多传感器组网及反隐身、抗干扰接力跟踪技术研究
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摘要
反隐身、抗干扰的高机动目标定位与跟踪方法是一个具有挑战性的课题。单传感器在来袭目标隐身或伴随支援干扰情况下获取的量测信息缺损时,无法进行定位跟踪。多传感器目标跟踪是信息融合技术在目标跟踪领域的应用范例,它将多个传感器信息有机合成,估计目标的运动状态,产生比单一传感器更优越的跟踪性能。因此,研究如何充分利用多传感器的互补信息和冗余信息,实现对感兴趣目标持续、精确的定位于跟踪,具有重要的理论意义和实际的应用价值。本课题基于与航天集团某部的合作项目,以单地基雷达组网探测跟踪空中机动目标(导弹、飞机等)为背景,主要研究了雷达网布站优化、机动目标融合定位跟踪以及量测盲区航迹拟合与跟踪等问题。课题的主要内容如下:
首先,提出了适用于警戒系统的一种雷达优化布站方法,以求在给定的地理环境和应用背景下获得满意的警戒空域、重点探测空域和具备一定的抗干扰、反隐身能力。在分析组网系统探测性能的空间分布和作战原则的基础上,根据所要探测目标的雷达散射面积特性和各雷达的空间探测特性,建立了雷达优化布站的数学模型,并采用遗传算法解决复杂寻优问题。仿真结果验证了该模型进行优化布站的有效性。RCS
其次,基于上述雷达布站探测背景,研究了多传感器融合定位跟踪方法,针对干扰背景下各雷达获取量测信息残缺(方位或距离信息丢失)情况下的定位问题,提出了以纯角度、纯距离、全信息等可定位量测子集优组合优化定位的方法来提高定位精度和扩展可定位空域。同时建立了基于当前统计模型的先定位后KF跟踪模型与直接EKF集中式融合跟踪模型。通过仿真试验比较了两种模型在提高跟踪精度和建立连续航迹的有效性。
最后,针对现有算法跟踪高机动目标存在的问题,提出了一种基于分段航迹识别的新的机动目标跟踪方法,并将该算法用于三维环境下的盲区机动目标航迹拟合与跟踪,该算法具有一定的创新性。仿真结果表明,与现有的机动目标算法相比,在高机动目标跟踪环境下,本文提出的算法拥有较大的优势。
Highly maneuverable target locating and tracking under anti-stealth and anti-interference environment is a challenging subject. Part of measurements of single sensor will be lost in traditional interference or target stealth technology. Multi-sensor target tracking is a paradigm of information fusion technique dealing with target tracking problem. It estimates target state through intelligent integration of multi-sensor data to gain better tracking performance than single sensor does. So it is significant in theory and practical in application to research on how to make use of the redundant and complement information of multi-sensor for object locating and tracking continually, accurately.
In this thesis, the methods of single station radar netting optimize embattle techniques, multi-sensor target locating and tracking fusion, track fitting and tracing on blind area are mainly researched with the background of one project that cooperates with certain department of China Aerospace Science & Industry Company.
Main contents and results are as follow:
First, an approach to radar netting to solve the problem of how optimally to locate the different radars is proposed to achieve a satisfactory surveillance area and some highly-concerned areas inside as well as the ability of anti-stealth and anti interference in some degree. Based on the RCS of the interested targets and the coverage diagrams of the radars, the performance distribution in the surveillance area is analyzed, and a mathematical model for radar netting optimization along with some strategies in the netting algorithm is presented. The approach also takes several factors into account, such as local terrain around radar, man-made interference, stealth target, flying direction of target, track information known previously and so on. Genetic algorithm is introduced to solve the complexity of finding the best result. Simulation experiment illustrates the validity of the approach.
Second, multi-station fusion locating and tracking algorithms under the simulate background provide by first part are researched. in order to get high location precision in most of areas, assembled optimum location algorithm is presented by combining full information location, bearing only location and range only location algorithms, and least square optimization is used for each algorithm to improve precision. based on EKF algorithms, and central fusion structure is selected for tracing. It can solve observability and nonlinear problems when tracing by bearing-only measures. Another algorithms locating first then taking the location data as measure of the KF input is presented. The EKF and KF is based on Current Statistical Model. The simulation experiment is conducted for the case which consists of twenty stations. The result shows that the EKF tracking performances are satisfied comparing with the KF.
Finally, a creative method based on above research is presented for highly maneuvering target tracking and applying under three dimension and blind area circumstance, which is based on segmenting track identifier. Simulation results show that under the circumstance of tracking highly maneuvering targets, comparing with the existence methods this algorithm has a better performance.
首先,提出了适用于警戒系统的一种雷达优化布站方法,以求在给定的地理环境和应用背景下获得满意的警戒空域、重点探测空域和具备一定的抗干扰、反隐身能力。在分析组网系统探测性能的空间分布和作战原则的基础上,根据所要探测目标的雷达散射面积特性和各雷达的空间探测特性,建立了雷达优化布站的数学模型,并采用遗传算法解决复杂寻优问题。仿真结果验证了该模型进行优化布站的有效性。RCS
其次,基于上述雷达布站探测背景,研究了多传感器融合定位跟踪方法,针对干扰背景下各雷达获取量测信息残缺(方位或距离信息丢失)情况下的定位问题,提出了以纯角度、纯距离、全信息等可定位量测子集优组合优化定位的方法来提高定位精度和扩展可定位空域。同时建立了基于当前统计模型的先定位后KF跟踪模型与直接EKF集中式融合跟踪模型。通过仿真试验比较了两种模型在提高跟踪精度和建立连续航迹的有效性。
最后,针对现有算法跟踪高机动目标存在的问题,提出了一种基于分段航迹识别的新的机动目标跟踪方法,并将该算法用于三维环境下的盲区机动目标航迹拟合与跟踪,该算法具有一定的创新性。仿真结果表明,与现有的机动目标算法相比,在高机动目标跟踪环境下,本文提出的算法拥有较大的优势。
Highly maneuverable target locating and tracking under anti-stealth and anti-interference environment is a challenging subject. Part of measurements of single sensor will be lost in traditional interference or target stealth technology. Multi-sensor target tracking is a paradigm of information fusion technique dealing with target tracking problem. It estimates target state through intelligent integration of multi-sensor data to gain better tracking performance than single sensor does. So it is significant in theory and practical in application to research on how to make use of the redundant and complement information of multi-sensor for object locating and tracking continually, accurately.
In this thesis, the methods of single station radar netting optimize embattle techniques, multi-sensor target locating and tracking fusion, track fitting and tracing on blind area are mainly researched with the background of one project that cooperates with certain department of China Aerospace Science & Industry Company.
Main contents and results are as follow:
First, an approach to radar netting to solve the problem of how optimally to locate the different radars is proposed to achieve a satisfactory surveillance area and some highly-concerned areas inside as well as the ability of anti-stealth and anti interference in some degree. Based on the RCS of the interested targets and the coverage diagrams of the radars, the performance distribution in the surveillance area is analyzed, and a mathematical model for radar netting optimization along with some strategies in the netting algorithm is presented. The approach also takes several factors into account, such as local terrain around radar, man-made interference, stealth target, flying direction of target, track information known previously and so on. Genetic algorithm is introduced to solve the complexity of finding the best result. Simulation experiment illustrates the validity of the approach.
Second, multi-station fusion locating and tracking algorithms under the simulate background provide by first part are researched. in order to get high location precision in most of areas, assembled optimum location algorithm is presented by combining full information location, bearing only location and range only location algorithms, and least square optimization is used for each algorithm to improve precision. based on EKF algorithms, and central fusion structure is selected for tracing. It can solve observability and nonlinear problems when tracing by bearing-only measures. Another algorithms locating first then taking the location data as measure of the KF input is presented. The EKF and KF is based on Current Statistical Model. The simulation experiment is conducted for the case which consists of twenty stations. The result shows that the EKF tracking performances are satisfied comparing with the KF.
Finally, a creative method based on above research is presented for highly maneuvering target tracking and applying under three dimension and blind area circumstance, which is based on segmenting track identifier. Simulation results show that under the circumstance of tracking highly maneuvering targets, comparing with the existence methods this algorithm has a better performance.
引文
1 A. Fanna, F.A. Studer. Rardar and Sensor Netting Presentand Future. Microwave Jounal. 1998(1): 97~100
2 Sirnvasan R. Distributed Radar Detcection Theroy. IEEE Aerospace Electron System. 1986(4):133~160
3 E.D. Addio, A. Farina. Overview of Detection Theory in Multistatic Radar. IEEE Trans Aerospace Electron System.1986, (6):133~166
4 H. Karniely, H.T. Siegelmann. Sensor Registration Using Neural Network. IEEE Aerospace Electron System. 2000, 36(1): 85~10
5 Y. Zhou, H. leung, P. Yip. An Exact Maximum Likelihood Registration for Data Fusion. IEEE Trans Aerospace Electron System. 1997, 45(6): 1560~1573
6 F. Gini, L. Fabrizo, K. Parmod. On Distributed Signal Detection Witch Multiple Local Free Parameters. IEEE Trans Aerospace Electron System. 1999, 35(4): 1457~1466
7 F.Gini, F. Lombardini, L. Verrazzani. Roubust Monoparametric Multi-radar CFAR Dection against Non Gaussian Spiky Clutter. IEE Proc. Radar Sonar Naving. 1997,144(34): 131~140
8 K.C.C. Chan, V. Lee, H.A. Leung. Fuzzy Multisensor Tracking System. SPIE. 1999,30(2): 407~419
9 Leung Et Al. Evaluation of Multiple Radar Tracking Trackers in Stressful Environments. IEEE Trans. Aerospace Electron System. 1998,35(4): 664~674
10李建中,李金宝,石胜.传感器网络及其数据管理的概念、问题与进展.软件学报. 2003,14(10): 1717~1727
11阙渭焰,彭应宁.一种针对有向目标的雷达优化布站方法.现代雷达. 1996,18(6): 1~6
12杨仕明,柯炳清,薛正辉.基于遗传算法的区域雷达网优化布站方法.北京理工大学学报. 2005,25(6):535~537
13王维玲.组网反隐身多雷达跟踪数据处理及仿真.系统工程与电子技术. 1994,(12): 67~76
14王万磊,李侠,周启明,王中杰.雷达网反隐身优化部署决策模型及算法研究.现代雷达. 2006,28(11):8~11
15陆祥君.单基地雷达组网反隐身的理论计算和实验设想.现代雷达. 1997,(5):14~19
16徐绵起,李侠,朱剑平,罗玉文.地面对空监视雷达网体系结构研究.现代防御技术. 2003,31(4):34~40
17谢虹,杨志强,何芳.地面监视雷达网抗干扰能力建模研究.电子对抗技术. 2003,18(2):18~21
18徐绵起,李侠,董鹏曙,花良发.一种定量评估监视雷达网生存能力的综合方法.空军雷达学院学报. 2002,16(2):4~6
19郦能敬.监视雷达网效能评价研究(续).现代雷达. 2000,22(2):1~10
20张训立,杨承军,苏鑫,王兴平.弹道导弹防御系统效能分析与措施研究.现代防御技术. 2002, 30(5): 9~12
21卢君明,李瑞棠.组网雷达自组织最小均方差数据融合算法.西安电子科技大学学报. 2000,27(2):161~165
22郭晶,汪浩.组网雷达跟踪系统的类结构设计.国防科技大学学报. 1997,19(2): 78~84;
23何兵,毛士意,张有为,李少红.不同类型传感器的分层融合算法研究.电子学报. 2000,28(6): 4~7
24陆祥君.雷达网系统误差校正的一种方法.现代雷达. 2001,(6): 1~6
25尹以新,何明浩,马晓岩.雷达组网ECCM性能评估方法.系统工程与电子技术.2000,22(11):53~55
26花良发,李侠.雷达组网性能评估指标分析.雷达与对抗. 1999,(4):1~6
27朱丽莉,王朝樨.制导雷达组网技术研究.现代雷达. 2003(7): 1~3
28陈永光,李修和.组网雷达作战能力分析与评估.国防工业出版社. 2006:
29杨仕明,柯炳清,薛正辉.基于遗传算法的区域雷达网优化布站方法.北京理工大学学报. 2005,25(6):534~537
30徐会法,梁幼鸣,刘维炜.基于探测概率的雷达网反隐身开关机模型.雷达科学与技术. 2007,5(2): 95~99
31魏华,李瑞棠.组网雷达中目标照射角的计算及应用.西安电子科技大学学报(自然科学版). 2000,27(6): 696~708
32 E. Waltz, J. Llinas. Multi-sensor Data Fusion. Boston,MA:Artech House,1990
33 D.L. Hall. Mathematic Techniques in Multi-sensor Data Fusion. Boston,MA:Artech House,1992
34 D.L. Hall, J. Llinas. Handbook of Multi-sensor Data Fusion. Washington DC,NY:CRC Press,2001
35刘源.基于模糊信息处理的数据融合方法研究.西安电子科技大学博士论文. 1999: 30~36
36乔向东.信息融合系统中的目标跟踪技术研究.西安电子科技大学博士论文. 2003: 29~34
37何友.多目标多传感器分布信息融合算法研究.清华大学博士论文. 1996: 42~49
38王明辉.多传感器数据融合中几个关键技术的研究,西北工业大学博士论文. 2000: 37~42
39何兵.多传感器数据融合领域若干问题的研究.北京航空航天大学博士论文. 2001: 34~44
40王国宏.分布式检测、跟踪及异类传感器数据关联与引导研究.北京航空航天大学博士论文. 2002:21~34
41杨宏文.多传感器目标跟踪理论与技术研究.国防科学技术大学博士论文. 2000: 33~41
42康耀红.数据融合理论与应用.西安电子科技大学出版社. 1997: 215~223
43刘同明,夏祖勋,解洪成.数据融合技术及其应用.国防工业出版社. 1998: 135~124
44何友,王国宏.传感器信息融合及应用.电子工业出社. 2000: 78~113
45李洪志.信息融合技术.国防工业出版社. 1996: 98~110
46周宏仁,敬忠良,王培德.机动目标跟踪.国防工业出版社. 1991:130~141
47敬忠良.神经网络跟踪理论及应用.国防工业出版社. 1996: 83~96
48权太范.信息融合:神经网络-模糊推理理论与应用.国防工业出版社. 2002: 146~160
49赵宗贵.数据融合方法概论.信息产业部第二十八研究所. 1998: 53~61
50杨靖宇.战场数据融合技术.兵器工业出版社. 1994: 173~188
51蔡庆宇,薛毅,张伯彦.相控阵雷达数据处理及其仿真技术.国防工业出版社. 1997: 146~158
52 J. Levine, R. Marino. Constnats Peed Target Tracken via Bearings-only-measurements. IEEE Transaetionson Aerospace and Electronic Systems. 1992,28l: 174~180
53 E. Fogel, M. Gvaish. Nth-order Dynamics Target Obsevrbility from Angle Measurements. IEEE Transaetions on Aerospace and Eleetronic Systems. 1988,24(3): 30~38
54韦毅.红外无源定位技术研究.西安电子科技大学硕士论文. 2002: 29~35
55刘宗香.被动传感器组网系统目标探测与跟踪方法.西安电子科技大学博士论文. 2005: 38~48
56辛云宏.红外搜索与跟踪系统的点目标定位及跟踪算法研究.西安电子科技大学博士论文. 2005: 36~45
57梁恒译.基于MATLAB的数值分析.第二版.电子工业出版社. 2002: 168~172
58李宏凯,王强,吕宾滨.用曲线拟合预测空中雷达目标.舰船电子对抗. 2006,29(6): 47~49
59廉杰航迹起始及机动目标跟踪方法的研究哈尔滨工业大学优秀硕士论文. 2006
60 K. B. Lim, K. Xin, G. S. Hong. Detection and Estimation of Circular Arc Segments. Pattern Recognition Letters. 1995,16: 627~636
61 P. L. Rosin, G.A. W. West. Segmenting Curves Int Elliptic Arcs and Straight Lines.Prented at Computer Vision. 1990: 393~405
62 S. Hsin-Teng, H. Wu-Chih. Multi-primitive Segmentation of Planar Curves-a Two-level Breakpoint Classification and Tuning Approach. IEEE Trans. Pattern Anal. Machine Intell. 1999,20(4): 791~797
63 L. Wenyin, D. Dori. Incremental Arc Segmentation Algorithm and Its Evaluation. IEEE Trans. Pattern Anal. Machine Intell. 1998,20(4): 421~431
64 J. Angeles, A. Alivizatos, P. J. Zsombor-Murray. The Synthesis of Smooth Trajectories for Pick-and-Place Operations. IEEE Transactions on Systems, Man and Cybernetics. 1988,18(6): 173~178
65 F. M. Yoshimoto, M. Harada. Automatic Knot Placement by a Genetic Algorithm for Data Fitting with a Spline. Presented at International Conference on Shape Modeling Interational. 1999: 241~252
66李明亮,安渭琳,常龙.组网雷达反隐身效果评估.中国雷达. 2006,(4) : 16~19
67郦能敬.对空情报雷达的频率优选.雷达科学与技术. 2006,4(1) : 1~6
68郦能敬.对空情报雷达的测量精度分析.雷达科学与技术. 2005,3(1) : 1~10
69郦能敬.对空监视雷达探测威力检飞的几个问题.雷达科学与技术. 2003,1(1) : 7~13
70丁鹭飞,耿富录.雷达原理.西安电子科技大学出版社. 1984: 124~133
71何友,关键,彭应宁.雷达自动监测与恒虚警处理.清华大学出版社. 1999: 68~72
72 F E Nathanson. Radar Design Principles. 2nd edition. McGraw-Hill. 1990: 92~101
73权太范.信息融合神经网络镇糊推理理论与应用.国防工业出版社. 2002: 182~197
74朱允民.多传感器分布式统计判决.科学出版社. 2000: 83~94
75李丹.机动目标跟踪的滤波方法研究.计算机仿真. 2007,24(4):82~86
76 Qiu B S, Liu H Y, Cai Y Q. An Adaptive Parameter Model for Maneuvering Target Tracking. Proceedings of the 4th International Conference on Signal Processing. ICSP IEEE. 1998: 465~469
77 Singer R A. Estimating Optimal Tracking Filter Performance for Manned Maneuvering Targets. IEEE Transactions on Aerospace and Electronic Systems,1970,6(4): 473~483
78 Pan Q, Wang P D, Zhou H R. Innovation Filter and Its Application to the IMM Algorithm Using Zhou Model. International Conference on Circuits and Systems. Shenzhen China. IEEE. 1991: 801~804
79 Zhang J S, Yang W Q, Hu S Q. Target Tracking Using the Interactive Multiple Model Method. Journal of Beijing Institute of Technology. 1998,7(3): 299~304
80周明,孙树栋.遗传算法原理及应用.国防工业出版社. 1999: 1~89
81 Bucy R S, Renne K D. Digital Synthesis of Nonlinear Filters. Automatica. 1971,7(3): 287~289
82孙仲康,周一宇.单-多基地有源无源定位技术.国防工业出版社. 1996: 28~38
2 Sirnvasan R. Distributed Radar Detcection Theroy. IEEE Aerospace Electron System. 1986(4):133~160
3 E.D. Addio, A. Farina. Overview of Detection Theory in Multistatic Radar. IEEE Trans Aerospace Electron System.1986, (6):133~166
4 H. Karniely, H.T. Siegelmann. Sensor Registration Using Neural Network. IEEE Aerospace Electron System. 2000, 36(1): 85~10
5 Y. Zhou, H. leung, P. Yip. An Exact Maximum Likelihood Registration for Data Fusion. IEEE Trans Aerospace Electron System. 1997, 45(6): 1560~1573
6 F. Gini, L. Fabrizo, K. Parmod. On Distributed Signal Detection Witch Multiple Local Free Parameters. IEEE Trans Aerospace Electron System. 1999, 35(4): 1457~1466
7 F.Gini, F. Lombardini, L. Verrazzani. Roubust Monoparametric Multi-radar CFAR Dection against Non Gaussian Spiky Clutter. IEE Proc. Radar Sonar Naving. 1997,144(34): 131~140
8 K.C.C. Chan, V. Lee, H.A. Leung. Fuzzy Multisensor Tracking System. SPIE. 1999,30(2): 407~419
9 Leung Et Al. Evaluation of Multiple Radar Tracking Trackers in Stressful Environments. IEEE Trans. Aerospace Electron System. 1998,35(4): 664~674
10李建中,李金宝,石胜.传感器网络及其数据管理的概念、问题与进展.软件学报. 2003,14(10): 1717~1727
11阙渭焰,彭应宁.一种针对有向目标的雷达优化布站方法.现代雷达. 1996,18(6): 1~6
12杨仕明,柯炳清,薛正辉.基于遗传算法的区域雷达网优化布站方法.北京理工大学学报. 2005,25(6):535~537
13王维玲.组网反隐身多雷达跟踪数据处理及仿真.系统工程与电子技术. 1994,(12): 67~76
14王万磊,李侠,周启明,王中杰.雷达网反隐身优化部署决策模型及算法研究.现代雷达. 2006,28(11):8~11
15陆祥君.单基地雷达组网反隐身的理论计算和实验设想.现代雷达. 1997,(5):14~19
16徐绵起,李侠,朱剑平,罗玉文.地面对空监视雷达网体系结构研究.现代防御技术. 2003,31(4):34~40
17谢虹,杨志强,何芳.地面监视雷达网抗干扰能力建模研究.电子对抗技术. 2003,18(2):18~21
18徐绵起,李侠,董鹏曙,花良发.一种定量评估监视雷达网生存能力的综合方法.空军雷达学院学报. 2002,16(2):4~6
19郦能敬.监视雷达网效能评价研究(续).现代雷达. 2000,22(2):1~10
20张训立,杨承军,苏鑫,王兴平.弹道导弹防御系统效能分析与措施研究.现代防御技术. 2002, 30(5): 9~12
21卢君明,李瑞棠.组网雷达自组织最小均方差数据融合算法.西安电子科技大学学报. 2000,27(2):161~165
22郭晶,汪浩.组网雷达跟踪系统的类结构设计.国防科技大学学报. 1997,19(2): 78~84;
23何兵,毛士意,张有为,李少红.不同类型传感器的分层融合算法研究.电子学报. 2000,28(6): 4~7
24陆祥君.雷达网系统误差校正的一种方法.现代雷达. 2001,(6): 1~6
25尹以新,何明浩,马晓岩.雷达组网ECCM性能评估方法.系统工程与电子技术.2000,22(11):53~55
26花良发,李侠.雷达组网性能评估指标分析.雷达与对抗. 1999,(4):1~6
27朱丽莉,王朝樨.制导雷达组网技术研究.现代雷达. 2003(7): 1~3
28陈永光,李修和.组网雷达作战能力分析与评估.国防工业出版社. 2006:
29杨仕明,柯炳清,薛正辉.基于遗传算法的区域雷达网优化布站方法.北京理工大学学报. 2005,25(6):534~537
30徐会法,梁幼鸣,刘维炜.基于探测概率的雷达网反隐身开关机模型.雷达科学与技术. 2007,5(2): 95~99
31魏华,李瑞棠.组网雷达中目标照射角的计算及应用.西安电子科技大学学报(自然科学版). 2000,27(6): 696~708
32 E. Waltz, J. Llinas. Multi-sensor Data Fusion. Boston,MA:Artech House,1990
33 D.L. Hall. Mathematic Techniques in Multi-sensor Data Fusion. Boston,MA:Artech House,1992
34 D.L. Hall, J. Llinas. Handbook of Multi-sensor Data Fusion. Washington DC,NY:CRC Press,2001
35刘源.基于模糊信息处理的数据融合方法研究.西安电子科技大学博士论文. 1999: 30~36
36乔向东.信息融合系统中的目标跟踪技术研究.西安电子科技大学博士论文. 2003: 29~34
37何友.多目标多传感器分布信息融合算法研究.清华大学博士论文. 1996: 42~49
38王明辉.多传感器数据融合中几个关键技术的研究,西北工业大学博士论文. 2000: 37~42
39何兵.多传感器数据融合领域若干问题的研究.北京航空航天大学博士论文. 2001: 34~44
40王国宏.分布式检测、跟踪及异类传感器数据关联与引导研究.北京航空航天大学博士论文. 2002:21~34
41杨宏文.多传感器目标跟踪理论与技术研究.国防科学技术大学博士论文. 2000: 33~41
42康耀红.数据融合理论与应用.西安电子科技大学出版社. 1997: 215~223
43刘同明,夏祖勋,解洪成.数据融合技术及其应用.国防工业出版社. 1998: 135~124
44何友,王国宏.传感器信息融合及应用.电子工业出社. 2000: 78~113
45李洪志.信息融合技术.国防工业出版社. 1996: 98~110
46周宏仁,敬忠良,王培德.机动目标跟踪.国防工业出版社. 1991:130~141
47敬忠良.神经网络跟踪理论及应用.国防工业出版社. 1996: 83~96
48权太范.信息融合:神经网络-模糊推理理论与应用.国防工业出版社. 2002: 146~160
49赵宗贵.数据融合方法概论.信息产业部第二十八研究所. 1998: 53~61
50杨靖宇.战场数据融合技术.兵器工业出版社. 1994: 173~188
51蔡庆宇,薛毅,张伯彦.相控阵雷达数据处理及其仿真技术.国防工业出版社. 1997: 146~158
52 J. Levine, R. Marino. Constnats Peed Target Tracken via Bearings-only-measurements. IEEE Transaetionson Aerospace and Electronic Systems. 1992,28l: 174~180
53 E. Fogel, M. Gvaish. Nth-order Dynamics Target Obsevrbility from Angle Measurements. IEEE Transaetions on Aerospace and Eleetronic Systems. 1988,24(3): 30~38
54韦毅.红外无源定位技术研究.西安电子科技大学硕士论文. 2002: 29~35
55刘宗香.被动传感器组网系统目标探测与跟踪方法.西安电子科技大学博士论文. 2005: 38~48
56辛云宏.红外搜索与跟踪系统的点目标定位及跟踪算法研究.西安电子科技大学博士论文. 2005: 36~45
57梁恒译.基于MATLAB的数值分析.第二版.电子工业出版社. 2002: 168~172
58李宏凯,王强,吕宾滨.用曲线拟合预测空中雷达目标.舰船电子对抗. 2006,29(6): 47~49
59廉杰航迹起始及机动目标跟踪方法的研究哈尔滨工业大学优秀硕士论文. 2006
60 K. B. Lim, K. Xin, G. S. Hong. Detection and Estimation of Circular Arc Segments. Pattern Recognition Letters. 1995,16: 627~636
61 P. L. Rosin, G.A. W. West. Segmenting Curves Int Elliptic Arcs and Straight Lines.Prented at Computer Vision. 1990: 393~405
62 S. Hsin-Teng, H. Wu-Chih. Multi-primitive Segmentation of Planar Curves-a Two-level Breakpoint Classification and Tuning Approach. IEEE Trans. Pattern Anal. Machine Intell. 1999,20(4): 791~797
63 L. Wenyin, D. Dori. Incremental Arc Segmentation Algorithm and Its Evaluation. IEEE Trans. Pattern Anal. Machine Intell. 1998,20(4): 421~431
64 J. Angeles, A. Alivizatos, P. J. Zsombor-Murray. The Synthesis of Smooth Trajectories for Pick-and-Place Operations. IEEE Transactions on Systems, Man and Cybernetics. 1988,18(6): 173~178
65 F. M. Yoshimoto, M. Harada. Automatic Knot Placement by a Genetic Algorithm for Data Fitting with a Spline. Presented at International Conference on Shape Modeling Interational. 1999: 241~252
66李明亮,安渭琳,常龙.组网雷达反隐身效果评估.中国雷达. 2006,(4) : 16~19
67郦能敬.对空情报雷达的频率优选.雷达科学与技术. 2006,4(1) : 1~6
68郦能敬.对空情报雷达的测量精度分析.雷达科学与技术. 2005,3(1) : 1~10
69郦能敬.对空监视雷达探测威力检飞的几个问题.雷达科学与技术. 2003,1(1) : 7~13
70丁鹭飞,耿富录.雷达原理.西安电子科技大学出版社. 1984: 124~133
71何友,关键,彭应宁.雷达自动监测与恒虚警处理.清华大学出版社. 1999: 68~72
72 F E Nathanson. Radar Design Principles. 2nd edition. McGraw-Hill. 1990: 92~101
73权太范.信息融合神经网络镇糊推理理论与应用.国防工业出版社. 2002: 182~197
74朱允民.多传感器分布式统计判决.科学出版社. 2000: 83~94
75李丹.机动目标跟踪的滤波方法研究.计算机仿真. 2007,24(4):82~86
76 Qiu B S, Liu H Y, Cai Y Q. An Adaptive Parameter Model for Maneuvering Target Tracking. Proceedings of the 4th International Conference on Signal Processing. ICSP IEEE. 1998: 465~469
77 Singer R A. Estimating Optimal Tracking Filter Performance for Manned Maneuvering Targets. IEEE Transactions on Aerospace and Electronic Systems,1970,6(4): 473~483
78 Pan Q, Wang P D, Zhou H R. Innovation Filter and Its Application to the IMM Algorithm Using Zhou Model. International Conference on Circuits and Systems. Shenzhen China. IEEE. 1991: 801~804
79 Zhang J S, Yang W Q, Hu S Q. Target Tracking Using the Interactive Multiple Model Method. Journal of Beijing Institute of Technology. 1998,7(3): 299~304
80周明,孙树栋.遗传算法原理及应用.国防工业出版社. 1999: 1~89
81 Bucy R S, Renne K D. Digital Synthesis of Nonlinear Filters. Automatica. 1971,7(3): 287~289
82孙仲康,周一宇.单-多基地有源无源定位技术.国防工业出版社. 1996: 28~38