等方面有了总体的概念；根据论文研究内容，特别对集中式多雷达系统的特点、关键问题进行了分析。
2．从空间校准、时间校准和点迹合并三方面，对集中式多雷达系统的点迹处理进行了重点研究；通过点迹处理将集中式多雷达系统的跟踪转换为单雷达多目标跟踪问题。论文详细地研究了应用模式识别中的聚类思想进行点迹合并的算法，有效地减低了状态估计的计算负荷。研究了聚类半径的选取并通过仿真验证了参数的合理性；提出了正确聚类概率这个概念，用以评价某种聚类准则下的聚类质量。
3．对单雷达的多目标跟踪理论(卡尔曼滤波、机动目标模型、航迹起始与终结、跟踪门的形成和互联算法)进行了系统的研究，以此作为点迹处理之后集中式多雷达系统跟踪技术的基础。
4．建立了空间校准、时间校准、点迹合并、航迹起始与终结、跟踪门判断和互联算法六个模块的算法模型；通过数字仿真，探讨了某些模块对跟踪结果的影响并给出相应的仿真结果。最后对分布式系统与集中式系统进行了对比研究。
In the target-tracking field of information fusion, centralized-system take a important role because of it's good tracking-precision and rapid track-origination. Centralized-system have complex structure and need a great deal of calculations,But by a series of advanced senseor integrated conception,it have strong vitality. All modules in the tracking algorithm of multi-radar centralized-system be studied in this paper.The main work are outlined as followed:
Firstly,the basic theory of information-fusion is systemly studied. The data-fusion's intention,significance, basic principle,content,evolution and application are systemly researched.Based on the main content,the trait and key-matter of multi-radar centralized-system are analyzed.
Secondly, By studying the space-calibration,time- calibration and spot-track'unite, the spot-track of multi-radar centralized-system be importantly discussed how to deal with and the tracking problem of multi-radar centralized-system be turned single radar multi-target tracking matter.In the spot-track'unite,the clustering idear of mode-identify is used to settle the problem and the calculation load is be reduced. The selection of clustering radius is studied and the rationality of parameter is validated.The notion of right-clustering-probability is put forward and is used to evaluate the clustering quality of some clustering rule.
Thirdly,the theory of single radar multi-target tracking (kalman filter algorithm ,dynamic target model, track's origination and expiration,the form of tracking-door and association algorithm)is dicussed,which is turned the basis of multi-radar centralized-system's tracking algorithm.
Finally,the algorithm model of six modules(space-calibration, time-calibration,spot-track'unite, track's origination and expiration, the form of tracking-door and association algorithm) are founded.The effect of some modules to tracking result are studied and their intimated results are gained. The intimation result
of centralized-system and distributed-system are compared in the end.
引文
1．刘同明、夏祖勋、解洪成著 数据融合技术及其应用 国防工业出版社2000．3
2．何友、王国宏、彭应宁等著 多传感器信息融合及应用 电子工业出版社2001．4
3．周宏仁、敬忠良、王培德著 机动目标跟踪 国防工业出版社1991．8
4．A.费利那、F.A.斯塔德著 孙龙祥、张祖稷等译 雷达数据处理 国防工业出版社 1992．3
5．李金宗著 模式识别导论 高等教育出版社 1994．7
6．蔡宇庆、薛毅、张伯彦著 相控阵雷达数据处理及其仿真技术 国防工业出版社 2000．2
7．杨振起、张永顺、骆永军著 双(多)基地雷达系统 国防工业出版社1998．3
8．袁信、俞济祥、陈哲著 导航系统 航空工业出版社 1993．12
9．陈新海编著 最优估计理论 (张洪钺主编《现代控制理论》((第三册))北京航空学院出版社
10. Y. Bar-Shalom Tracking Methods in a Multitarget Enviroment. IEEE Transactions on Automatic Control, Vol. 24, No. 4, 1978
11. Mulholland R G, Stout D W. Stereographic projection in the national airspace system. IEEE Trans On AES, 1982, 18(1); 48～56
12．万安民、陆静 雷达组网的特点及其抗干扰设计[TJ]．火力与指挥控制 2001．3：41～45
13．余谅、邓宏洋 空中交通管制系统中多雷达数据的配准法 四川联合大学学报(工程科学版) 1999．5 Vol．3(3)
14．徐盐生 滑窗式航迹自动起始 船舶总公司723所 1998．2
15．刘洋、徐毓 基于观测值聚类的多雷达数据融合 雷达与对抗 2002．2
16. Dana M P Registration: a prerequisite for multiple sensor tracking. In:
Multitarget Multisensor Tracking: Advanced Applications, edited by Y. Bar-Shalom, Artech House Inc, 1990
17. Zhou Y, Leung H. Sensor alignment with earth-centered earth-fixed(ECEF) coordinate system. IEEE. AES, 1999; 35(2): 410～417
18. Deta Cruz, Rice A. Sensor registration in multisensor systems. In: SPIE Proc. Signal and Data Processing of Small Target, O. E., 1992:382～393
19. Helmick R E, Rice. Removal of alignment errors in an intergrated system of two 3D sensors. IEEEAES, 1993; 27(4): 1333～1343
20. Leung H, Gault K. Comparison of registration error correction techniques for air surveillance radar network. In: SPIE Proc. Signal and Data Processing of Small Target, San Diego, CA, 1995:498～508
21．李鸿艳、冯新春 一种基于ECEF坐标转换的多雷达误差配准算法 电子对抗技术 2001：16(2)
22．原新、朱齐丹 舰载指控系统航迹相关算法研究 哈尔滨工业大学学报 2002．2：34(1)
23. Hall D L, Linas J. An Introduction to Multisensor Data Fusion. Proc. of the IEEE, 1997, 85(1): 6～18
24. Varshney P K. Scanning the Special Issue on Data Fusion. Proc. of the IEEE, 1997, 85(1): 3～5
25．王宝树、李芳社 基于数据融合技术的多目标跟踪算法研究 西安电子科技大学学报 1998．6：25(3)
26. Freedman D D, Smyton P A. Overview of data fusion activities[A], in Proc. Amer Contr Conf[C]. San Francisco: CA, 1993, 128～130
27. Thomopoulos S C A, Okello N N. Distributed and centralized multisensor detection with misaligned sensor[J]. Inform Sci, 1994, 77(4): 293～323
28．李教、敬忠良、王安 多平台多传感器多源信息融合中的时空校准 空军工程大学学报(自然科学版) 2002．10：3(5)
29. Blackman S S. Multiple-targettracking with radar applications[M]. Dedham: Artech House, 1986
30. D L Hall. Mathematical techniques in multi-sensor data fusion[M]. Norword: Artech House, 1992
31. A D Stoyenko, P A Laplante, R Harrison et al. Doubling the engineers utility[J]. IEEE Spectrum, 1994, 31:32～39
32. Y Zhou, H Leung, P C Yipetal. An exact maximum likelihood registration algorithm for data fusion[J]. IEEE Trans on Signal Processing, 1997, 45(6): 1560
33. Y Zhou, H Leung, K C C Chart et al. A two-step extended Ka.lman filter fusion approach for misaligned sensors[A]. Proc of the Int Confon Multisource-multi-sensor Information Fusion[C]. Las Vegas CSREA Press, 1998:54～58
34. N Nataa, R H Bishop. Solution to a multisensor tracking problem with sensor registration errors[J]. IEEE Trans AES, 1999, 35(1): 354～363
35．陈非、敬忠良、姚晓东 空基多平台多传感器时间空间数据配准与目标跟踪 控制与决策 2001．11：16
36. Bar-Shalom Y. Extension of the probabilistic data association filter in multi-target tracking. Proceedings of 5th Symp. On Nonlinear Estimation, 1974, 16～21
37. Fortman T E, Bar-Shalom Y, Scheffe M. Multitarget tracking using joint Probabilistic data association. Proceedings of the 19th IEEE Conference on Decision and Control, 1980, 807～812
38. Bar-Shalom Y, Fortmann T E. Tracking and data association. Oriando: Academic Press, Inc., 1988
39．郭明、许录平 集中式多雷达系统的数据融合 雷达与对抗 2003．1
40. Y. Bar-Shalom and T. E. Fortman. Tracking and Data Association. New York: Academic Press. 1988
41. Y. Bar-Shalom(Ed.) Multitarget Multisensor Tracking: Advanced Application 1: Norwood, MA: Artech House 1990
42. Y. Bar-Shalom(Ed.) Multitarget Multisensor Tracking: Advanced Application 2: Norwood, MA: Artech House 1992
43. J. A. Roecher and G. L. Phillis. Suboptimal Joint Probabilistic Data
Association. IEEE Transactions on Aerospace and Electronic Systems. 1993, 29(2): 510～517
44. J. A. Roecker. A Class of Near Optimal JPDA Algorithms. IEEE Transactions on Aerospace and Electronic Systems. 1994, 30(2): 504～510
45．田科钰、钟恢扶 一种新的联合概率数据互联算法 火控雷达技术 1999．3：28
46．郁光辉、戴亚平、候朝桢、陈杰 复杂环境下多目标跟踪问题的研究 火力指挥与控制 2002．6：27(2)
47．杨国胜、候朝桢、窦丽华 联合概率数据互联中的双门限跟踪算法研究 2002．8：24(8)
48．陆正刚、杨杰、叶晨洲 多雷达传感器数据融合技术与应用 上海铁道大学学报 2000．7：21(6)
49．陆祥君 雷达组网系统误差校正的一种方法 现代雷达 2001．6
50．王伟伦、梁同京 机载双基地雷达目标距离测定 西北工业大学学报 1997．2
51．王永诚、吴小飞 雷达组网反隐身数据融合技术探讨 现代雷达 1994．8
52．徐毓、李铮、金以慧 基于聚类融合的多目标跟踪算法 传感器技术 2002：21(7)
53．张军英 多雷达站数据融合处理中的聚类方法 计算机仿真 2000．5
54．张洪刚、刘刚、郭军 FCM-VKNN聚类算法的研究 自动化学报 2002．7
2．何友、王国宏、彭应宁等著 多传感器信息融合及应用 电子工业出版社2001．4
3．周宏仁、敬忠良、王培德著 机动目标跟踪 国防工业出版社1991．8
4．A.费利那、F.A.斯塔德著 孙龙祥、张祖稷等译 雷达数据处理 国防工业出版社 1992．3
5．李金宗著 模式识别导论 高等教育出版社 1994．7
6．蔡宇庆、薛毅、张伯彦著 相控阵雷达数据处理及其仿真技术 国防工业出版社 2000．2
7．杨振起、张永顺、骆永军著 双(多)基地雷达系统 国防工业出版社1998．3
8．袁信、俞济祥、陈哲著 导航系统 航空工业出版社 1993．12
9．陈新海编著 最优估计理论 (张洪钺主编《现代控制理论》((第三册))北京航空学院出版社
10. Y. Bar-Shalom Tracking Methods in a Multitarget Enviroment. IEEE Transactions on Automatic Control, Vol. 24, No. 4, 1978
11. Mulholland R G, Stout D W. Stereographic projection in the national airspace system. IEEE Trans On AES, 1982, 18(1); 48～56
12．万安民、陆静 雷达组网的特点及其抗干扰设计[TJ]．火力与指挥控制 2001．3：41～45
13．余谅、邓宏洋 空中交通管制系统中多雷达数据的配准法 四川联合大学学报(工程科学版) 1999．5 Vol．3(3)
14．徐盐生 滑窗式航迹自动起始 船舶总公司723所 1998．2
15．刘洋、徐毓 基于观测值聚类的多雷达数据融合 雷达与对抗 2002．2
16. Dana M P Registration: a prerequisite for multiple sensor tracking. In:
Multitarget Multisensor Tracking: Advanced Applications, edited by Y. Bar-Shalom, Artech House Inc, 1990
17. Zhou Y, Leung H. Sensor alignment with earth-centered earth-fixed(ECEF) coordinate system. IEEE. AES, 1999; 35(2): 410～417
18. Deta Cruz, Rice A. Sensor registration in multisensor systems. In: SPIE Proc. Signal and Data Processing of Small Target, O. E., 1992:382～393
19. Helmick R E, Rice. Removal of alignment errors in an intergrated system of two 3D sensors. IEEEAES, 1993; 27(4): 1333～1343
20. Leung H, Gault K. Comparison of registration error correction techniques for air surveillance radar network. In: SPIE Proc. Signal and Data Processing of Small Target, San Diego, CA, 1995:498～508
21．李鸿艳、冯新春 一种基于ECEF坐标转换的多雷达误差配准算法 电子对抗技术 2001：16(2)
22．原新、朱齐丹 舰载指控系统航迹相关算法研究 哈尔滨工业大学学报 2002．2：34(1)
23. Hall D L, Linas J. An Introduction to Multisensor Data Fusion. Proc. of the IEEE, 1997, 85(1): 6～18
24. Varshney P K. Scanning the Special Issue on Data Fusion. Proc. of the IEEE, 1997, 85(1): 3～5
25．王宝树、李芳社 基于数据融合技术的多目标跟踪算法研究 西安电子科技大学学报 1998．6：25(3)
26. Freedman D D, Smyton P A. Overview of data fusion activities[A], in Proc. Amer Contr Conf[C]. San Francisco: CA, 1993, 128～130
27. Thomopoulos S C A, Okello N N. Distributed and centralized multisensor detection with misaligned sensor[J]. Inform Sci, 1994, 77(4): 293～323
28．李教、敬忠良、王安 多平台多传感器多源信息融合中的时空校准 空军工程大学学报(自然科学版) 2002．10：3(5)
29. Blackman S S. Multiple-targettracking with radar applications[M]. Dedham: Artech House, 1986
30. D L Hall. Mathematical techniques in multi-sensor data fusion[M]. Norword: Artech House, 1992
31. A D Stoyenko, P A Laplante, R Harrison et al. Doubling the engineers utility[J]. IEEE Spectrum, 1994, 31:32～39
32. Y Zhou, H Leung, P C Yipetal. An exact maximum likelihood registration algorithm for data fusion[J]. IEEE Trans on Signal Processing, 1997, 45(6): 1560
33. Y Zhou, H Leung, K C C Chart et al. A two-step extended Ka.lman filter fusion approach for misaligned sensors[A]. Proc of the Int Confon Multisource-multi-sensor Information Fusion[C]. Las Vegas CSREA Press, 1998:54～58
34. N Nataa, R H Bishop. Solution to a multisensor tracking problem with sensor registration errors[J]. IEEE Trans AES, 1999, 35(1): 354～363
35．陈非、敬忠良、姚晓东 空基多平台多传感器时间空间数据配准与目标跟踪 控制与决策 2001．11：16
36. Bar-Shalom Y. Extension of the probabilistic data association filter in multi-target tracking. Proceedings of 5th Symp. On Nonlinear Estimation, 1974, 16～21
37. Fortman T E, Bar-Shalom Y, Scheffe M. Multitarget tracking using joint Probabilistic data association. Proceedings of the 19th IEEE Conference on Decision and Control, 1980, 807～812
38. Bar-Shalom Y, Fortmann T E. Tracking and data association. Oriando: Academic Press, Inc., 1988
39．郭明、许录平 集中式多雷达系统的数据融合 雷达与对抗 2003．1
40. Y. Bar-Shalom and T. E. Fortman. Tracking and Data Association. New York: Academic Press. 1988
41. Y. Bar-Shalom(Ed.) Multitarget Multisensor Tracking: Advanced Application 1: Norwood, MA: Artech House 1990
42. Y. Bar-Shalom(Ed.) Multitarget Multisensor Tracking: Advanced Application 2: Norwood, MA: Artech House 1992
43. J. A. Roecher and G. L. Phillis. Suboptimal Joint Probabilistic Data
Association. IEEE Transactions on Aerospace and Electronic Systems. 1993, 29(2): 510～517
44. J. A. Roecker. A Class of Near Optimal JPDA Algorithms. IEEE Transactions on Aerospace and Electronic Systems. 1994, 30(2): 504～510
45．田科钰、钟恢扶 一种新的联合概率数据互联算法 火控雷达技术 1999．3：28
46．郁光辉、戴亚平、候朝桢、陈杰 复杂环境下多目标跟踪问题的研究 火力指挥与控制 2002．6：27(2)
47．杨国胜、候朝桢、窦丽华 联合概率数据互联中的双门限跟踪算法研究 2002．8：24(8)
48．陆正刚、杨杰、叶晨洲 多雷达传感器数据融合技术与应用 上海铁道大学学报 2000．7：21(6)
49．陆祥君 雷达组网系统误差校正的一种方法 现代雷达 2001．6
50．王伟伦、梁同京 机载双基地雷达目标距离测定 西北工业大学学报 1997．2
51．王永诚、吴小飞 雷达组网反隐身数据融合技术探讨 现代雷达 1994．8
52．徐毓、李铮、金以慧 基于聚类融合的多目标跟踪算法 传感器技术 2002：21(7)
53．张军英 多雷达站数据融合处理中的聚类方法 计算机仿真 2000．5
54．张洪刚、刘刚、郭军 FCM-VKNN聚类算法的研究 自动化学报 2002．7