特征辅助的目标机动检测技术
|
摘要
机动检测是属于一类典型的突变检测问题,是行为辨识、目标跟踪与识别等研究领域所广泛关注一个重要课题,在机动目标跟踪与拦截、自动驾驶、汽车防撞等军、民用领域都有着广泛的应用。然而目前的机动检测技术主要依赖滤波过程的观测残差及其统计特征,难以同时获得良好的机动检测概率和快速的机动检测性能。由于雷达目标特征信号与其运动模式之间具有紧密的关系,因而雷达回波中蕴含了丰富的目标运动模式相关信息,从而为利用特征信号进行机动检测提供了可能性。本文结合防空、反导、远程空空等应用背景,以脉冲多普勒雷达系统为主要对象,通过研究雷达目标特征信号,旨在设计低检测延迟的机动检测器以提高检测概率,开展了“特征辅助的目标机动检测技术”研究。
第一章在分析机动检测技术存在的问题后,指出本文的研究思路。首先结合应用背景分析特征辅助的机动检测技术的重要意义;然后对机动检测问题的国内外研究现状进行较为全面的总结和分析;在此基础上指出目前存在的不足和需要进一步研究的方向和内容,最后介绍论文的主要工作和安排。
第二章通过分析机动目标雷达特征信号,建立雷达特征信号与目标运动模式之间的联系,为特征辅助的机动检测技术提供理论依据。首先推导分析不同运动模式下目标姿态角变化率公式,结果表明机动目标跟踪与机动检测领域中重点关注的法向加速机动与非机动模式具有很好的可分性;其次基于多散射中心目标模型,推导姿态敏感雷达特征信号,得到雷达散射截面(Radar Cross Section, RCS)、角闪烁线偏差在不同收发极化方式下矢量形式表达式,给出了目标高分辨多普勒像的数学表示;最后以两理想散射点组成的简单目标为例,分析目标特征信号变化与姿态角变化率之间的关系,得到不同运动模式下雷达特征信号的起伏变化特性,从而建立了雷达特征信号与目标运动模式之间的联系。
第三章应用特征分析的结论,设计了一种新的基于多普勒像的机动检测器,并给出新的性能评估指标。首先介绍了已有的基于RCS和角闪烁特征信号的机动检测算法,并在高数据率应用条件下对算法进行了改进,提出基于累积检验统计量的机动检测器;然后介绍了高分辨多普勒像的性质以及成像处理流程,并基于多普勒像特征信号提出一种新的机动检测方法,通过提取多普勒像分辨率差异特征矢量,将目标机动检测问题视作非机动、机动两类分类识别问题,构造一种基于后向传播神经网络的模式分类机动检测器;随后提出两个新的检测延迟时间评估指标,即延迟常数和收敛时间,相对于平均检测延迟,这两个新的指标体现了对应时刻检测器的检测概率,更全面地反映检测器动态性能;最后通过仿真实验全面评估特征辅助机动检测算法的性能,实验结果表明特征辅助机动检测算法有效降低了机动检测延迟,大大提高了机动检测概率,全面提升了机动检测性能,并且本文提出的基于多普勒像的机动检测算法性能总体上优于其它两种特征辅助的机动检测算法。
第四章为实验验证部分,分别通过外场和仿真实验验证了基于雷达特征信号的运动模式的可分性以及特征辅助的机动检测器的有效性。首先针对外场实验中雷达中频信号采集问题,讨论了相参脉冲雷达中频信号采集系统的设计,重点分析同步触发系统的通用性设计,包括采样率约束条件和脉间相参条件不满足时非均匀采样信号重建问题等,并基于虚拟仪器技术构建了高速大容量采集记录系统,成功应用于本次外场实验的信号采集任务;其次介绍了外场实验系统组成情况,给出了外场实验场景设置,由于受限于多种因素,未能直接验证机动起始和机动终止检测过程,但实验数据处理结果表明,基于RCS和多普勒像特征信号构造的检验统计量可有效区分非机动和机动运动模式,为特征辅助的雷达目标机动检测算法的工程应用进行了有益的探索;最后对特征辅助的机动检测器在机动目标跟踪中的有效性进行了验证,分析了机动检测延迟与状态估计误差之间关系,给出了在一定的误差上限条件下的机动检测延迟上限,为机动检测器设计提供了理论依据,并提出了特征辅助的变结构多模机动目标跟踪算法,仿真实验结果表明所提出的算法性能优于自主多模和交互多模算法,并且计算量更小。
第五章总结了本文的研究工作及所取得的结论和成果,并指出了论文研究中存在的问题和需要进一步研究的方向。
Maneuverdetection belongs to the classic problem of abrupt change detection. It hasattracted considerable attention in activity identification, target tracking and recognition,and other communities, and has a wide range of military and civil applications, e.g., ma-neuvering target tracking and interception, automatic drive, car anti-crash, etc. However,at present, maneuver detection technology mostly depends on measurement residual anditsstatisticsinthefiltering. Itcannotobtainhighdetectionprobabilityandquickdetectionspeed simultaneously. Due to the close relationship between radar signatures and targetmotion mode, rich information of motion modes is embedded in the echoes. This pro-vides the feasibility of maneuver detection using radar signatures. Combining with aerialdefence, antimissile defence, long range air-to-air defence, and other application back-grounds, this thesis employs pulse Doppler radar system as the main object, and aimsto design a maneuver detector with low detection delay and high detection probabilityby studying radar signatures, which is entitled“feature aided target maneuver detectiontechnology”.
Chapter 1 analyzes the existing problems in the maneuver detection, and presentsthe route of our research work. We first analyze the major significance of feature aidedmaneuver detection combing with application backgrounds. The researching progress ofmaneuver detection at home and abroad is summarized and surveyed comprehensively.We then point out current shortcomings and further researching directions and work. Ourwork and organization of the thesis are introduced at last.
Chapter 2 establishes the relationship between radar signatures and target motionmodes by analyzing the signatures of maneuvering targets. It provides theoretical guide-lines for feature aided maneuver detection. Firstly, the formulae of target pose angularrates under different motion modes are derived. The results show that normal acceleratedmaneuvering motion mode and nonmaneuvering motion mode are well classifiable. Theformer has attracted much attention by maneuvering target tracking and maneuver detec-tion. Secondly, the expressions of pose sensitive radar signatures including radar crosssections (RCS) and angular glint errors under different polarizations are obtained in thevector form based on a multiple-scatterer model. Mathematical description of high reso-lution Doppler profile (HRDP) is also given. Finally, taken a simple target consisting of two ideal scatterers as an example, we analyze the relationship between radar signaturesand pose angular rates, and come to the conclusions on the fluctuating characteristics ofthe radar signatures.
Chapter 3 designs a novel maneuver detector based on the HRDP by applying theconclusions of signature analysis, and presents novel indices of performance evaluation.Firstly,existingalgorithmsareintroducedwhicharebasedonRCSandangularglinterror.We then modified the algorithms to accommodate to high data rate applications, and pro-posethenewdetectorsbasedonthecumulativeteststatistics. Secondly,thepropertiesandprofiling scheme of HRDP are introduced. A novel maneuver detection algorithm is pro-posed based on the HRDP. We extract the feature vector of HRDP resolution differences,regard maneuver detection as classification problem where nonmaneuvering and maneu-vering motion modes are two classes to be classified, and develop a maneuver detectorbased on the back propagation neural network. Thirdly, two indices, i.e., delay constantand convergence time, are proposed to evaluate the detection delay performance. Theyreflect the detection probabilities at the corresponding times with respect to the averagedetection delay, and reflect the dynamic performance of the detector more completely.Finally, the performance of feature aided maneuver detection algorithms is fully evaluat-ed by simulation experiments. The results show that the feature aided maneuver detectionalgorithms decrease maneuver detection delay effectively, improve detection probabilitygreatly, and enhance detection performance generally. In addition, the proposed maneu-ver detection algorithm which is based on HRDP outperforms the other two feature aidedalgorithms.
Chapter 4 is a chapter of the experimental validation. The field and simulated exper-iments are carried out to validate the classifiability of motion modes based on radar signa-tures and the effectiveness of feature aided maneuver detectors. Firstly, aiming at radar IFsignal smapling problem in the field experiments, we discuss IF signal sampling systemdesign for coherent pulse radar. The generality design of synchronous trigger system ispresented, which includes constraints on sampling rate, nonuniformly sampled signal re-construction when inter-pulse coherent conditions are not met. A sampling and recordingsystem with high speed and huge capacity is developed based on the virtual instrumen-t technique, and is applied to the signal sampling tasks in the current field experimentsuccessfully. Secondly, the components of the experimental system are introduced, and the experimental scenarios are presented. Maneuver onset and termination detection isnot validated directly due to the limitations of many factors. Fortunately, experimentalresults show that the test statistics based on RCS and HRDP can distinct nonmaneuveringand maneuvering motion modes. It is a valuable exploration for feature aided target ma-neuver detection algorithms in engineering application. Finally, the effectiveness of thefeature aided maneuver detector in the application of maneuvering target tracking is vali-dated. The filtering error dynamics in terms of detection delay are presented and a upperbound for detection delay with given filtering errors is given, which provide theoreticalguidelinesformaneuverdetectordesign. Afeatureaidedvariable-structuremultiplemod-el approach for maneuvering target tracking is proposed. Simulation results show that theproposed algorithm outperforms the autonomous multiple model and interacting multiplemodel algorithms, and provides less computational complexity.
Chapter 5 summarizes the researching work of the thesis, and presents the resultsand conclusions we obtained. The shortcomings and future work are also included.
第一章在分析机动检测技术存在的问题后,指出本文的研究思路。首先结合应用背景分析特征辅助的机动检测技术的重要意义;然后对机动检测问题的国内外研究现状进行较为全面的总结和分析;在此基础上指出目前存在的不足和需要进一步研究的方向和内容,最后介绍论文的主要工作和安排。
第二章通过分析机动目标雷达特征信号,建立雷达特征信号与目标运动模式之间的联系,为特征辅助的机动检测技术提供理论依据。首先推导分析不同运动模式下目标姿态角变化率公式,结果表明机动目标跟踪与机动检测领域中重点关注的法向加速机动与非机动模式具有很好的可分性;其次基于多散射中心目标模型,推导姿态敏感雷达特征信号,得到雷达散射截面(Radar Cross Section, RCS)、角闪烁线偏差在不同收发极化方式下矢量形式表达式,给出了目标高分辨多普勒像的数学表示;最后以两理想散射点组成的简单目标为例,分析目标特征信号变化与姿态角变化率之间的关系,得到不同运动模式下雷达特征信号的起伏变化特性,从而建立了雷达特征信号与目标运动模式之间的联系。
第三章应用特征分析的结论,设计了一种新的基于多普勒像的机动检测器,并给出新的性能评估指标。首先介绍了已有的基于RCS和角闪烁特征信号的机动检测算法,并在高数据率应用条件下对算法进行了改进,提出基于累积检验统计量的机动检测器;然后介绍了高分辨多普勒像的性质以及成像处理流程,并基于多普勒像特征信号提出一种新的机动检测方法,通过提取多普勒像分辨率差异特征矢量,将目标机动检测问题视作非机动、机动两类分类识别问题,构造一种基于后向传播神经网络的模式分类机动检测器;随后提出两个新的检测延迟时间评估指标,即延迟常数和收敛时间,相对于平均检测延迟,这两个新的指标体现了对应时刻检测器的检测概率,更全面地反映检测器动态性能;最后通过仿真实验全面评估特征辅助机动检测算法的性能,实验结果表明特征辅助机动检测算法有效降低了机动检测延迟,大大提高了机动检测概率,全面提升了机动检测性能,并且本文提出的基于多普勒像的机动检测算法性能总体上优于其它两种特征辅助的机动检测算法。
第四章为实验验证部分,分别通过外场和仿真实验验证了基于雷达特征信号的运动模式的可分性以及特征辅助的机动检测器的有效性。首先针对外场实验中雷达中频信号采集问题,讨论了相参脉冲雷达中频信号采集系统的设计,重点分析同步触发系统的通用性设计,包括采样率约束条件和脉间相参条件不满足时非均匀采样信号重建问题等,并基于虚拟仪器技术构建了高速大容量采集记录系统,成功应用于本次外场实验的信号采集任务;其次介绍了外场实验系统组成情况,给出了外场实验场景设置,由于受限于多种因素,未能直接验证机动起始和机动终止检测过程,但实验数据处理结果表明,基于RCS和多普勒像特征信号构造的检验统计量可有效区分非机动和机动运动模式,为特征辅助的雷达目标机动检测算法的工程应用进行了有益的探索;最后对特征辅助的机动检测器在机动目标跟踪中的有效性进行了验证,分析了机动检测延迟与状态估计误差之间关系,给出了在一定的误差上限条件下的机动检测延迟上限,为机动检测器设计提供了理论依据,并提出了特征辅助的变结构多模机动目标跟踪算法,仿真实验结果表明所提出的算法性能优于自主多模和交互多模算法,并且计算量更小。
第五章总结了本文的研究工作及所取得的结论和成果,并指出了论文研究中存在的问题和需要进一步研究的方向。
Maneuverdetection belongs to the classic problem of abrupt change detection. It hasattracted considerable attention in activity identification, target tracking and recognition,and other communities, and has a wide range of military and civil applications, e.g., ma-neuvering target tracking and interception, automatic drive, car anti-crash, etc. However,at present, maneuver detection technology mostly depends on measurement residual anditsstatisticsinthefiltering. Itcannotobtainhighdetectionprobabilityandquickdetectionspeed simultaneously. Due to the close relationship between radar signatures and targetmotion mode, rich information of motion modes is embedded in the echoes. This pro-vides the feasibility of maneuver detection using radar signatures. Combining with aerialdefence, antimissile defence, long range air-to-air defence, and other application back-grounds, this thesis employs pulse Doppler radar system as the main object, and aimsto design a maneuver detector with low detection delay and high detection probabilityby studying radar signatures, which is entitled“feature aided target maneuver detectiontechnology”.
Chapter 1 analyzes the existing problems in the maneuver detection, and presentsthe route of our research work. We first analyze the major significance of feature aidedmaneuver detection combing with application backgrounds. The researching progress ofmaneuver detection at home and abroad is summarized and surveyed comprehensively.We then point out current shortcomings and further researching directions and work. Ourwork and organization of the thesis are introduced at last.
Chapter 2 establishes the relationship between radar signatures and target motionmodes by analyzing the signatures of maneuvering targets. It provides theoretical guide-lines for feature aided maneuver detection. Firstly, the formulae of target pose angularrates under different motion modes are derived. The results show that normal acceleratedmaneuvering motion mode and nonmaneuvering motion mode are well classifiable. Theformer has attracted much attention by maneuvering target tracking and maneuver detec-tion. Secondly, the expressions of pose sensitive radar signatures including radar crosssections (RCS) and angular glint errors under different polarizations are obtained in thevector form based on a multiple-scatterer model. Mathematical description of high reso-lution Doppler profile (HRDP) is also given. Finally, taken a simple target consisting of two ideal scatterers as an example, we analyze the relationship between radar signaturesand pose angular rates, and come to the conclusions on the fluctuating characteristics ofthe radar signatures.
Chapter 3 designs a novel maneuver detector based on the HRDP by applying theconclusions of signature analysis, and presents novel indices of performance evaluation.Firstly,existingalgorithmsareintroducedwhicharebasedonRCSandangularglinterror.We then modified the algorithms to accommodate to high data rate applications, and pro-posethenewdetectorsbasedonthecumulativeteststatistics. Secondly,thepropertiesandprofiling scheme of HRDP are introduced. A novel maneuver detection algorithm is pro-posed based on the HRDP. We extract the feature vector of HRDP resolution differences,regard maneuver detection as classification problem where nonmaneuvering and maneu-vering motion modes are two classes to be classified, and develop a maneuver detectorbased on the back propagation neural network. Thirdly, two indices, i.e., delay constantand convergence time, are proposed to evaluate the detection delay performance. Theyreflect the detection probabilities at the corresponding times with respect to the averagedetection delay, and reflect the dynamic performance of the detector more completely.Finally, the performance of feature aided maneuver detection algorithms is fully evaluat-ed by simulation experiments. The results show that the feature aided maneuver detectionalgorithms decrease maneuver detection delay effectively, improve detection probabilitygreatly, and enhance detection performance generally. In addition, the proposed maneu-ver detection algorithm which is based on HRDP outperforms the other two feature aidedalgorithms.
Chapter 4 is a chapter of the experimental validation. The field and simulated exper-iments are carried out to validate the classifiability of motion modes based on radar signa-tures and the effectiveness of feature aided maneuver detectors. Firstly, aiming at radar IFsignal smapling problem in the field experiments, we discuss IF signal sampling systemdesign for coherent pulse radar. The generality design of synchronous trigger system ispresented, which includes constraints on sampling rate, nonuniformly sampled signal re-construction when inter-pulse coherent conditions are not met. A sampling and recordingsystem with high speed and huge capacity is developed based on the virtual instrumen-t technique, and is applied to the signal sampling tasks in the current field experimentsuccessfully. Secondly, the components of the experimental system are introduced, and the experimental scenarios are presented. Maneuver onset and termination detection isnot validated directly due to the limitations of many factors. Fortunately, experimentalresults show that the test statistics based on RCS and HRDP can distinct nonmaneuveringand maneuvering motion modes. It is a valuable exploration for feature aided target ma-neuver detection algorithms in engineering application. Finally, the effectiveness of thefeature aided maneuver detector in the application of maneuvering target tracking is vali-dated. The filtering error dynamics in terms of detection delay are presented and a upperbound for detection delay with given filtering errors is given, which provide theoreticalguidelinesformaneuverdetectordesign. Afeatureaidedvariable-structuremultiplemod-el approach for maneuvering target tracking is proposed. Simulation results show that theproposed algorithm outperforms the autonomous multiple model and interacting multiplemodel algorithms, and provides less computational complexity.
Chapter 5 summarizes the researching work of the thesis, and presents the resultsand conclusions we obtained. The shortcomings and future work are also included.
引文
[1]全军深入学习实践科学发展观活动领导小组.国防和军队建设贯彻落实科学发展观重要论述选编[M].北京:解放军出版社,2008.
[2]范金荣.精确制导武器信息化关键技术分析[J].现代防御技术.2003,31 (4):27–30.
[3]王雅梅.立体化发展我军信息化装备[J].装备指挥技术学院学报.2007,18 (5):19–22.
[4]王维平,朱自力,杨斌.现代作战理论研究[M].长沙:国防科技大学出版社,2001.
[5]梁薇,张科.精确制导武器发展及其关键技术[J].火力与指挥控制.2008,33 (12):5–7, 12.
[6]冯翠菊.现代武器智慧的眼睛——精确制导技术[J].现代物理知识.2008,20 (1):41–44.
[7]付强,何峻,程肖,等.精确制导武器技术应用向导[M].北京:国防工业出版社,2010.
[8]杨树谦.精确制导武器和技术[J].红外与激光工程.1999,28 (6):1–3,9.
[9]刘峥,张守宏.步进频率雷达在精确制导武器中的应用[J].制导与引信.2002,23 (3):9–13.
[10]黄立新,赵显超.精确制导武器的关键技术[J].无线电工程.2006,36 (12):7–9, 20.
[11]陈定昌,袁起,范金荣.精确制导武器发展趋向[J].现代防御技术.2000,28 (4):41–47, 57.
[12]殷兴良.精确制导技术的发展[J].电子学报.1995,23 (10):100–104.
[13]郭修煌.精确制导技术[M].北京:国防工业出版社,1999.
[14]刘隆和.多模复合寻的制导技术[M].北京:国防工业出版社,2001.
[15]杨树谦.精确制导技术发展现状与展望[J].航天控制.2004,22 (4):17–20.
[16]魏伟波,芮筱亭.精确制导技术研究[J].火力与指挥控制.2006,31 (2):5–8, 11.
[17]黄培康,袁起,朱振福,等.光学精确制导技术的发展现状与展望[J].红外与激光工程.2007,36 (S):1–6.
[18]顾振杰,刘宇.反舰导弹精确制导技术发展趋势分析[J].制导与引信.2010,31 (3):23–26, 48.
[19]魏伟波,芮筱亭.毫米波精确制导技术[J].火力与指挥控制.2005,30 (S):4–6, 10.
[20]姚秀娟,彭晓乐,张永科.几种精确制导技术简述[J].激光与红外.2006,36 (5):338–340.
[21]苏宏艳,朱淮城.毫米波精确制导技术及其发展趋势[J].制导与引信.2008,29 (2):6–9, 14.
[22]刘逸平.国外毫米波精确制导技术的发展趋势[J].火控雷达技术.2008,37 (3):1–6.
[23] Li X R, Jilkov V P. A Survey of Maneuvering Target Tracking– Part I: DynamicModels [C]. In Proceedings of SPIE Conference on Signal and Data Processing ofSmall Targets. Orlando, FL, USA, April 2000: 212–235.
[24] Li X R, Jilkov V P. A Survey of Maneuvering Target Tracking– Part II: Ballis-tic Targets Models [C]. In Proceedings of SPIE Conference on Signal and DataProcessing of Small Targets. San Diego, CA, USA, July– August 2001: 559–581.
[25] Li X R, Jilkov V P. A Survey of Maneuvering Target Tracking– Part III: Measure-ment Models [C]. In Proceedings of SPIE Conference on Signal and Data Process-ing of Small Targets. San Diego, CA, USA, July– August 2001: 423–446.
[26] Li X R, Jilkov V P. A Survey of Maneuvering Target Tracking– Part IV: Decision-Based Methods [C]. In Proceedings of the SPIE Conference on Signal and DataProcessing of Small Targets. Orlando, FL, USA, April 2002: 511–534.
[27] Li X R, Jilkov V P. Overview of Multiple-Model Methods for Maneuvering TargetTracking [C]. In Proceedings of SPIE Conference on Signal and Data Processingof Small Targets. San Diego, CA, USA, August 2003: 200–210.
[28] Li X R, Jilkov V P. A Survey of Maneuvering Target Tracking: ApproximationTechniques for Nonlinear Filtering [C]. In Proceedings of SPIE Conference onSignal and Data Processing of Small Targets. Orlando, FL, USA, April 2004:537–550.
[29] Li X R, Jilkov V P. A Survey of Maneuvering TargetTracking– Part VIa: Density-BasedExactNonlinearFiltering[C].InProceedingsofSPIEConferenceonSignaland Data Processing of Small Targets. Orlando, FL, USA, April 2010: 76981D-1–76981D-12.
[30] Li X R, Jilkov V P. A Survey of Maneuvering Target Tracking– Part VIb: Ap-proximate Nonlinear Density Filtering in Mixed Time [C]. In Proceedings of SPIEConference on Signal and Data Processing of Small Targets. Orlando, FL, USA,April 2010: 76981E-1–76981E-12.
[31] LiXR,JilkovVP.SurveyofManeuveringTargetTracking.PartI:DynamicMod-els [J]. IEEE Transactions on Aerospace and Electronic Systems. 2003, 39 (4):1333–1363.
[32] Li X R, Jilkov V P. Survey of Maneuvering Target Tracking. Part II: Motion Mod-els of Ballistic and Space Targets [J]. IEEE Transactions on Aerospace and Elec-tronic Systems. 2010, 46 (1): 96–119.
[33] Li X R, Jilkov V P. Survey of Maneuvering Target Tracking. Part V: Multiple-Model Methods [J]. IEEE Transactions on Aerospace and Electronic Systems.2005, 41 (4): 1255–1321.
[34]周宏仁,敬忠良,王培德.机动目标跟踪[M].北京:国防工业出版社,1991.
[35]王德纯,丁家会,程望东.精密跟踪测量雷达技术[M].北京:电子工业出版社,2006.
[36]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.
[37]权太范.目标跟踪新理论与技术[M].北京:国防工业出版社,2009.
[38] Sworder D D, Kent M, Vojak R, et al. Renewal Maneuvering Targets [J]. IEEETransactions on Aerospace and Electronic Systems. 1995, 31 (1): 138–149.
[39] Cui N, Hong L, Layne J R. A Comparison of Nonlinear Filtering Approaches withan Application to Ground Target Tracking [J]. Signal Processing. 2005, 85 (8):1469– 1492.
[40] Qu H, Pang L, Li S. A Novel Interacting Multiple Model Algorithm [J]. SignalProcessing. 2009, 89 (11): 2171–2177.
[41] Bizup D F. Improving Radar Target Tracking with the Range Rate Measuremen-t [D]. Virginia: University of Virginia, 2003.
[42] BizupDF,BrownDE.ManeuverDetectionUsingtheRadarRangeRateMeasure-ment [J]. IEEE Transactions on Aerospace and Electronic Systems. 2004, 40 (1):330–336.
[43] Ru J, Chen H, Li X R, et al. A Range Rate Based Detection Technique for Track-ing a Maneuvering Target [C]. In Proceedings of SPIE Conference on Signal andData Processing of Small Targets. San Diego, CA, USA, August 2005: 59131Q-1–59131Q-13.
[44] Zhai M, Fu S. Applying Target Maneuver Onset Detection Algorithms to DefectsDetection in Aluminum Foil [J]. Signal Processing. 2010, 90 (7): 2319– 2326.
[45]范红旗,王胜,付强.目标机动检测算法综述[J].系统工程与电子技术.2009,31 (5):1064–1070.
[46]范红旗.主动寻的制导中机动目标运动模式辨识技术[D].长沙:国防科学技术大学,2008.
[47] Turetsky V, Shinar J. Missile Guidance Laws Based on Pursuit-Evasion GameFormulations [J]. Automatica. 2003, 39 (4): 607–618.
[48] Fan H, Zhu Y, Fu Q. Impact of Mode Decision Delay on Estimation Error for Ma-neuvering Target Interception [J]. IEEE Transactions on Aerospace and ElectronicSystems. 2011, 47 (1): 702–711.
[49]黄培康,林桂森,樊正芳,等.雷达目标特征信号[M].北京:宇航出版社,1993.
[50]黄培康,殷红成,许小剑.雷达目标特性[M].北京:电子工业出版社,2005.
[51]郭桂蓉,庄钊文,陈曾平.电磁特征抽取与目标识别[M].长沙:国防科技大学出版社,1996.
[52]杜兰.雷达高分辨距离像目标识别方法研究[D].西安:西安电子科技大学,2007.
[53] Ru J, Jilkov V P, Li X R, et al. Sequential Detection of Target Maneuvers [C]. InProceedings of the 8th International Conference on Information Fusion. Philadel-phia, PA, USA, July 2005: 345–351.
[54] Ru J, Bashi A, Li X R. Performance Comparison of Target Maneuver Onset De-tectionAlgorithms[C].InProceedingsoftheSPIEConferenceonSignalandDataProcessing of Small Targets. Orlando, FL, USA, April 2004: 419–428.
[55] Basseville M, Nikiforov I. Detection of Abrupt Changes: Theory and Applica-tion [M]. Englewood Cliffs: Prentice Hall, 1993.
[56] Page E S. A Test for a Change in a Parameter Occurring at an Unknown Point [J].Biometrika. 1955, 42 (4): 523–527.
[57] Gustafsson F. The Marginalized Likelihood Test Ratio for Detecting Abrup-t Changes [J]. IEEE Transactions on Automatic Control. 1996, 41 (1): 66–78.
[58] Malldi D P, Speyer J L. A Generalized Shiryaev Sequential Probability Ratio Testfor Change Detection and Isolation [J]. IEEE Transactions on Automatic Control.1999, 44 (8): 1522–1534.
[59] Nikiforov I V. On a Class of Quadratic Tests for Detection of Abrupt Changes inSignals and Systems [C]. In Proceedings of the 1998 American Control Confer-ence. Philadelphia, PA, USA, June 1998: 751–755.
[60] Moustakides G V. Quickest Detection of Abrupt Changes for a Class of RandomProcesses[J].IEEETransactionsonInformationTheory.1998,44(5):1965–1968.
[61] Tze L L, Jerry Z S. Efficient Recursive Algorithms for Detection of Abrup-t Changes in Signals and Control Systems [J]. IEEE Transactions on AutomaticControl. 1999, 44 (5): 952–966.
[62] ChoJ,NtoulasA.EffectiveChangeDetectionUsingSampling[C].InProceedingsofthe28thInternationalConferenceonVeryLargeDataBases.HongKong,China,August 2002.
[63] Chan Y T, Hu A G C, Plant J B. A Kalman Filter Based Tracking Scheme withInput Estimation [J]. IEEE Transactions on Aerospace and Electronic Systems.1979, 15 (2): 237–244.
[64] Bogler P L. Tracking a Maneuvering Target Using Input Estimation [J]. IEEETransactions on Aerospace and Electronic Systems. 1987, 23 (3): 298–310.
[65] Lee H, Tahk M J. Generalized Input-Estimation Technique for Tracking Maneu-veringTargets[J].IEEETransactionsonAerospaceandElectronicSystems.1999,35 (4): 1388–1402.
[66] Chan Y T, Couture F. Maneuver Detection and Track Correction by Input Estima-tion [J]. IEE Proceedings F: Radar and Signal Processing. 1993, 140 (1): 21–28.
[67] Bar-Shalom Y, Birmiwal K. Variable Dimension Filter for Maneuvering TargetTracking [J]. IEEE Transactions on Aerospace and Electronic Systems. 1982,18 (5): 621–629.
[68] Bar-Shalom Y, Fortmann T E. Tracking and Data Association [M]. New York:Academic Press, 1988.
[69] YangWC,ChangFR,TsaiYH,etal.EarlyDetectionofTargetManoeuvresundera Specific False Alarm Rate [J]. IEE Proceedings - Radar, Sonar and Navigation.2003, 150 (5): 350–355.
[70] Bekir E. Adaptive Kalman Filter for Tracking Maneuvering Targets [J]. AIAAJournal of Guidance. 1983, 6 (5): 414–416.
[71] Lee S C, Liu C Y. Trajectory Estimation of Reentry Vehicle by Use of on-LineInput Estimation [J]. AIAA Journal of Guidance, Control and Dynamics. 1999,22 (6): 808–815.
[72] Kay S M.统计信号处理基础——估计与检测理论[M].罗鹏飞,张文明,刘忠,等,译.北京:电子工业出版社,2006.
[73] Willsky A S, Jones H L. A Generalized Likelihood Ratio Approach to State Esti-mation in Linear System Subject to Abrupt Changes [C]. In Proceedings of IEEEConference on Decision and Control including the 13th Symposium on AdaptiveProcesses. Phoenix, AZ, USA, November 1974: 846–853.
[74] Willsky A S, Jones H L. A Generalized Likelihood Ratio Approach to the Detec-tion and Estimation of Jumps in Linear Systems [J]. IEEE Transactions on Auto-matic Control. 1976, 21 (1): 108–112.
[75] Korn J, Gully S W, Willsky A S. Application of the Generalized Likelihood RatioAlgorithm to Maneuver Detection and Estimation [C]. In Proceedings of the 1982American Control Conference. Arlington, VA, USA, June 1982: 792–798.
[76] Schnepper K. A Comparison of GLR and Multiple Model Filters for a TargetTracking Problem [C]. In Proceedings of the 25th Conference on Decision andControl. Athens, Greece, December 1986: 666–670.
[77] Farooq M, Bruder S. Information Type Filters for Tracking a Maneuvering Tar-get [J]. IEEE Transactions on Aerospace and Electronic Systems. 1990, 26 (3):441–454.
[78] Ru J, Li X R, Jilkov V P. Multiple-Model Detection of Target Maneuvers [C]. InProceedings of SPIE Conference on Signal and Data Processing of Small Targets.San Diego, CA, USA, August 2005: 100–108.
[79] Wang T C, Varshney P K. A Tracking Algorithm for Maneuvering Targets [J].IEEE Transactions on Aerospace and Electronic Systems. 1993, 29 (3): 910–925.
[80] Whang I H, Sung T K, Lee J G. A Modified Target Maneuver Estimation Tech-nique Using Pseudo-Acceleration Information [C]. In Proceedings of the 1992 A-IAA Guidance Navigation and Control Conference. Hilton Head, SC, USA, Au-gust 1992: 1249–1254.
[81] Whang I H, Lee J G, Sung T K. Modified Input Estimation Technique Using Pseu-doresiduals [J]. IEEE Transactions on Aerospace and Electronic Systems. 1994,30 (1): 220–228.
[82] Smith M A. On Doppler Measurements for Tracking [C]. In Proceedings of Inter-national Conference on Radar. Adelaide, Australia, September 2008: 513–518.
[83] Petsios M N, Alivizatos E G, Uzunoglu N K. Manoeuvring Target Tracking us-ingMultipleBistaticRangeandRange-RateMeasurements[J].SignalProcessing.2007, 87 (4): 665–686.
[84]李小毛,刘兆磊,汪圣利.基于多个多普勒雷达的加速度和速度估计[J].现代雷达.2011,33 (1):47–50.
[85] Yuan X, Duan Z, Han C. A Maneuver Detection Method Using Multiple DopplerRadars [C]. In Proceedings of 40th Southeastern Symposium on System Theory.New Orleans, LA, USA, March 2008: 298–302.
[86] Yuan X, Han C, Duan Z, et al. Adaptive Turn Rate Estimation using Range RateMeasurements[J].IEEETransactionsonAerospaceandElectronicSystems.2006,42 (4): 1532–1540.
[87] Lei M, Han C, Cai K. Unified Maneuvering Model for Target Tracking by Us-ing Range-Rate Measurement [J]. Chinese Journal of Electronics. 2008, 17 (3):551–557.
[88] Veeraraghavan S, Rathi A, Sagayaraj M J. Turn Rate Estimation Techniques inIMM Estimators for ESA Radar Tracking [C]. In Proceedings of IEEE AerospaceConference. Big Sky, MT, USA, March 2008: 2053–2060.
[89]刘建成.加速运动目标检测及跟踪技术研究[D].长沙:国防科学技术大学,2007.
[90]李文臣.高速机动目标雷达信号参数估计与成像处理[D].长沙:国防科学技术大学,2009.
[91]邹虹.多分量线性调频信号的时频分析[D].西安:西安电子科技大学,2000.
[92] Wood J C, Barry D T. Linear Signal Synthesis Using the Radon-Wigner Transfor-m [J]. IEEE Transactions on Signal Processing. 1994, 42 (8): 2105–2111.
[93]刘建成,王雪松,肖顺平,等.基于Wigner-Hough变换的径向加速度估计[J].电子学报.2005,33 (12):2235–2238.
[94] Wang M, Chan A K, Chui C K. Linear Frequency Modulated Signal DetectionUsing Radon-Ambiguity Transform [J]. IEEE Transactions on Signal Processing.1998, 46 (3): 571–586.
[95]杜文超,王国宏,高学强.低信噪比条件下在短时信号中提取目标径向加速度方法研究[J].中国科学E辑:技术科学.2007,37 (7):923–943.
[96] Ru J, Jilkov V P, Li X R, et al. Detection of Target Maneuver Onset [J]. IEEETransactions on Aerospace and Electronic Systems. 2009, 45 (2): 536–554.
[97]赵军,单甘霖,吉兵,等.飞机姿态角辅助的交互式多模型跟踪算法[J].电光与控制.2011,18 (3):43–47, 51.
[98] Kendrick J D, Maybeck P S, Reid J G. Estimation of Aircraft Target Motion UsingOrientation Measurements [J]. IEEE Transactions on Aerospace and ElectronicSystems. 1981, AES-17 (2): 254–260.
[99] Hughes E J, Leyland M. Target Manoeuvre Detection Using Radar Glint [J]. Elec-tronics Letters. 1998, 34 (17): 1695–1696.
[100] Hughes E J. Radar Cross Section Modeling Using Genetic Algorithms [D].Shrivenham: Cranfield University, 1998.
[101] Yang C, Garber W, Mitchell R, et al. A Simple Maneuver Indicator From Target’sRange-Doppler Image [C]. In Proceedings of 10th International Conference onInformation Fusion. Quebec, Canada, July 2007: 9–16.
[102] Yang C, Blasch E. Estimating Target Range-Doppler Image Slope for ManeuverIndication [C]. In Proceedings of SPIE Conference on Signal Processing, SensorFusion, and Target Recognition XVII. Orlando, FL, USA, March 2008: 696808-1–696808-12.
[103]王国宏,毛士艺,何友.红外传感器目标跟踪算法[J].火力与指挥控制.2001,26 (2):5–9.
[104]何兵,毛士艺,张有为,等.利用近距离目标红外图像的机动检测问题研究[J].电子学报.2001,29 (3):332–336.
[105] SworderDD,HutchinsRG.ManeuverEstimationUsingMeasurementsofOrien-tation [J]. IEEE Transactions on Aerospace and Electronic Systems. 1990, 26 (4):625–638.
[106] Hutchins R G, Sworder D D. Image Fusion Algorithms for Tracking Maneuver-ing Targets [J]. AIAA Journal of Guidance, Control and Dynamics. 1992, 15 (1):175–184.
[107] Sworder D D, Hutchins R G. Improved Tracking of an Agile Target [J]. AIAAJournal of Guidance, Control and Dynamics. 1992, 15 (5): 1281–1284.
[108] Laneuville D, Mariton M. Image Based Target Maneuver Detection [C]. In Pro-ceedings of the 30th IEEE Conference on Decision and Control. Brighton, UK,December 1991: 2066–2067.
[109] Laneuville D, Dufour E, Bertrand P. Image Based Maneuvering Target Track-ing [C]. In Proceedings of the American Control Conference. Philadelphia, PA,USA, June 1998: 2444–2449.
[110] Shetty S, Alouani A T. Image Sensor Based Target Maneuver Detection [C]. InProceedings of SPIE Conference on Acquisition, Tracking, and Pointing VII. Or-lando, FL, USA, April 1993: 161–170.
[111] Shetty S, Alouani A T. Image-Sensor-Based Target Maneuver Detection [J]. Op-tical Engineering. 1993, 32 (11): 2735–2740.
[112] Shetty S, Alouani A T. A Multisensor Tracking System With an Image-Based Ma-neuvering Detector [C]. In Proceedings of the American Control Conference. Bal-timore, MD, USA, June 1994: 3288–3292.
[113] ShettyS, AlouaniAT.Performanceof an Image-BasedManeuverDetector[C].InProceedings of the 33rd Conference on Decision and Control. Lake Buena Vista,FL, USA, December 1994: 3259–3264.
[114] Shetty S, Alouani A T. A Multisensor Tracking System With an Image-Based Ma-neuvering Detector [J]. IEEE Transactions on Aerospace and Electronic Systems.1996, 32 (1): 167–181.
[115]何友,王国宏,陆大金,等.多传感器信息融合及应用[M].第二版.北京:电子工业出版社,2007.
[116]保铮,刑孟道,王彤.雷达成像技术[M].北京:电子工业出版社,2005.
[117] Song T L, Lee D G. Effective Filtering of Target Glint [J]. IEEE Transactions onAerospace and Electronic Systems. 2001, 36 (1): 234–241.
[118] Blasch E, Yang C. Ten Methods to Fuse GMTI and HRRR Measurements for JointTracking Identification [C]. In Proceedings of the 7th International Conference onInformation Fusion. Stockholm, Sweden, June– July 2004: 1006–1013.
[119] Singer P F, Coursey A L. Feature Aided Tracking (FAT) [C]. In Proceedings of theSPIE Conference on Signal and Data Processing of Small Targets. Orlando, FL,USA, 2004: 249–259.
[120] Oshman Y, David A. Differential-Game-Based Guidance Law using Target Orien-tation Observations [J]. IEEE Transactions on Aerospace and Electronic Systems.2006, 42 (1): 316–326.
[121] Tsang L, Kong J A, Ding K-H, et al. Scattering of Electromagnetic Waves: Nu-merical Simulations [M]. New York: John Wiley and Sons, 2001.
[122] Tsang L, Kong J A. Scattering of Electromagnetic Waves: Advanced Topics [M].New York: John Wiley and Sons, 2001.
[123] MusickSH,SherwoodJU,PiattTL,etal.ASimulationSystemforFeature-AidedTrackingResearch[C].InProceedingsofSPIEConferenceonAlgorithmsforSyn-thetic Aperture Radar Imagery XI. Orlando, FL, USA, April 2004: 309–320.
[124] Piatt T L, Sherwood J U, Musick S H. Radar Signature Generation for Feature-Aided Tracking Research [C]. In Proceedings of SPIE Conference on Algorithmsfor Synthetic Aperture Radar Imagery XII. Orlando, FL, USA, March–April 2005:419–427.
[125]肖业伦.航空航天器运动的建模——飞行动力学的理论基础[M].北京:北京航空航天大学出版社,2003.
[126]曹义华.直升机飞行力学[M].北京:北京航空航天大学出版社,2005.
[127] Adler F P. Missile Guidance by Three-Dimensional Proportional Navigation [J].Journal of Applied Physics. 1956, 27 (5): 500–507.
[128] Berndt J S. JSBSim Reference Manual, August, 2009.
[129] http://www.jsbsim.org. 2011.
[130] HarringtonRF.Time-HarmonicElectromagneticFields[M].NewYork:McGraw-Hill, 1968.
[131] BowmanJJ.ElectromagneticandAcousticScatteringbySimpleShapes[M].Am-sterdam: North-Holland Publishing, 1969.
[132] Kline M, Kay I W. Electromagnetic Theory and Geometrical Optics [M]. NewYork: John Wiley and Sons, 1965.
[133] Ruck G T. Radar Cross Section Handbook [M]. New York: Plenum Press, 1970.
[134] Crispin J W. Method of Radar Section Analysis [M]. New York: Academic Press,1968.
[135] Knott E F. Radar Cross Section [M]. Dedham: Artech House, 1985.
[136] BhattacharyyaAK,SenguptaDL.RadarCrossSectionAnalysisandControl[M].Norwood: Artech House, 1991.
[137] Wang J J H. Generalized Moment Methods in Electromagnetics [M]. New York:John Wiley and Sons, 1991.
[138] Fritch P C. Special Issue on Radar Reflectivity [J]. Proceedings of the IEEE. 1965,53 (8): 769–1166.
[139] Stone W R. Special Issue on Radar Cross Sections of Complex Objects [J]. Pro-ceedings of the IEEE. 1989, 77 (5): 639–823.
[140] Skolnik M I. Radar Handbook [M]. 3rd ed. New York: McGraw-Hill, 2008.
[141] Marcum J I. A Statistical Theory of Target Detection by Pulsed Radar [J]. IRETransactions on Information Theory. 1960, 6 (2): 59–267.
[142] Swerling P. Probability of Detection for Fluctuating Tragets [J]. IRE Transactionson Information Theory. 1960, 6 (2): 269–308.
[143] Weinstock W. Target Cross Section Models for Radar System Analysis [D]. Penn-sylvania: University of Pennsylvania, 1964.
[144] Meyer D P, Mayer H A. Radar Target Detection– Handbook of Theory and Prac-tice [M]. San Diego: Academic Press, 1973.
[145] Scholefield P H R. Statistical Aspects of Ideal Radar Targets [J]. Proceedings ofthe IEEE. 1967, 55 (4): 587–589.
[146] HeidbrederGR,MitchellRL.DetectionProbabilitiesforLog-NormallyDistribut-ed Signals [J]. IEEE Transactions on Aerospace and Electronic Systems. 1967,3 (1): 5–13.
[147]黄培康.飞行器隐身技术评述[J].系统工程与电子技术.1984,6 (1):1–8.
[148]尹光俊,廖绍彬.单层与多层吸波材料设计[J].北京大学学报(自然科学版).1990,26 (3):327–327.
[149] HowardD D. Radar TargetGlint in Trackingand GuidanceSystem Based on EchoSignal Phase Distortion [C]. In Procedings of NEC. 1959: 840–849.
[150] Lindsay J E. Anglar Glint and the Moving, Rotating, Complex Radar Target [J].IEEE Transactions on Aerospace and Electronic Systems. 1968, AES-4 (2):164–173.
[151] DunnJH,HowardDD.RadarTargetAmplitude,Angle,andDopplerScintillationfrom Analysis of the Echo Signal Propagating in Space [J]. IEEE Transactions onMicrowave Theory and Techniques. 1968, 16 (9): 715–728.
[152]黄培康,殷红成.扩展目标的角闪烁[J].系统工程与电子技术.1990,12 (12):1–17.
[153] YinHC,HuangPK.UnificationandComparisonBetweenTwoConceptsofRadarTargetAngularGlint[J].IEEETransactionsonAerospaceandElectronicSystems.1995, 31 (2): 778–783.
[154] Yin H C, Huang P K. Further Comparison Between Two Concepts of Radar TargetAngular Glint [J]. IEEE Transactions on Aerospace and Electronic Systems. 2008,44 (1): 372–380.
[155] OstrovityanovRV,BasalovFA.StatisticalTheoryofExtendedRadarTargets[M].Norwood: Artech House, 1985.
[156]陈国瑛.雷达目标角闪烁的建模与抑制研究[D].北京:航天工业总公司第二研究院,1998.
[157] Sims R J, Graf E R. The Reduction of Radar Glint by Diversity Techniques [J].IEEE Transactions on Antennas and Propagation. 1971, AP-19 (4): 462–468.
[158] Berizzi F, Corsini G. Autofocusing of Inverse Synthetic Aperture Radar Imagesusing Contrast Optimization [J]. IEEE Transactions on Aerospace and ElectronicSystems. 1996, 32 (3): 1185–1191.
[159]邢孟道,保铮.低分辨雷达的一维横向成像及提高分辨率的方法[J].西安电子科技大学学报(自然科学版).2000,27 (6):700–704.
[160]夏桂芬,朱淮城,李天池,等.毫米波雷达导引头频域仿形技术研究[J].系统工程与电子技术.2008,30 (9):1649–1652.
[161]高烽,王树文.单脉冲雷达导引头仿形技术[J].制导与引信.2003,24(2):1–5.
[162]姜正林,保铮,邢孟道.低分辨雷达编队目标分辨新方法[J].西安电子科技大学学报(自然科学版).2001,28 (4):482–486.
[163] Chen V C, Ling H. Time-Frequency Transforms for Radar Imaging and SignalAnalysis [M]. Norwood: Artech House, 2002.
[164] Keller J B. Geometrical Theory of Diffraction [J]. Journal of the Optical Societyof America. 1962, 52 (2): 116–130.
[165] Potter L C, Chiang D-M, Carriere R, et al. A GTD Based Parametric Modelfor Radar Scattering [J]. IEEE Transactions on Antennas and Propagation. 1995,43 (10): 1058–1067.
[166] BhallaR,LingH,MooreR,etal.3DScatteringCenterRepresentationofComplexTargets Using the Shooting and Bouncing Ray Technique: A Review [J]. IEEEAntennas and Propagation Magazine. 1998, 40 (5): 30–39.
[167]范红旗,王胜,祝依龙,等.相位梯度法计算近场角闪烁的解析式[J].电子学报.2009,37 (5):937–941.
[168]周剑雄.光学区雷达目标三维散射中心重构理论与技术[D].长沙:国防科学技术大学,2006.
[169] Zhou J, Zhao H, Shi Z, et al. Global Scattering Center Model Extraction of RadarTargets Based on Wideband Measurements [J]. IEEE Transactions on Antennasand Propagation. 2008, 56 (7): 2051–2060.
[170]丁鹭飞,耿富录.雷达原理[M].第三版.西安:西安电子科技大学出版社,2002.
[171]皇甫堪,陈建文,楼生强.现代数字信号处理[M].北京:电子工业出版社,2004.
[172] Boers Y, Driessen J N. Multitarget Particle Filter Track Before Detect Applica-tion [J]. IEE Proceedings - Radar, Sonar and Navigation. 2004, 151 (6): 351–357.
[173] Boers Y, Driessen H, Torstensson J, et al. Track-Before-Detect Algorithm forTracking Extended Targets [J]. IEE Proceedings - Radar, Sonar and Navigation.2006, 153 (4): 345–351.
[174] Kurien T. Framework for Integrated Tracking and Identification of Multiple Tar-gets [C]. In Proceedings of IEEE/AIAA 10th Digital Avionics Systems Confer-ence. Los Angels, CA, USA, October 1991: 362–366.
[175] Yang C, Blasch E. Mutual-Aided Target Tracking and Identification [C]. In Pro-ceedings of SPIE Conference on Multisensor, Multisource Information Fusion:Architectures, Algorithms, and Applications. Orlando, FL, USA, April 2003:152–163.
[176] Minvielle P, Marrs A D, Maskell S, et al. Joint Target Tracking and Identification- Part I: Sequential Monte Carlo Model-Based Approaches [C]. In Proceedings ofthe 8th International Conference on Information Fusion. Philadephia, PA, USA,July 2005: 256–266.
[177] Minvielle P, Marrs A D, Maskell S, et al. Joint Target Tracking and Identifica-tion - Part II: Shape Video Computing [C]. In Proceedings of the 8th InternationalConference on Information Fusion. Philadephia, PA, USA, July 2005: 267–274.
[178] Drummond O E. On Categorical Feature-Aided Target Tracking [C]. In Proceed-ings of the SPIE Conference on Signal and Data Processing of Small Targets. SanDiego, CA, USA, August 2003: 544–558.
[179] Chenouard N, Blochb I, Olivo-Marin J-C. Feature-Aided Particle Tracking [C].In Proceedings of 15th IEEE International Conference on Image Processing. SanDiego, CA, USA, October 2008: 1796–1799.
[180] Oshman Y, Arad D. Enhanced Air-to-Air Missile Tracking Using Target Orienta-tion Observations [J]. AIAA Journal of Guidance, Control and Dynamics. 2004,27 (4): 595–606.
[181] Daubechies I.小波十讲[M].李建平,杨万年,译.北京:国防工业出版社,2004.
[182]成礼智,王红霞,罗永.小波的理论与应用[M].北京:科学出版社,2004.
[183]郭桂蓉,谢维信,庄钊文,等.模糊模式识别[M].长沙:国防科技大学出版社,1992.
[184]徐扬,秦克云,刘军,等.模糊模式识别及其应用[M].成都:西南交通大学出版社,1999.
[185] Li J, Stoica P. Efficient Mixed-Spectrum Estimation with Applications to Tar-get Feature Extraction [J]. IEEE Transactions on Signal Processing. 1996, 42 (2):281–295.
[186] Li J, Zheng D, Stoica P. Angle and Waveform Estimation Via RELAX [J]. IEEETransactions on Aerospace and Electronic Systems. 1997, 33 (3): 1077–1087.
[187] Maranda B H. On the False Alarm Probability for an Overlapped FFT Proces-sor [J]. IEEE Transactions on Aerospace and Electronic Systems. 1996, 32 (4):1452–1456.
[188] Fan H, Wang S, Chen F, et al. Frame-overlapped Zoom-FFT Optimization in PDRadar Application [C]. In Proceedings of 2006 CIE International Conference onRadar. Shanghai, China, October 2006: 660–664.
[189] Haykin S. Neural Networks Expand SP’s Horizons [J]. IEEE Signal ProcessingMagazine. 1996, 13 (2): 24–29.
[190] Bhattacharya T K, Haykin S. Neural Network-Based Radar Detection from an O-cean Environment [J]. IEEE Transactions on Aerospace and Electronic Systems.1997, 33 (2): 408–420.
[191] Haykin S, Bhattacharya T K. Modular Learning Strategy for Signal Detection ina Nonstationary Environment [J]. IEEE Transactions on Signal Processing. 1997,45 (6): 1619–1637.
[192] Haykin S. Signal Detection in a Nonstationary Environment Reformulated asan Adaptive Pattern Classification Problem [J]. Proceedings of the IEEE. 1998,86 (11): 2325–2344.
[193]史忠植.神经计算[M].北京:电子工业出版社,1993.
[194] Haykin S.神经网络原理[M].叶世伟,史忠植,译.北京:机械工业出版社,2004.
[195]敬忠良.神经网络跟踪理论及应用[M].北京:国防工业出版社,1995.
[196]杨行峻,郑君里.人工神经网络与盲信号处理[M].北京:清华大学出版社,2003.
[197]罗四维.大规模人工神经网络理论基础[M].北京:清华大学出版社,2004.
[198] Principe J C, Kim M, Fisher J W. Target Discrimination in Synthetic ApertureRadar Using Artificial Neural Networks [J]. IEEE Transactions on Image Process-ing. 1998, 7 (8): 1136–1149.
[199] http://www.surfaceoptics.com. 2011.
[200] http://www.flightgear.org. 2011.
[201] Li X R, Bar-Shalom Y. Multiple-Model Estimation with Variable Structure [J].IEEE Transactions on Automatic Control. 1996, 41 (4): 478–493.
[202] Li X R. Multiple-Model Estimation with Variable Structure Part II: Model-Set Adaptation [J]. IEEE Transactions on Automatic Control. 2000, 45 (11):2047–2060.
[203] Li X R, Zhi X, Zhang Y. MuItipie-Model Estimation with Variable Structure PartIII: Model-Group Switching Algorithm [J]. IEEE Transactions on Aerospace andElectronic Systems. 1999, 35 (1): 225–241.
[204] Li X R, Zhang Y, Zhi X. MuItipie-Model Estimation with Variable Structure PartIV: Design and Evaluation of Model-Croup Switching Algorithm [J]. IEEE Trans-actions on Aerospace and Electronic Systems. 1999, 35 (1): 242–254.
[205] Li X R, Zhang Y. Multiple-Model Estimation with Variable Structure Part V:Likely-Model Set Algorithm [J]. IEEE Transactions on Aerospace and ElectronicSystems. 2000, 36 (2): 448–466.
[206] Li X R, Jilkov V P, Ru J. Multiple-Model Estimation with Variable Structure PartVI: Expected-Mode Augmentation [J].IEEE Transactionson AerospaceandElec-tronic Systems. 2005, 41 (3): 853–867.
[207]祝依龙.脉冲雷达中频信号采集记录系统设计与实现[D].长沙:国防科学技术大学,2006.
[208]马博韬.通用雷达数据采集记录系统设计[D].长沙:国防科学技术大学,2007.
[209]范红旗,王胜,祝依龙,等.基于PXI-E的脉冲雷达通用采集记录系统[J].数据采集与处理.2006,21 (S):242–246.
[210]王元钦,杨文革,熊伟,等.高速、大容量雷达信号采集与分析系统[J].飞行器测控学报.2002,21 (4):32–35.
[211]张昆帆,王展,皇甫勘.高速数据采集和存储[J].现代雷达.2004,26(4):14–16.
[212] Ma B, Zhu Y, Fan H. TDC Based Radar Signal Reconstruction from PeriodicNonuniform Samples [C]. In Proceedings of 2007 8th International Conferenceon Electronic Measurement and Instruments. Xi’an, Shanxi, China, August 2007:673–676.
[213]马博韬,范红旗,付强.相参脉冲雷达中频采样条件研究[J].数据采集与处理.2009,24 (1):114–118.
[214]曾涛.脉冲多普勒雷达实时信号处理的理论与实现[D].北京:北京理工大学,1999.
[215] Jenq Y C. Digital Spectrum of Nonuniformly Sampled Signals: Fundamentals andHigh-Speed Waveform [J]. IEEE Transactions on Instrumentation and Measure-ment. 1988, 37 (2): 245–251.
[216] Jenq Y C. Digital Spectra of Nonuniformly Sampled Signals—Digital Look-Up Tunable Sinusoidal Oscillators [J]. IEEE Transactions on Instrumentation andMeasurement. 1988, 37 (3): 358–362.
[217] Jenq Y C. Digital Spectra of Nonuniformly Sampled Signals: A Robust Sam-pling Time Offset Estimation Algorithm for Ultra High-Speed Waveform Digi-tizers Using Interleaving [J]. IEEE Transactions on Instrumentation and Measure-ment. 1990, 39 (1): 71–75.
[218] Jenq Y C. Digital Spectra of Nonuniformly Sampled Signals: Theories and Appli-cations—Measuring Clock/Aperture Jitter of an A/D System [J]. IEEE Transac-tions on Instrumentation and Measurement. 1990, 39 (6): 969–971.
[219] Jenq Y C. Perfect Reconstruction of Digital Spectrum from Nonuniformly Sam-pled Signals [J]. IEEE Transactions on Instrumentation and Measurement. 1997,46 (3): 649–652.
[220]张延,黄佩诚.高精度时间间隔测量技术与方法[J].天文学进展.2006,24 (1):1–15.
[221] Oppenheim A V,Schafer R W,Buck J R.离散时间信号处理[M].刘树棠,黄建国,译.第二版.西安:西安交通大学出版社,2001.
[222] Lyons R G.数字信号处理[M].朱光明,程建远,刘保童,译.第二版.北京:机械工业出版社,2006.
[223]弋稳.雷达接收机技术[M].北京:电子工业出版社,2005.
[224]范红旗,翟庆林,王胜.基于IP核的锐截止中频采样滤波器优化设计[J].电子测量与仪器学报.2008,22 (1):99–103.
[225]范红旗,翟庆林,王胜,等.锐截止中频采样滤波器的设计与实现[J].电路与系统学报.2009,14 (5):31–36.
[226] Analog Devices. ADSP-TS101 TigerSHARC Processor Hardware Reference,May, 2004.
[227] Analog Devices. ADSP-TS101 TigerSHARC Processor Programming Reference,February, 2005.
[228]杨乐平,李海涛,杨磊.LabVIEW程序设计与应用[M].第二版.北京:电子工业出版社,2005.
[229] Conway J,Watts S.软件工程方法在LabVIEW中的应用[M].罗霄,周毅,译.北京:清华大学出版社,2006.
[230] Hwang I, Balakrishnan H, Tomlin C. Observability Criteria and Estimator DesignforStochasticLinearHybridSystems[C].InProceedingsofIEEEuropeanControlConference. 2003.
[231] Li X R, Zhao Z, Zhang P, et al. Model-Set Design, Choice, and Comparison forMultiple-Model Approach to Hybrid Estimation [C]. In Proceedings of Workshopon Signal Processing, Communications, Chaos and Systems. Newport, RI, USA,June 2002: 59–92.
[232] Li X R, Zhao Z, Li X-B. General Model-Set Design Methods for Multiple-ModelApproach [J]. IEEE Transactions on Automatic Control. 2005, 50 (9): 1260–1276.
[2]范金荣.精确制导武器信息化关键技术分析[J].现代防御技术.2003,31 (4):27–30.
[3]王雅梅.立体化发展我军信息化装备[J].装备指挥技术学院学报.2007,18 (5):19–22.
[4]王维平,朱自力,杨斌.现代作战理论研究[M].长沙:国防科技大学出版社,2001.
[5]梁薇,张科.精确制导武器发展及其关键技术[J].火力与指挥控制.2008,33 (12):5–7, 12.
[6]冯翠菊.现代武器智慧的眼睛——精确制导技术[J].现代物理知识.2008,20 (1):41–44.
[7]付强,何峻,程肖,等.精确制导武器技术应用向导[M].北京:国防工业出版社,2010.
[8]杨树谦.精确制导武器和技术[J].红外与激光工程.1999,28 (6):1–3,9.
[9]刘峥,张守宏.步进频率雷达在精确制导武器中的应用[J].制导与引信.2002,23 (3):9–13.
[10]黄立新,赵显超.精确制导武器的关键技术[J].无线电工程.2006,36 (12):7–9, 20.
[11]陈定昌,袁起,范金荣.精确制导武器发展趋向[J].现代防御技术.2000,28 (4):41–47, 57.
[12]殷兴良.精确制导技术的发展[J].电子学报.1995,23 (10):100–104.
[13]郭修煌.精确制导技术[M].北京:国防工业出版社,1999.
[14]刘隆和.多模复合寻的制导技术[M].北京:国防工业出版社,2001.
[15]杨树谦.精确制导技术发展现状与展望[J].航天控制.2004,22 (4):17–20.
[16]魏伟波,芮筱亭.精确制导技术研究[J].火力与指挥控制.2006,31 (2):5–8, 11.
[17]黄培康,袁起,朱振福,等.光学精确制导技术的发展现状与展望[J].红外与激光工程.2007,36 (S):1–6.
[18]顾振杰,刘宇.反舰导弹精确制导技术发展趋势分析[J].制导与引信.2010,31 (3):23–26, 48.
[19]魏伟波,芮筱亭.毫米波精确制导技术[J].火力与指挥控制.2005,30 (S):4–6, 10.
[20]姚秀娟,彭晓乐,张永科.几种精确制导技术简述[J].激光与红外.2006,36 (5):338–340.
[21]苏宏艳,朱淮城.毫米波精确制导技术及其发展趋势[J].制导与引信.2008,29 (2):6–9, 14.
[22]刘逸平.国外毫米波精确制导技术的发展趋势[J].火控雷达技术.2008,37 (3):1–6.
[23] Li X R, Jilkov V P. A Survey of Maneuvering Target Tracking– Part I: DynamicModels [C]. In Proceedings of SPIE Conference on Signal and Data Processing ofSmall Targets. Orlando, FL, USA, April 2000: 212–235.
[24] Li X R, Jilkov V P. A Survey of Maneuvering Target Tracking– Part II: Ballis-tic Targets Models [C]. In Proceedings of SPIE Conference on Signal and DataProcessing of Small Targets. San Diego, CA, USA, July– August 2001: 559–581.
[25] Li X R, Jilkov V P. A Survey of Maneuvering Target Tracking– Part III: Measure-ment Models [C]. In Proceedings of SPIE Conference on Signal and Data Process-ing of Small Targets. San Diego, CA, USA, July– August 2001: 423–446.
[26] Li X R, Jilkov V P. A Survey of Maneuvering Target Tracking– Part IV: Decision-Based Methods [C]. In Proceedings of the SPIE Conference on Signal and DataProcessing of Small Targets. Orlando, FL, USA, April 2002: 511–534.
[27] Li X R, Jilkov V P. Overview of Multiple-Model Methods for Maneuvering TargetTracking [C]. In Proceedings of SPIE Conference on Signal and Data Processingof Small Targets. San Diego, CA, USA, August 2003: 200–210.
[28] Li X R, Jilkov V P. A Survey of Maneuvering Target Tracking: ApproximationTechniques for Nonlinear Filtering [C]. In Proceedings of SPIE Conference onSignal and Data Processing of Small Targets. Orlando, FL, USA, April 2004:537–550.
[29] Li X R, Jilkov V P. A Survey of Maneuvering TargetTracking– Part VIa: Density-BasedExactNonlinearFiltering[C].InProceedingsofSPIEConferenceonSignaland Data Processing of Small Targets. Orlando, FL, USA, April 2010: 76981D-1–76981D-12.
[30] Li X R, Jilkov V P. A Survey of Maneuvering Target Tracking– Part VIb: Ap-proximate Nonlinear Density Filtering in Mixed Time [C]. In Proceedings of SPIEConference on Signal and Data Processing of Small Targets. Orlando, FL, USA,April 2010: 76981E-1–76981E-12.
[31] LiXR,JilkovVP.SurveyofManeuveringTargetTracking.PartI:DynamicMod-els [J]. IEEE Transactions on Aerospace and Electronic Systems. 2003, 39 (4):1333–1363.
[32] Li X R, Jilkov V P. Survey of Maneuvering Target Tracking. Part II: Motion Mod-els of Ballistic and Space Targets [J]. IEEE Transactions on Aerospace and Elec-tronic Systems. 2010, 46 (1): 96–119.
[33] Li X R, Jilkov V P. Survey of Maneuvering Target Tracking. Part V: Multiple-Model Methods [J]. IEEE Transactions on Aerospace and Electronic Systems.2005, 41 (4): 1255–1321.
[34]周宏仁,敬忠良,王培德.机动目标跟踪[M].北京:国防工业出版社,1991.
[35]王德纯,丁家会,程望东.精密跟踪测量雷达技术[M].北京:电子工业出版社,2006.
[36]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.
[37]权太范.目标跟踪新理论与技术[M].北京:国防工业出版社,2009.
[38] Sworder D D, Kent M, Vojak R, et al. Renewal Maneuvering Targets [J]. IEEETransactions on Aerospace and Electronic Systems. 1995, 31 (1): 138–149.
[39] Cui N, Hong L, Layne J R. A Comparison of Nonlinear Filtering Approaches withan Application to Ground Target Tracking [J]. Signal Processing. 2005, 85 (8):1469– 1492.
[40] Qu H, Pang L, Li S. A Novel Interacting Multiple Model Algorithm [J]. SignalProcessing. 2009, 89 (11): 2171–2177.
[41] Bizup D F. Improving Radar Target Tracking with the Range Rate Measuremen-t [D]. Virginia: University of Virginia, 2003.
[42] BizupDF,BrownDE.ManeuverDetectionUsingtheRadarRangeRateMeasure-ment [J]. IEEE Transactions on Aerospace and Electronic Systems. 2004, 40 (1):330–336.
[43] Ru J, Chen H, Li X R, et al. A Range Rate Based Detection Technique for Track-ing a Maneuvering Target [C]. In Proceedings of SPIE Conference on Signal andData Processing of Small Targets. San Diego, CA, USA, August 2005: 59131Q-1–59131Q-13.
[44] Zhai M, Fu S. Applying Target Maneuver Onset Detection Algorithms to DefectsDetection in Aluminum Foil [J]. Signal Processing. 2010, 90 (7): 2319– 2326.
[45]范红旗,王胜,付强.目标机动检测算法综述[J].系统工程与电子技术.2009,31 (5):1064–1070.
[46]范红旗.主动寻的制导中机动目标运动模式辨识技术[D].长沙:国防科学技术大学,2008.
[47] Turetsky V, Shinar J. Missile Guidance Laws Based on Pursuit-Evasion GameFormulations [J]. Automatica. 2003, 39 (4): 607–618.
[48] Fan H, Zhu Y, Fu Q. Impact of Mode Decision Delay on Estimation Error for Ma-neuvering Target Interception [J]. IEEE Transactions on Aerospace and ElectronicSystems. 2011, 47 (1): 702–711.
[49]黄培康,林桂森,樊正芳,等.雷达目标特征信号[M].北京:宇航出版社,1993.
[50]黄培康,殷红成,许小剑.雷达目标特性[M].北京:电子工业出版社,2005.
[51]郭桂蓉,庄钊文,陈曾平.电磁特征抽取与目标识别[M].长沙:国防科技大学出版社,1996.
[52]杜兰.雷达高分辨距离像目标识别方法研究[D].西安:西安电子科技大学,2007.
[53] Ru J, Jilkov V P, Li X R, et al. Sequential Detection of Target Maneuvers [C]. InProceedings of the 8th International Conference on Information Fusion. Philadel-phia, PA, USA, July 2005: 345–351.
[54] Ru J, Bashi A, Li X R. Performance Comparison of Target Maneuver Onset De-tectionAlgorithms[C].InProceedingsoftheSPIEConferenceonSignalandDataProcessing of Small Targets. Orlando, FL, USA, April 2004: 419–428.
[55] Basseville M, Nikiforov I. Detection of Abrupt Changes: Theory and Applica-tion [M]. Englewood Cliffs: Prentice Hall, 1993.
[56] Page E S. A Test for a Change in a Parameter Occurring at an Unknown Point [J].Biometrika. 1955, 42 (4): 523–527.
[57] Gustafsson F. The Marginalized Likelihood Test Ratio for Detecting Abrup-t Changes [J]. IEEE Transactions on Automatic Control. 1996, 41 (1): 66–78.
[58] Malldi D P, Speyer J L. A Generalized Shiryaev Sequential Probability Ratio Testfor Change Detection and Isolation [J]. IEEE Transactions on Automatic Control.1999, 44 (8): 1522–1534.
[59] Nikiforov I V. On a Class of Quadratic Tests for Detection of Abrupt Changes inSignals and Systems [C]. In Proceedings of the 1998 American Control Confer-ence. Philadelphia, PA, USA, June 1998: 751–755.
[60] Moustakides G V. Quickest Detection of Abrupt Changes for a Class of RandomProcesses[J].IEEETransactionsonInformationTheory.1998,44(5):1965–1968.
[61] Tze L L, Jerry Z S. Efficient Recursive Algorithms for Detection of Abrup-t Changes in Signals and Control Systems [J]. IEEE Transactions on AutomaticControl. 1999, 44 (5): 952–966.
[62] ChoJ,NtoulasA.EffectiveChangeDetectionUsingSampling[C].InProceedingsofthe28thInternationalConferenceonVeryLargeDataBases.HongKong,China,August 2002.
[63] Chan Y T, Hu A G C, Plant J B. A Kalman Filter Based Tracking Scheme withInput Estimation [J]. IEEE Transactions on Aerospace and Electronic Systems.1979, 15 (2): 237–244.
[64] Bogler P L. Tracking a Maneuvering Target Using Input Estimation [J]. IEEETransactions on Aerospace and Electronic Systems. 1987, 23 (3): 298–310.
[65] Lee H, Tahk M J. Generalized Input-Estimation Technique for Tracking Maneu-veringTargets[J].IEEETransactionsonAerospaceandElectronicSystems.1999,35 (4): 1388–1402.
[66] Chan Y T, Couture F. Maneuver Detection and Track Correction by Input Estima-tion [J]. IEE Proceedings F: Radar and Signal Processing. 1993, 140 (1): 21–28.
[67] Bar-Shalom Y, Birmiwal K. Variable Dimension Filter for Maneuvering TargetTracking [J]. IEEE Transactions on Aerospace and Electronic Systems. 1982,18 (5): 621–629.
[68] Bar-Shalom Y, Fortmann T E. Tracking and Data Association [M]. New York:Academic Press, 1988.
[69] YangWC,ChangFR,TsaiYH,etal.EarlyDetectionofTargetManoeuvresundera Specific False Alarm Rate [J]. IEE Proceedings - Radar, Sonar and Navigation.2003, 150 (5): 350–355.
[70] Bekir E. Adaptive Kalman Filter for Tracking Maneuvering Targets [J]. AIAAJournal of Guidance. 1983, 6 (5): 414–416.
[71] Lee S C, Liu C Y. Trajectory Estimation of Reentry Vehicle by Use of on-LineInput Estimation [J]. AIAA Journal of Guidance, Control and Dynamics. 1999,22 (6): 808–815.
[72] Kay S M.统计信号处理基础——估计与检测理论[M].罗鹏飞,张文明,刘忠,等,译.北京:电子工业出版社,2006.
[73] Willsky A S, Jones H L. A Generalized Likelihood Ratio Approach to State Esti-mation in Linear System Subject to Abrupt Changes [C]. In Proceedings of IEEEConference on Decision and Control including the 13th Symposium on AdaptiveProcesses. Phoenix, AZ, USA, November 1974: 846–853.
[74] Willsky A S, Jones H L. A Generalized Likelihood Ratio Approach to the Detec-tion and Estimation of Jumps in Linear Systems [J]. IEEE Transactions on Auto-matic Control. 1976, 21 (1): 108–112.
[75] Korn J, Gully S W, Willsky A S. Application of the Generalized Likelihood RatioAlgorithm to Maneuver Detection and Estimation [C]. In Proceedings of the 1982American Control Conference. Arlington, VA, USA, June 1982: 792–798.
[76] Schnepper K. A Comparison of GLR and Multiple Model Filters for a TargetTracking Problem [C]. In Proceedings of the 25th Conference on Decision andControl. Athens, Greece, December 1986: 666–670.
[77] Farooq M, Bruder S. Information Type Filters for Tracking a Maneuvering Tar-get [J]. IEEE Transactions on Aerospace and Electronic Systems. 1990, 26 (3):441–454.
[78] Ru J, Li X R, Jilkov V P. Multiple-Model Detection of Target Maneuvers [C]. InProceedings of SPIE Conference on Signal and Data Processing of Small Targets.San Diego, CA, USA, August 2005: 100–108.
[79] Wang T C, Varshney P K. A Tracking Algorithm for Maneuvering Targets [J].IEEE Transactions on Aerospace and Electronic Systems. 1993, 29 (3): 910–925.
[80] Whang I H, Sung T K, Lee J G. A Modified Target Maneuver Estimation Tech-nique Using Pseudo-Acceleration Information [C]. In Proceedings of the 1992 A-IAA Guidance Navigation and Control Conference. Hilton Head, SC, USA, Au-gust 1992: 1249–1254.
[81] Whang I H, Lee J G, Sung T K. Modified Input Estimation Technique Using Pseu-doresiduals [J]. IEEE Transactions on Aerospace and Electronic Systems. 1994,30 (1): 220–228.
[82] Smith M A. On Doppler Measurements for Tracking [C]. In Proceedings of Inter-national Conference on Radar. Adelaide, Australia, September 2008: 513–518.
[83] Petsios M N, Alivizatos E G, Uzunoglu N K. Manoeuvring Target Tracking us-ingMultipleBistaticRangeandRange-RateMeasurements[J].SignalProcessing.2007, 87 (4): 665–686.
[84]李小毛,刘兆磊,汪圣利.基于多个多普勒雷达的加速度和速度估计[J].现代雷达.2011,33 (1):47–50.
[85] Yuan X, Duan Z, Han C. A Maneuver Detection Method Using Multiple DopplerRadars [C]. In Proceedings of 40th Southeastern Symposium on System Theory.New Orleans, LA, USA, March 2008: 298–302.
[86] Yuan X, Han C, Duan Z, et al. Adaptive Turn Rate Estimation using Range RateMeasurements[J].IEEETransactionsonAerospaceandElectronicSystems.2006,42 (4): 1532–1540.
[87] Lei M, Han C, Cai K. Unified Maneuvering Model for Target Tracking by Us-ing Range-Rate Measurement [J]. Chinese Journal of Electronics. 2008, 17 (3):551–557.
[88] Veeraraghavan S, Rathi A, Sagayaraj M J. Turn Rate Estimation Techniques inIMM Estimators for ESA Radar Tracking [C]. In Proceedings of IEEE AerospaceConference. Big Sky, MT, USA, March 2008: 2053–2060.
[89]刘建成.加速运动目标检测及跟踪技术研究[D].长沙:国防科学技术大学,2007.
[90]李文臣.高速机动目标雷达信号参数估计与成像处理[D].长沙:国防科学技术大学,2009.
[91]邹虹.多分量线性调频信号的时频分析[D].西安:西安电子科技大学,2000.
[92] Wood J C, Barry D T. Linear Signal Synthesis Using the Radon-Wigner Transfor-m [J]. IEEE Transactions on Signal Processing. 1994, 42 (8): 2105–2111.
[93]刘建成,王雪松,肖顺平,等.基于Wigner-Hough变换的径向加速度估计[J].电子学报.2005,33 (12):2235–2238.
[94] Wang M, Chan A K, Chui C K. Linear Frequency Modulated Signal DetectionUsing Radon-Ambiguity Transform [J]. IEEE Transactions on Signal Processing.1998, 46 (3): 571–586.
[95]杜文超,王国宏,高学强.低信噪比条件下在短时信号中提取目标径向加速度方法研究[J].中国科学E辑:技术科学.2007,37 (7):923–943.
[96] Ru J, Jilkov V P, Li X R, et al. Detection of Target Maneuver Onset [J]. IEEETransactions on Aerospace and Electronic Systems. 2009, 45 (2): 536–554.
[97]赵军,单甘霖,吉兵,等.飞机姿态角辅助的交互式多模型跟踪算法[J].电光与控制.2011,18 (3):43–47, 51.
[98] Kendrick J D, Maybeck P S, Reid J G. Estimation of Aircraft Target Motion UsingOrientation Measurements [J]. IEEE Transactions on Aerospace and ElectronicSystems. 1981, AES-17 (2): 254–260.
[99] Hughes E J, Leyland M. Target Manoeuvre Detection Using Radar Glint [J]. Elec-tronics Letters. 1998, 34 (17): 1695–1696.
[100] Hughes E J. Radar Cross Section Modeling Using Genetic Algorithms [D].Shrivenham: Cranfield University, 1998.
[101] Yang C, Garber W, Mitchell R, et al. A Simple Maneuver Indicator From Target’sRange-Doppler Image [C]. In Proceedings of 10th International Conference onInformation Fusion. Quebec, Canada, July 2007: 9–16.
[102] Yang C, Blasch E. Estimating Target Range-Doppler Image Slope for ManeuverIndication [C]. In Proceedings of SPIE Conference on Signal Processing, SensorFusion, and Target Recognition XVII. Orlando, FL, USA, March 2008: 696808-1–696808-12.
[103]王国宏,毛士艺,何友.红外传感器目标跟踪算法[J].火力与指挥控制.2001,26 (2):5–9.
[104]何兵,毛士艺,张有为,等.利用近距离目标红外图像的机动检测问题研究[J].电子学报.2001,29 (3):332–336.
[105] SworderDD,HutchinsRG.ManeuverEstimationUsingMeasurementsofOrien-tation [J]. IEEE Transactions on Aerospace and Electronic Systems. 1990, 26 (4):625–638.
[106] Hutchins R G, Sworder D D. Image Fusion Algorithms for Tracking Maneuver-ing Targets [J]. AIAA Journal of Guidance, Control and Dynamics. 1992, 15 (1):175–184.
[107] Sworder D D, Hutchins R G. Improved Tracking of an Agile Target [J]. AIAAJournal of Guidance, Control and Dynamics. 1992, 15 (5): 1281–1284.
[108] Laneuville D, Mariton M. Image Based Target Maneuver Detection [C]. In Pro-ceedings of the 30th IEEE Conference on Decision and Control. Brighton, UK,December 1991: 2066–2067.
[109] Laneuville D, Dufour E, Bertrand P. Image Based Maneuvering Target Track-ing [C]. In Proceedings of the American Control Conference. Philadelphia, PA,USA, June 1998: 2444–2449.
[110] Shetty S, Alouani A T. Image Sensor Based Target Maneuver Detection [C]. InProceedings of SPIE Conference on Acquisition, Tracking, and Pointing VII. Or-lando, FL, USA, April 1993: 161–170.
[111] Shetty S, Alouani A T. Image-Sensor-Based Target Maneuver Detection [J]. Op-tical Engineering. 1993, 32 (11): 2735–2740.
[112] Shetty S, Alouani A T. A Multisensor Tracking System With an Image-Based Ma-neuvering Detector [C]. In Proceedings of the American Control Conference. Bal-timore, MD, USA, June 1994: 3288–3292.
[113] ShettyS, AlouaniAT.Performanceof an Image-BasedManeuverDetector[C].InProceedings of the 33rd Conference on Decision and Control. Lake Buena Vista,FL, USA, December 1994: 3259–3264.
[114] Shetty S, Alouani A T. A Multisensor Tracking System With an Image-Based Ma-neuvering Detector [J]. IEEE Transactions on Aerospace and Electronic Systems.1996, 32 (1): 167–181.
[115]何友,王国宏,陆大金,等.多传感器信息融合及应用[M].第二版.北京:电子工业出版社,2007.
[116]保铮,刑孟道,王彤.雷达成像技术[M].北京:电子工业出版社,2005.
[117] Song T L, Lee D G. Effective Filtering of Target Glint [J]. IEEE Transactions onAerospace and Electronic Systems. 2001, 36 (1): 234–241.
[118] Blasch E, Yang C. Ten Methods to Fuse GMTI and HRRR Measurements for JointTracking Identification [C]. In Proceedings of the 7th International Conference onInformation Fusion. Stockholm, Sweden, June– July 2004: 1006–1013.
[119] Singer P F, Coursey A L. Feature Aided Tracking (FAT) [C]. In Proceedings of theSPIE Conference on Signal and Data Processing of Small Targets. Orlando, FL,USA, 2004: 249–259.
[120] Oshman Y, David A. Differential-Game-Based Guidance Law using Target Orien-tation Observations [J]. IEEE Transactions on Aerospace and Electronic Systems.2006, 42 (1): 316–326.
[121] Tsang L, Kong J A, Ding K-H, et al. Scattering of Electromagnetic Waves: Nu-merical Simulations [M]. New York: John Wiley and Sons, 2001.
[122] Tsang L, Kong J A. Scattering of Electromagnetic Waves: Advanced Topics [M].New York: John Wiley and Sons, 2001.
[123] MusickSH,SherwoodJU,PiattTL,etal.ASimulationSystemforFeature-AidedTrackingResearch[C].InProceedingsofSPIEConferenceonAlgorithmsforSyn-thetic Aperture Radar Imagery XI. Orlando, FL, USA, April 2004: 309–320.
[124] Piatt T L, Sherwood J U, Musick S H. Radar Signature Generation for Feature-Aided Tracking Research [C]. In Proceedings of SPIE Conference on Algorithmsfor Synthetic Aperture Radar Imagery XII. Orlando, FL, USA, March–April 2005:419–427.
[125]肖业伦.航空航天器运动的建模——飞行动力学的理论基础[M].北京:北京航空航天大学出版社,2003.
[126]曹义华.直升机飞行力学[M].北京:北京航空航天大学出版社,2005.
[127] Adler F P. Missile Guidance by Three-Dimensional Proportional Navigation [J].Journal of Applied Physics. 1956, 27 (5): 500–507.
[128] Berndt J S. JSBSim Reference Manual, August, 2009.
[129] http://www.jsbsim.org. 2011.
[130] HarringtonRF.Time-HarmonicElectromagneticFields[M].NewYork:McGraw-Hill, 1968.
[131] BowmanJJ.ElectromagneticandAcousticScatteringbySimpleShapes[M].Am-sterdam: North-Holland Publishing, 1969.
[132] Kline M, Kay I W. Electromagnetic Theory and Geometrical Optics [M]. NewYork: John Wiley and Sons, 1965.
[133] Ruck G T. Radar Cross Section Handbook [M]. New York: Plenum Press, 1970.
[134] Crispin J W. Method of Radar Section Analysis [M]. New York: Academic Press,1968.
[135] Knott E F. Radar Cross Section [M]. Dedham: Artech House, 1985.
[136] BhattacharyyaAK,SenguptaDL.RadarCrossSectionAnalysisandControl[M].Norwood: Artech House, 1991.
[137] Wang J J H. Generalized Moment Methods in Electromagnetics [M]. New York:John Wiley and Sons, 1991.
[138] Fritch P C. Special Issue on Radar Reflectivity [J]. Proceedings of the IEEE. 1965,53 (8): 769–1166.
[139] Stone W R. Special Issue on Radar Cross Sections of Complex Objects [J]. Pro-ceedings of the IEEE. 1989, 77 (5): 639–823.
[140] Skolnik M I. Radar Handbook [M]. 3rd ed. New York: McGraw-Hill, 2008.
[141] Marcum J I. A Statistical Theory of Target Detection by Pulsed Radar [J]. IRETransactions on Information Theory. 1960, 6 (2): 59–267.
[142] Swerling P. Probability of Detection for Fluctuating Tragets [J]. IRE Transactionson Information Theory. 1960, 6 (2): 269–308.
[143] Weinstock W. Target Cross Section Models for Radar System Analysis [D]. Penn-sylvania: University of Pennsylvania, 1964.
[144] Meyer D P, Mayer H A. Radar Target Detection– Handbook of Theory and Prac-tice [M]. San Diego: Academic Press, 1973.
[145] Scholefield P H R. Statistical Aspects of Ideal Radar Targets [J]. Proceedings ofthe IEEE. 1967, 55 (4): 587–589.
[146] HeidbrederGR,MitchellRL.DetectionProbabilitiesforLog-NormallyDistribut-ed Signals [J]. IEEE Transactions on Aerospace and Electronic Systems. 1967,3 (1): 5–13.
[147]黄培康.飞行器隐身技术评述[J].系统工程与电子技术.1984,6 (1):1–8.
[148]尹光俊,廖绍彬.单层与多层吸波材料设计[J].北京大学学报(自然科学版).1990,26 (3):327–327.
[149] HowardD D. Radar TargetGlint in Trackingand GuidanceSystem Based on EchoSignal Phase Distortion [C]. In Procedings of NEC. 1959: 840–849.
[150] Lindsay J E. Anglar Glint and the Moving, Rotating, Complex Radar Target [J].IEEE Transactions on Aerospace and Electronic Systems. 1968, AES-4 (2):164–173.
[151] DunnJH,HowardDD.RadarTargetAmplitude,Angle,andDopplerScintillationfrom Analysis of the Echo Signal Propagating in Space [J]. IEEE Transactions onMicrowave Theory and Techniques. 1968, 16 (9): 715–728.
[152]黄培康,殷红成.扩展目标的角闪烁[J].系统工程与电子技术.1990,12 (12):1–17.
[153] YinHC,HuangPK.UnificationandComparisonBetweenTwoConceptsofRadarTargetAngularGlint[J].IEEETransactionsonAerospaceandElectronicSystems.1995, 31 (2): 778–783.
[154] Yin H C, Huang P K. Further Comparison Between Two Concepts of Radar TargetAngular Glint [J]. IEEE Transactions on Aerospace and Electronic Systems. 2008,44 (1): 372–380.
[155] OstrovityanovRV,BasalovFA.StatisticalTheoryofExtendedRadarTargets[M].Norwood: Artech House, 1985.
[156]陈国瑛.雷达目标角闪烁的建模与抑制研究[D].北京:航天工业总公司第二研究院,1998.
[157] Sims R J, Graf E R. The Reduction of Radar Glint by Diversity Techniques [J].IEEE Transactions on Antennas and Propagation. 1971, AP-19 (4): 462–468.
[158] Berizzi F, Corsini G. Autofocusing of Inverse Synthetic Aperture Radar Imagesusing Contrast Optimization [J]. IEEE Transactions on Aerospace and ElectronicSystems. 1996, 32 (3): 1185–1191.
[159]邢孟道,保铮.低分辨雷达的一维横向成像及提高分辨率的方法[J].西安电子科技大学学报(自然科学版).2000,27 (6):700–704.
[160]夏桂芬,朱淮城,李天池,等.毫米波雷达导引头频域仿形技术研究[J].系统工程与电子技术.2008,30 (9):1649–1652.
[161]高烽,王树文.单脉冲雷达导引头仿形技术[J].制导与引信.2003,24(2):1–5.
[162]姜正林,保铮,邢孟道.低分辨雷达编队目标分辨新方法[J].西安电子科技大学学报(自然科学版).2001,28 (4):482–486.
[163] Chen V C, Ling H. Time-Frequency Transforms for Radar Imaging and SignalAnalysis [M]. Norwood: Artech House, 2002.
[164] Keller J B. Geometrical Theory of Diffraction [J]. Journal of the Optical Societyof America. 1962, 52 (2): 116–130.
[165] Potter L C, Chiang D-M, Carriere R, et al. A GTD Based Parametric Modelfor Radar Scattering [J]. IEEE Transactions on Antennas and Propagation. 1995,43 (10): 1058–1067.
[166] BhallaR,LingH,MooreR,etal.3DScatteringCenterRepresentationofComplexTargets Using the Shooting and Bouncing Ray Technique: A Review [J]. IEEEAntennas and Propagation Magazine. 1998, 40 (5): 30–39.
[167]范红旗,王胜,祝依龙,等.相位梯度法计算近场角闪烁的解析式[J].电子学报.2009,37 (5):937–941.
[168]周剑雄.光学区雷达目标三维散射中心重构理论与技术[D].长沙:国防科学技术大学,2006.
[169] Zhou J, Zhao H, Shi Z, et al. Global Scattering Center Model Extraction of RadarTargets Based on Wideband Measurements [J]. IEEE Transactions on Antennasand Propagation. 2008, 56 (7): 2051–2060.
[170]丁鹭飞,耿富录.雷达原理[M].第三版.西安:西安电子科技大学出版社,2002.
[171]皇甫堪,陈建文,楼生强.现代数字信号处理[M].北京:电子工业出版社,2004.
[172] Boers Y, Driessen J N. Multitarget Particle Filter Track Before Detect Applica-tion [J]. IEE Proceedings - Radar, Sonar and Navigation. 2004, 151 (6): 351–357.
[173] Boers Y, Driessen H, Torstensson J, et al. Track-Before-Detect Algorithm forTracking Extended Targets [J]. IEE Proceedings - Radar, Sonar and Navigation.2006, 153 (4): 345–351.
[174] Kurien T. Framework for Integrated Tracking and Identification of Multiple Tar-gets [C]. In Proceedings of IEEE/AIAA 10th Digital Avionics Systems Confer-ence. Los Angels, CA, USA, October 1991: 362–366.
[175] Yang C, Blasch E. Mutual-Aided Target Tracking and Identification [C]. In Pro-ceedings of SPIE Conference on Multisensor, Multisource Information Fusion:Architectures, Algorithms, and Applications. Orlando, FL, USA, April 2003:152–163.
[176] Minvielle P, Marrs A D, Maskell S, et al. Joint Target Tracking and Identification- Part I: Sequential Monte Carlo Model-Based Approaches [C]. In Proceedings ofthe 8th International Conference on Information Fusion. Philadephia, PA, USA,July 2005: 256–266.
[177] Minvielle P, Marrs A D, Maskell S, et al. Joint Target Tracking and Identifica-tion - Part II: Shape Video Computing [C]. In Proceedings of the 8th InternationalConference on Information Fusion. Philadephia, PA, USA, July 2005: 267–274.
[178] Drummond O E. On Categorical Feature-Aided Target Tracking [C]. In Proceed-ings of the SPIE Conference on Signal and Data Processing of Small Targets. SanDiego, CA, USA, August 2003: 544–558.
[179] Chenouard N, Blochb I, Olivo-Marin J-C. Feature-Aided Particle Tracking [C].In Proceedings of 15th IEEE International Conference on Image Processing. SanDiego, CA, USA, October 2008: 1796–1799.
[180] Oshman Y, Arad D. Enhanced Air-to-Air Missile Tracking Using Target Orienta-tion Observations [J]. AIAA Journal of Guidance, Control and Dynamics. 2004,27 (4): 595–606.
[181] Daubechies I.小波十讲[M].李建平,杨万年,译.北京:国防工业出版社,2004.
[182]成礼智,王红霞,罗永.小波的理论与应用[M].北京:科学出版社,2004.
[183]郭桂蓉,谢维信,庄钊文,等.模糊模式识别[M].长沙:国防科技大学出版社,1992.
[184]徐扬,秦克云,刘军,等.模糊模式识别及其应用[M].成都:西南交通大学出版社,1999.
[185] Li J, Stoica P. Efficient Mixed-Spectrum Estimation with Applications to Tar-get Feature Extraction [J]. IEEE Transactions on Signal Processing. 1996, 42 (2):281–295.
[186] Li J, Zheng D, Stoica P. Angle and Waveform Estimation Via RELAX [J]. IEEETransactions on Aerospace and Electronic Systems. 1997, 33 (3): 1077–1087.
[187] Maranda B H. On the False Alarm Probability for an Overlapped FFT Proces-sor [J]. IEEE Transactions on Aerospace and Electronic Systems. 1996, 32 (4):1452–1456.
[188] Fan H, Wang S, Chen F, et al. Frame-overlapped Zoom-FFT Optimization in PDRadar Application [C]. In Proceedings of 2006 CIE International Conference onRadar. Shanghai, China, October 2006: 660–664.
[189] Haykin S. Neural Networks Expand SP’s Horizons [J]. IEEE Signal ProcessingMagazine. 1996, 13 (2): 24–29.
[190] Bhattacharya T K, Haykin S. Neural Network-Based Radar Detection from an O-cean Environment [J]. IEEE Transactions on Aerospace and Electronic Systems.1997, 33 (2): 408–420.
[191] Haykin S, Bhattacharya T K. Modular Learning Strategy for Signal Detection ina Nonstationary Environment [J]. IEEE Transactions on Signal Processing. 1997,45 (6): 1619–1637.
[192] Haykin S. Signal Detection in a Nonstationary Environment Reformulated asan Adaptive Pattern Classification Problem [J]. Proceedings of the IEEE. 1998,86 (11): 2325–2344.
[193]史忠植.神经计算[M].北京:电子工业出版社,1993.
[194] Haykin S.神经网络原理[M].叶世伟,史忠植,译.北京:机械工业出版社,2004.
[195]敬忠良.神经网络跟踪理论及应用[M].北京:国防工业出版社,1995.
[196]杨行峻,郑君里.人工神经网络与盲信号处理[M].北京:清华大学出版社,2003.
[197]罗四维.大规模人工神经网络理论基础[M].北京:清华大学出版社,2004.
[198] Principe J C, Kim M, Fisher J W. Target Discrimination in Synthetic ApertureRadar Using Artificial Neural Networks [J]. IEEE Transactions on Image Process-ing. 1998, 7 (8): 1136–1149.
[199] http://www.surfaceoptics.com. 2011.
[200] http://www.flightgear.org. 2011.
[201] Li X R, Bar-Shalom Y. Multiple-Model Estimation with Variable Structure [J].IEEE Transactions on Automatic Control. 1996, 41 (4): 478–493.
[202] Li X R. Multiple-Model Estimation with Variable Structure Part II: Model-Set Adaptation [J]. IEEE Transactions on Automatic Control. 2000, 45 (11):2047–2060.
[203] Li X R, Zhi X, Zhang Y. MuItipie-Model Estimation with Variable Structure PartIII: Model-Group Switching Algorithm [J]. IEEE Transactions on Aerospace andElectronic Systems. 1999, 35 (1): 225–241.
[204] Li X R, Zhang Y, Zhi X. MuItipie-Model Estimation with Variable Structure PartIV: Design and Evaluation of Model-Croup Switching Algorithm [J]. IEEE Trans-actions on Aerospace and Electronic Systems. 1999, 35 (1): 242–254.
[205] Li X R, Zhang Y. Multiple-Model Estimation with Variable Structure Part V:Likely-Model Set Algorithm [J]. IEEE Transactions on Aerospace and ElectronicSystems. 2000, 36 (2): 448–466.
[206] Li X R, Jilkov V P, Ru J. Multiple-Model Estimation with Variable Structure PartVI: Expected-Mode Augmentation [J].IEEE Transactionson AerospaceandElec-tronic Systems. 2005, 41 (3): 853–867.
[207]祝依龙.脉冲雷达中频信号采集记录系统设计与实现[D].长沙:国防科学技术大学,2006.
[208]马博韬.通用雷达数据采集记录系统设计[D].长沙:国防科学技术大学,2007.
[209]范红旗,王胜,祝依龙,等.基于PXI-E的脉冲雷达通用采集记录系统[J].数据采集与处理.2006,21 (S):242–246.
[210]王元钦,杨文革,熊伟,等.高速、大容量雷达信号采集与分析系统[J].飞行器测控学报.2002,21 (4):32–35.
[211]张昆帆,王展,皇甫勘.高速数据采集和存储[J].现代雷达.2004,26(4):14–16.
[212] Ma B, Zhu Y, Fan H. TDC Based Radar Signal Reconstruction from PeriodicNonuniform Samples [C]. In Proceedings of 2007 8th International Conferenceon Electronic Measurement and Instruments. Xi’an, Shanxi, China, August 2007:673–676.
[213]马博韬,范红旗,付强.相参脉冲雷达中频采样条件研究[J].数据采集与处理.2009,24 (1):114–118.
[214]曾涛.脉冲多普勒雷达实时信号处理的理论与实现[D].北京:北京理工大学,1999.
[215] Jenq Y C. Digital Spectrum of Nonuniformly Sampled Signals: Fundamentals andHigh-Speed Waveform [J]. IEEE Transactions on Instrumentation and Measure-ment. 1988, 37 (2): 245–251.
[216] Jenq Y C. Digital Spectra of Nonuniformly Sampled Signals—Digital Look-Up Tunable Sinusoidal Oscillators [J]. IEEE Transactions on Instrumentation andMeasurement. 1988, 37 (3): 358–362.
[217] Jenq Y C. Digital Spectra of Nonuniformly Sampled Signals: A Robust Sam-pling Time Offset Estimation Algorithm for Ultra High-Speed Waveform Digi-tizers Using Interleaving [J]. IEEE Transactions on Instrumentation and Measure-ment. 1990, 39 (1): 71–75.
[218] Jenq Y C. Digital Spectra of Nonuniformly Sampled Signals: Theories and Appli-cations—Measuring Clock/Aperture Jitter of an A/D System [J]. IEEE Transac-tions on Instrumentation and Measurement. 1990, 39 (6): 969–971.
[219] Jenq Y C. Perfect Reconstruction of Digital Spectrum from Nonuniformly Sam-pled Signals [J]. IEEE Transactions on Instrumentation and Measurement. 1997,46 (3): 649–652.
[220]张延,黄佩诚.高精度时间间隔测量技术与方法[J].天文学进展.2006,24 (1):1–15.
[221] Oppenheim A V,Schafer R W,Buck J R.离散时间信号处理[M].刘树棠,黄建国,译.第二版.西安:西安交通大学出版社,2001.
[222] Lyons R G.数字信号处理[M].朱光明,程建远,刘保童,译.第二版.北京:机械工业出版社,2006.
[223]弋稳.雷达接收机技术[M].北京:电子工业出版社,2005.
[224]范红旗,翟庆林,王胜.基于IP核的锐截止中频采样滤波器优化设计[J].电子测量与仪器学报.2008,22 (1):99–103.
[225]范红旗,翟庆林,王胜,等.锐截止中频采样滤波器的设计与实现[J].电路与系统学报.2009,14 (5):31–36.
[226] Analog Devices. ADSP-TS101 TigerSHARC Processor Hardware Reference,May, 2004.
[227] Analog Devices. ADSP-TS101 TigerSHARC Processor Programming Reference,February, 2005.
[228]杨乐平,李海涛,杨磊.LabVIEW程序设计与应用[M].第二版.北京:电子工业出版社,2005.
[229] Conway J,Watts S.软件工程方法在LabVIEW中的应用[M].罗霄,周毅,译.北京:清华大学出版社,2006.
[230] Hwang I, Balakrishnan H, Tomlin C. Observability Criteria and Estimator DesignforStochasticLinearHybridSystems[C].InProceedingsofIEEEuropeanControlConference. 2003.
[231] Li X R, Zhao Z, Zhang P, et al. Model-Set Design, Choice, and Comparison forMultiple-Model Approach to Hybrid Estimation [C]. In Proceedings of Workshopon Signal Processing, Communications, Chaos and Systems. Newport, RI, USA,June 2002: 59–92.
[232] Li X R, Zhao Z, Li X-B. General Model-Set Design Methods for Multiple-ModelApproach [J]. IEEE Transactions on Automatic Control. 2005, 50 (9): 1260–1276.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |