战术制导武器捷联惯导系统快速传递对准研究
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摘要
世界政治格局已由两极对峙状态转化为多极化状态,因而世界各国的军事战略也随之发生了巨大的变化。随着世界局部战争的发展,世界各军事大国的军事战略由原来的以全国性的战略防御和进攻为重点逐渐转变为以战区防御和进攻为重点。而在战区军事防御和进攻中,战术制导武器扮演着重要角色。为了适应灵活性、多变性和突发性的战术特点,要求战术制导武器捷联惯导系统对准速度快,精度高,鲁棒性强。而如何解决惯导系统对准精确性和快速性之间的矛盾一直是惯性技术领域研究的难点课题。另外由于战术制导武器一般在运载体上发射,其所处的环境比较恶劣,所以其对准性能的鲁棒性也更为重要。为解决上述问题,本文将小波理论和鲁棒滤波理论应用于传递对准,取得了以下几方面的成果。
针对运载体上的主惯导系统多数是平台惯导系统,它不能直接给出角速度信息的特点,提出了新的快速传递对准方案,即速度加姿态变化量匹配方案。该方案直接对主、子惯导的导航坐标系之间的失准角进行估计,次优Kalman滤波状态变量只有6个。仿真研究表明,该方案是十分有效的。
提出了二次快速传递对准和三次快速传递对准的概念和方法。在此基础上给出了机载导弹空中二次快速传递对准的方法、垂直发射舰载高速导弹二次快速传递对准和三次快速传递对准的方法。三种对准方法在对准第一阶段均采用速度加姿态变化量匹配方法,完成由运载体主惯导对弹载SINS的第一次传递对准。第一次传递对准是在导弹发射之前进行的,主要完成航向对准,同时初步完成水平对准。在对准第二阶段采用速度匹配方法,完成由弹载GPS对弹载SINS的第二次传递对准。对于机载导弹的空中对准来说,第二次传递对准的任务是导弹发射后在导弹上进一步完成水平对准。对于垂直发射的舰载导弹来说,第二次传递对准是在垂直上升阶段进行的,其任务是进一步完成水平对准。而舰载导弹的第三次传递对准是在水平飞行过程中进行的,其任务是再一次进行航向对准。二次和三次快速传递对准方法极大的缩短了发射前的对准时间。
深入研究了机动运动对状态变量可观测度的影响,提出了Kalman滤波器观测增强方法,进而从理论上证明了增加机动运动的强度可以提高状态变量的可观测度,并提出了提高状态变量可观测度的几种方法。
以基于Krein空间的H_∞滤波理论为基础,将H_∞滤波用于快速传递对准,对滤波与Kalman滤波的估计精度对不确定噪声的鲁棒性进行了研究。结果表明,在一定的噪声不确定性范围内,Kalman滤波对于噪声的不确定性是具有一H_∞定的鲁棒性的,并且就精度而言,其鲁棒性优于H_∞滤波,但滤波的估计速度优于Kalman滤波。在此基础上提出了基于H_∞滤波与Kalman滤波联合滤波的
二次快速传递对准的方法。即第一次传递对准利用H_∞滤波器估计速度快的这一优点,通过速度匹配进行水平对准;第二次对准采用Kalman滤波器通过速度加姿态变化量匹配方案进行航向对准。
将基于Krein空间的鲁棒Kalman滤波器用于快速传递对准。结果表明,在有参数摄动的情况下,通过适当选择等效白噪声的强度以及鲁棒Kalman滤波器参数,鲁棒Kalman滤波器的精度鲁棒性优于标准Kalman滤波器。
以小波变换和提升小波变换理论为基础,将小波滤波和提升小波滤波用于快速传递对准。提出了基于批次小波预滤波和基于批次提升小波预滤波的自适应快速传递对准方法,研究结果表明方法是十分有效的。
The world politics situation has changed from the two poles confronting each other to multiple poles, and the military strategies of the countries in possession of strong military force have greatly changed. With the development of the local world wars, the military strategies of the countries in possession of strong military force have turned their military strategic emphases from countrywide strategic defense and offense to local region defense and offense. Tactical guided weapons play an important part in war region defense and offense. In order to adapt tactical guided weapons to the characteristic of agility, levity and burst tactics, it is required that the alignment of their strapdown inertial navigation systems is rapid, accurate and robust. How to deal with the conflict between the rapidity and the accuracy of inertial navigation systems has been important topic in inertial technology field for a long time. Because tactical guided weapons are commonly launched on vehicles and in bad environments, their alignment robust performance is more important. In order to solve above problem, wavelet theory and robust filtering theory are applied to transfer alignment in this dissertation. Investigation is done in the following.
Because many master inertial navigation systems on vehicles are gimbaled inertial navigation systems and don’t provide angle rate, a new rapid transfer alignment approach called velocity plus attitude change matching approach is proposed. This approach direct estimates misalignment angle between master and slave inertial navigation systems and its suboptimal Kalman filter only has six state variables. Simulation shows it is very effective. The concept and approach of twice transfer alignment and thrice transfer alignment are presented. Twice rapid transfer alignment approach to the missiles carried aboard in flight, twice and thrice rapid transfer alignment approach to high-speed missiles carried on warships that are launched vertically are proposed according to the concept. All the three approaches in the first phrase employ the velocity plus attitude change matching, and perform the first time transfer alignment between master INS and slave SINS of missiles. The first time transfer alignment mainly performs azimuth alignment and primarily performs horizon alignment before missiles are launched. In the second phrase the approach employs velocity matching and performs the second time transfer alignment between GPS and SINS of missiles. For the missiles carried aboard in flight, the second time transfer alignment is carried out after the missiles are launched, and the horizon alignment is performed in the second phrase. For the high-speed missiles carried on warships that are launched vertically, the second time transfer alignment is carried out when missiles are rising and its task is to perform horizon alignment once more. The third time transfer alignment of the missiles carried on warships is carried out when the missiles are in level and straight flight, and its task is to perform azimuth alignment once more. Twice and thrice alignment approaches reduce accurate alignment time before launching the missiles.
The influence of maneuver on observable degree of state variables are investigated intensively, and the approach of enhancing observable degree of the state variables in Kalman filter is proposed. Furthermore, Increasing maneuver intensity can enhance observable degree of the state variables in Kalman filter is demonstrated in theory, and several approaches of enhancing observable degree of the state variables are presented.
Based on H_∞filtering theory in Krein space, H_∞filter is applied to rapid transfer alignment. The robustness of estimation accuracy of H_∞filter and Kalman filter against uncertain noise is investigated. The study result shows that within a certain range of noise uncertainty, Kalman filter has robustness against uncertain noise, and in accuracy robustness Kalman filter is superior to H_∞filter, but the estimation speed of H_∞filter is superior to Kalman filter. Based on the result, an approach to twice rapid transfer alignment based on H_∞filtering associated with
Kalman filtering is proposed. In the first time alignment, H_∞filter feature being taken advantage of, horizontal alignment is achieved by velocity matching. In the second time alignment, Kalman filter being used, azimuth alignment is achieved by velocity plus attitude change matching. Robust Kalman filter in Krein space is applied to rapid transfer alignment. It is showed that in the case of parameter perturbation, with the equivalent intensity of white noise and the parameters of robust Kalman filter are properly chose, the accuracy robustness of robust Kalman filter is superior to that of standard Kalman filter.
Based on wavelet transform and lifting wavelet transform theory, wavelet filtering and lifting wavelet filtering are applied to rapid transfer alignment. The rapid transfer alignment approaches based on wavelet pre-filtering with batch data and lifting wavelet pre-filtering with batch data are proposed. It is showed that the proposed approaches are very effective.
针对运载体上的主惯导系统多数是平台惯导系统,它不能直接给出角速度信息的特点,提出了新的快速传递对准方案,即速度加姿态变化量匹配方案。该方案直接对主、子惯导的导航坐标系之间的失准角进行估计,次优Kalman滤波状态变量只有6个。仿真研究表明,该方案是十分有效的。
提出了二次快速传递对准和三次快速传递对准的概念和方法。在此基础上给出了机载导弹空中二次快速传递对准的方法、垂直发射舰载高速导弹二次快速传递对准和三次快速传递对准的方法。三种对准方法在对准第一阶段均采用速度加姿态变化量匹配方法,完成由运载体主惯导对弹载SINS的第一次传递对准。第一次传递对准是在导弹发射之前进行的,主要完成航向对准,同时初步完成水平对准。在对准第二阶段采用速度匹配方法,完成由弹载GPS对弹载SINS的第二次传递对准。对于机载导弹的空中对准来说,第二次传递对准的任务是导弹发射后在导弹上进一步完成水平对准。对于垂直发射的舰载导弹来说,第二次传递对准是在垂直上升阶段进行的,其任务是进一步完成水平对准。而舰载导弹的第三次传递对准是在水平飞行过程中进行的,其任务是再一次进行航向对准。二次和三次快速传递对准方法极大的缩短了发射前的对准时间。
深入研究了机动运动对状态变量可观测度的影响,提出了Kalman滤波器观测增强方法,进而从理论上证明了增加机动运动的强度可以提高状态变量的可观测度,并提出了提高状态变量可观测度的几种方法。
以基于Krein空间的H_∞滤波理论为基础,将H_∞滤波用于快速传递对准,对滤波与Kalman滤波的估计精度对不确定噪声的鲁棒性进行了研究。结果表明,在一定的噪声不确定性范围内,Kalman滤波对于噪声的不确定性是具有一H_∞定的鲁棒性的,并且就精度而言,其鲁棒性优于H_∞滤波,但滤波的估计速度优于Kalman滤波。在此基础上提出了基于H_∞滤波与Kalman滤波联合滤波的
二次快速传递对准的方法。即第一次传递对准利用H_∞滤波器估计速度快的这一优点,通过速度匹配进行水平对准;第二次对准采用Kalman滤波器通过速度加姿态变化量匹配方案进行航向对准。
将基于Krein空间的鲁棒Kalman滤波器用于快速传递对准。结果表明,在有参数摄动的情况下,通过适当选择等效白噪声的强度以及鲁棒Kalman滤波器参数,鲁棒Kalman滤波器的精度鲁棒性优于标准Kalman滤波器。
以小波变换和提升小波变换理论为基础,将小波滤波和提升小波滤波用于快速传递对准。提出了基于批次小波预滤波和基于批次提升小波预滤波的自适应快速传递对准方法,研究结果表明方法是十分有效的。
The world politics situation has changed from the two poles confronting each other to multiple poles, and the military strategies of the countries in possession of strong military force have greatly changed. With the development of the local world wars, the military strategies of the countries in possession of strong military force have turned their military strategic emphases from countrywide strategic defense and offense to local region defense and offense. Tactical guided weapons play an important part in war region defense and offense. In order to adapt tactical guided weapons to the characteristic of agility, levity and burst tactics, it is required that the alignment of their strapdown inertial navigation systems is rapid, accurate and robust. How to deal with the conflict between the rapidity and the accuracy of inertial navigation systems has been important topic in inertial technology field for a long time. Because tactical guided weapons are commonly launched on vehicles and in bad environments, their alignment robust performance is more important. In order to solve above problem, wavelet theory and robust filtering theory are applied to transfer alignment in this dissertation. Investigation is done in the following.
Because many master inertial navigation systems on vehicles are gimbaled inertial navigation systems and don’t provide angle rate, a new rapid transfer alignment approach called velocity plus attitude change matching approach is proposed. This approach direct estimates misalignment angle between master and slave inertial navigation systems and its suboptimal Kalman filter only has six state variables. Simulation shows it is very effective. The concept and approach of twice transfer alignment and thrice transfer alignment are presented. Twice rapid transfer alignment approach to the missiles carried aboard in flight, twice and thrice rapid transfer alignment approach to high-speed missiles carried on warships that are launched vertically are proposed according to the concept. All the three approaches in the first phrase employ the velocity plus attitude change matching, and perform the first time transfer alignment between master INS and slave SINS of missiles. The first time transfer alignment mainly performs azimuth alignment and primarily performs horizon alignment before missiles are launched. In the second phrase the approach employs velocity matching and performs the second time transfer alignment between GPS and SINS of missiles. For the missiles carried aboard in flight, the second time transfer alignment is carried out after the missiles are launched, and the horizon alignment is performed in the second phrase. For the high-speed missiles carried on warships that are launched vertically, the second time transfer alignment is carried out when missiles are rising and its task is to perform horizon alignment once more. The third time transfer alignment of the missiles carried on warships is carried out when the missiles are in level and straight flight, and its task is to perform azimuth alignment once more. Twice and thrice alignment approaches reduce accurate alignment time before launching the missiles.
The influence of maneuver on observable degree of state variables are investigated intensively, and the approach of enhancing observable degree of the state variables in Kalman filter is proposed. Furthermore, Increasing maneuver intensity can enhance observable degree of the state variables in Kalman filter is demonstrated in theory, and several approaches of enhancing observable degree of the state variables are presented.
Based on H_∞filtering theory in Krein space, H_∞filter is applied to rapid transfer alignment. The robustness of estimation accuracy of H_∞filter and Kalman filter against uncertain noise is investigated. The study result shows that within a certain range of noise uncertainty, Kalman filter has robustness against uncertain noise, and in accuracy robustness Kalman filter is superior to H_∞filter, but the estimation speed of H_∞filter is superior to Kalman filter. Based on the result, an approach to twice rapid transfer alignment based on H_∞filtering associated with
Kalman filtering is proposed. In the first time alignment, H_∞filter feature being taken advantage of, horizontal alignment is achieved by velocity matching. In the second time alignment, Kalman filter being used, azimuth alignment is achieved by velocity plus attitude change matching. Robust Kalman filter in Krein space is applied to rapid transfer alignment. It is showed that in the case of parameter perturbation, with the equivalent intensity of white noise and the parameters of robust Kalman filter are properly chose, the accuracy robustness of robust Kalman filter is superior to that of standard Kalman filter.
Based on wavelet transform and lifting wavelet transform theory, wavelet filtering and lifting wavelet filtering are applied to rapid transfer alignment. The rapid transfer alignment approaches based on wavelet pre-filtering with batch data and lifting wavelet pre-filtering with batch data are proposed. It is showed that the proposed approaches are very effective.
引文
1 D. Tarrant, C. Roberts, D. Jones et al. Rapid and Robust Transfer Alignment. IEEE Proceedings of Aerospace Control Systems, 1993: 758~762
2 H. A. Jr. Klotz, C. B. Derbak. GPS-aided Navigation and Unaided Navigation on the Joint Direct Attack Munition. IEEE Position Location and Navigation Symposium, 1998: 412~419
3 J. E. Kain, J. R. Cloutier. Rapid Transfer Alignment for Tactical Weapon Applications. AIAA-89-3581
4 K. J. Shortelle, W. R. Graham, C. Rabourn. F-16 Flight Tests of a Rapid Transfer Alignment Procedure. IEEE Position Location and Navigation Symposium. 1998: 379~386
5 W. R. Graham, K. J. Shortelle. Rapid Alignment Prototype (RAP) Flight Test Demonstration. System Dynamics International. 1997, No. ISG97-01: 30
6 W. R. Graham et al. Rapid Alignment Prototype (RAP) Flight test Demonstration. Proceedings of the Institute of Navigation (ION) National Technical Meeting, 1998
7 D. Jones, C. Roberts, D. Tarrant et al. Transfer Alignment Design and Evaluation Environment. IEEE Proceedings of Aerospace Control Systems. 1993: 753~757
8 P. Kim, L. Glaros. Concepts for Payload to Launch Vehicle Transfer Alignment During Boost and Freefall. IEEE Position Location and Navigation Symposium, 1992: 555
9 K. Spalding, S. L. Missouri. An Efficient Rapid Transfer Alignment Filter. AIAA-92-4598
10 You-Chol Lim, Joon Lyou. An Error Compensation Method for Transfer Alignment. Proceedings of IEEE Conference on Electrical and Electronic Technology. TENCON, 2001, Vol.2: 850~855
11 You-Chol Lim, Joon Lyou. Transfer Alignment Error Compensator Design Using H-filter. American Control Conference. 2002: 1460~1465
12 C. C. Ross, T. F. Elbert. A Transfer Alignment Algorithm Study Based on Actual Flight Test Data From a Tactical Air-to-ground Weapon Launch. IEEE Position Location and Navigation Symposium. 1994: 431~438
13 R. M. Rogers. Velocity-plus-rate Matching for Improved Tactical Weapon Rapid Transfer Alignment. AIAA Guidance, Navigation and Control Conference, 1991: 1580~1588
14 F. H. Schlee, N. F. Toda, M. A. Islam et al. Use of an External Cascade Kalman Filter to Improve the Performance of a Global Positioning System (GPS) Inertial Navigator. IEEE Aerospace and Electronics Conference. 1988, Vol.1: 345~350
15 Chun Yang, Ching-Fang Lin, D. Tarrant. Transfer Alignment Design and Evaluation. AIAA-93-3892
16 D. Goshen-Meskin, I. Y. Bar-Itzhack. Observability Analysis of Piece-wise Constant System, Part: Theory. IEEE Transactions on Aerospace and Electronic Systems. 1992, 28(4): 1056~1067
17 D. Goshen-Meskin, I. Y. Bar-Itzhack. Observability Analysis of Piece-wise Constant System, Part: Application to Inertial Navigation In-flight Alignment. IEEE Transactions on Aerospace and Electronic Systems. 1992, 28(4): 1068~1075
18 Boaz Porat, I. Y. Bar-Itzhack. Azimuth Observability Enhancement During INS In-flight Alignment. AIAA Journal of Guidance, Control and Dynamics. 1980, 3(4): 337~344
19 R. M. Rogers. Low Dynamic IMU Alignment. IEEE Position Location and Navigation Symposium. 1998: 272~279
20 Boaz Porat, I. Y. Bar-Itzhack. Effect of Acceleration Switching During INS In-flight Alignment. AIAA Journal of Guidance, Control and Dynamics. 1981, 4(4): 385~389
21 R. B. Miller. A New Strapdown Attitude Algorithm. AIAA Journal of Guidance, Control and Dynamics. 1983, 6(4): 287~291
22 J. G. Lee, Y. J. Yoon, J. D. Mark et al. Extension of Strapdown Attitude Algorithm for High-frequency Base Motion. AIAA Journal of Guidance, Control and Dynamics. 1990, 13(4): 738~743
23 Y. F. Jiang, Y. P. Lin. Improved Strapdown Coning Algorithms. IEEE Transaction on Aerospace and Electronic Systems. 1992, 28(2): 484~490
24 S. P. Dmitriyev, O. A. Stepanov, S. V. Shepel. Nonlinear Filtering Methods Application in INS Alignment. IEEE Transactions on Aerospace and ElectronicSystems. 1997, 33(1): 260~271
25 P. G. Savage. Strapdown Inertial Navigation Integration Algorithm Design, Part Ⅰ: Attitude Algorithms. AIAA Journal of Guidance, Control and Dynamics. 1998, 21(1): 19~28
26 P. G. Savage. Strapdown Inertial Navigation Integration Algorithm Design, PartⅡ: Velocity and Position Algorithm. AIAA Journal of Guidance, Control and Dynamics. 1998, 21(2): 208~221
27 Y. A. Litmanovich, V. M. Lesyuchevsky, V. Z. Gusinsky. Two New Classes of Strapdown Navigation Algorithms. AIAA Journal of Guidance, Control and Dynamics. 2000, 23(1): 34~44
28 K. M. Roscoe. Equivalency between Strapdown Inertial Navigation Coning and Sculling Integrals/Algorithms. AIAA Journal of Guidance, Control and Dynamics. 2001, 24(2): 201~205
29 D. Goshen-Meskin, I. Y. Bar-Itzhack. Unified Approach to Inertial Navigation System Error Modeling. AIAA Journal of Guidance, Control and Dynamics. 1992, 15(3): 648~653
30 R. M. Rogers. Weapon IMU Transfer Alignment Using Aircraft Position From Actual Flight Tests. IEEE Position Location and Navigation Symposium. 1996: 328~335
31 J. Kaiser, G. Beck, S. Berning. Vital Advanced Inertial Network. IEEE Position, Location and Navigation Symposium. 1998: 61~68
32张炎华,程加斌.鲁棒滤波及舰载武器捷联系统初始对准研究.上海交通大学学报, 1997, 31(4): 65~68
33赵伟,袁信,林雪原.采用H∞滤波器的GPS/INS全组合导航系统研究.航空学报, 2002, 23(3): 265~267
34岳晓奎,袁建平.滤波算法及其在GPS/SINS组合导航系统中的应用.航空学报, 2001, 22(4): 366~368 H∞
35白宇骏,徐晓苏,刘国燕.基于博弈论的鲁棒滤波器应用于GPS/INS组合系统的设计研究.中国惯性技术学报, 2003, 11(4): 7~10
36黄华,程向红,万德钧. H∞滤波技术在捷联惯性系统在线校正中的应用.中国惯性技术学报, 2003, 12(1): 10~14
37王艳东,范跃祖.滤波在惯导系统地面快速对准中的应用.北京航空航天大学学报, 2000, 26(5): 516~518 H∞
38聂莉娟,吴俊伟,田炜. H∞滤波及其在惯导初始对准中的应用.中国惯性技术学报, 2003, 11(6): 39~43
39刘立恒,邓正隆.惯导系统初始对准的H∞滤波器设计.中国惯性技术学报, 2003, 11(1): 15~18
40顾冬晴,秦永元.姿态匹配传递对准的H∞滤波器设计.空军工程大学学报, 2005, 6(2): 32~35
41戴邵武,张亦农.基于H∞的双滤波算法在GPS/SINS组合导航系统中的研究.中国惯性技术学报, 2005, 13(5): 39~44
42吴富梅,聂建亮,董海静.基于Elman神经网络和Kalman滤波的捷联惯导精对准.中国惯性技术学报, 2006, 14(5): 9~13
43胡健,周百令,马云峰.鲁棒最小方差滤波在惯导初始对准中的应用研究.舰船电子工程, 2007, 27(2): 76~78
44康国华,刘建业,刘瑞华等.闭环H∞滤波在无源北斗/SINS导航系统中的实现.控制与决策, 2007, 22(5): 566~568
45刘锡祥,徐晓苏,刘建娟等.组合导航中模糊自适应Kalman滤波算法分析.中国惯性技术学报, 2006, 14(3): 31~35
46施航,朱纪洪. GPS/INS组合导航方差配置鲁棒滤波研究.中国惯性技术学报, 2005, 13(5): 33~38
47 S. P. Dmitriyev, O. A. Stipanov, S. V. Shepel. Nonlinear Filtering Methods Application in INS Alignment. IEEE Transactions on Aerospace and Electronic Systems. 1997, 33(1): 260~272
48王丹力,张洪钺.惯导系统初始对准的非线性滤波算法.中国惯性技术学报, 1999, 7(3): 17~21
49 C. Musso, N. Oudjane. Particle Methods For Multimodal Filtering Application to Terrain Navigation. IEE, Savory Place, London, 1999
50 C. Musso, N. Oudjane. Recent Particle Filter Applied to Terrain Navigation. Proceedings of the Third International Conference on Information Fusion, July 2000, Vol. 2: 26~33
51 H. Carvalho, P. D. Moral. Optimal Nonlinear Filtering in GPS/INS Integration. IEEE Trans AES, 1997, 33(3): 835~849
52 B. Azimi-Sadjadi. Approximate Nonlinear Filtering with Applications to Navigation. University of Maryland, 2001
53熊凯,张洪钺.粒子滤波在惯导系统非线性对准中的应用.中国惯性技术学报, 2003, 11(6): 20~26
54 A. Doucet, S. Godsill, C. Andrieu. On Sequential Monte Carlo Sampling Methods for Bayesian Filtering. Statistics and Computing, 2000, 10(3): 197~208
55马孝忠,陈明,刘宗玉.激光捷联贯导系统/地形辅助导航系统中卡尔曼/粒子组合滤波算法设计及仿真.中国惯性技术学报, 2006, 14(1): 41~44
56丁杨斌,王新龙,王缜等. Unscented卡尔曼滤波在SINS静基座大方位失准角初始对准中的应用研究.宇航学报, 2006, 27(6): 1201~1204
57张红梅,邓正隆.一种新的惯性导航初始对准滤波方法.中国惯性技术学报, 2005, 13(1): 1~4
58顾冬晴,秦永元.船用捷联惯导系统运动中对准的UKF设计.系统工程与电子技术, 2006, 28(8): 1218~1220
59陈兵舫,张育林,杨乐平. H∞鲁棒滤波在惯导初始对准中的应用.中国惯性技术学报, 2000, 8(4): 58~62
60雷旭亮,宋金来,周一览.捷联式惯导系统快速初始对准方法研究.中国惯性技术学报, 2005, 13(4): 6~9
61夏恩松,王艳东.直接对准算法及遗传算法在SINS初始对准中的应用研究.宇航学报, 2006, 27(5): 1091~1095
62贺娟,崔平远,陈阳舟等.基于RBF网络的捷联惯导初始对准优化研究.计算机仿真, 2006, 23(4): 30~49
63张传斌,杨宁,田蔚风等.基于多模型估计提高捷联惯导系统初始对准的精度.上海交通大学学报, 2005, 39(9): 1481~1484
64 M. J. Grimble. Design of Optimal Linear Filters. Proc.1987 MTNS, Phoenix, Arizona, June 1987. H∞
65 U. Shaked. -Minimum Error State Estimation of Linear Stationary Process. IEEE Trans. Automatic Control. 1990, 35(5): 554~557 H∞
66 J. C. Doyle, K. Glover, P. P. Khargonekar. State Space Solutions to Standard H &H∞and Control Problems. IEEE Trans. Automatic Control. 1989, 34(8): 831~847
67 M. Fu. Interpolation Approach to H∞Optimal Estimation and Its Interconnection to Loop Transfer Recovery. Sys. Contr. Lett, 1991, 17(1): 29 ~ 36
68 KM. Nagpal, P. P. Khargonekar. Filtering and Smoothing in an H∞Setting.IEEE Trans. Automatic Control, 1991, 36(2): 152~166
69 S. Weiqian, M. N. Krishan, Khargonekar et al. Control and Filtering for Sampled-data Systems. IEEE Trans. Automatic Control. 1993, 38(8): 1162 ~1175 H∞
70 Peng Shi, C. E. de Souza, Lihua Xie. Robust Filtering for Uncertain Systems with Sampled-data Measurements. Proc. 32st IEEE Conf. Decision Control, San Antonio, TX , USA, Dec. 1993, 1: 793~798 H∞
71 Peng Shi. Robust Filtering for Uncertain Sampled-data Systems. International Journal of Systems Science, Dec, 1996, 27 (12): 1403 ~1415
72 Babak Hassibi, Ali H. Sayed, T. Kailath. Linear Estimation in Krein Spaces-Part I: Theory. IEEE Transactions on Automatic Control. 1996, 41(1): 18~33
73 L. Xie, C. E. de Souza, M. Fu. H∞-Estimation for Discrete-time Linear Uncertain Systems. Int. J. Robust. Nolinear Control. 1991, 1(1): 111~123
74 Y. Theodor, Uri Shaked, E. Carlos de Souza. A Game Theory Approach to Robust Discrete-time Estimation. IEEE Transaction on Signal Processing. 1994, 42(6): 1486~1495 H∞
75 P. Pramod Khargonekar, A. Mario Rotea. Mixed Filtering. Proceedings of the 31H 2/ H∞th Conference on Decision and Control. 1992, 2: 2299~2304
76 R. M. Palhares, P. L. D. Peres. LMI Approach to the Mixed H 2/ H∞Filtering Design for Discrete-Time Uncertain Systems. IEEE Transaction on Aerospace and Electronic Systems. 2001, 37(1): 292~296
77 Fuwen Yang, Y. S. Hung. Robust Filtering with Error Variance Constraints for Uncertain Discrete-time Systems. Proceedings of the 2000 IEEE International Conference on Control Application. ALASKA, 2000: 635~640 H∞
78 Zidong Wang, Biao Huang. Robust H2 /H∞Filtering for Linear with Error Variance Constraints. IEEE Trans on Signal Processing. 2000, 48(8): 2463~2467
79 L. Xie, C. Soh, C. E. Souza. Robust Kalman Filtering for Uncertain Discrete-time Systems. IEEE Trans. Autom. Control. 1994, 39(6): 1310~1314
80 Y. Theodor, U. Shaked. Robust Discrete-time Minimum-variance Filtering. IEEE Trans. Signal Process. 1996, 44(2): 181~189
81 X. Zhu, Y. C. Soh, L. Xie. Design and Analysis of Discrete-time Robust Kalman Filters. Automatica. 2002, 38(6): 1069~1077
82 M. Fu, C. E. Souza, Z. Q. Luo. Finite Horizon Robust Kalman Filter Design. IEEE Trans. Signal Process. 2001, 49(9): 2103~2112
83 T. H. Lee, W. S. Ra, T. S. Yoon et al. Robust Kalman Filtering via Krein Space Estimation. IEE Proc.Control Theory Appl. 2004, 151(1): 59~63
84 A. Grossman, J. Morlet. Decomposition of Hardy Functions into Square Integrable Wavelets of Constant Shape. SIAMJ. Math Anal. 1984, 15(4): 723~726
85 I. Daubechies. Orthonormal Bases of Compactly Supported Wavelets. Communications on Pure and Applied Mathematics. 1988, 41(7): 909~1006
86 S. A. Mallat. Theory for Multiresolution Signal Decomposition: the Wavelet Representation. IEEE Trans. Pattern Anal. Machine Intelligence. 1989, 11(7): 673~693
87 A. Cohen, I. Daubechies. Bi-orthogonal Bases of Compactly Supported Wavelets. Communications on Pure and Applied Mathematics. 1992, 45(5): 485~560
88 R. Coifman et al. Entropy Based Algorithm for Best Basis Selection. IEEE Trans. Inform. Theory. 1992, 38(2): 713~718
89 M. V. Wickerhauser. INRIA Lectures on Wavelet Packet Algorithms. Technical report, Washington University, 1991
90 W. Sweldens. The Lifting Scheme: A Custom-design Construction of Biorthogonal Wavelets. Applied and Computation Harmonic Analysis. 1996, 3(2): 186~200
91 W. Sweldens. The Lifting Scheme: A Construction of Second Generation Wavelets. SIAM Journal of Mathematical Analysis. 1998, 29(2): 511~546
92 A. Witkin. Scale Space Filtering. Proc. 8th Int. Joint Conf. Artificial Intelligence. Karlsrube, West Germany, 1983: 1019~1021
93 S. Mallat, W. L. Hwang. Singularty Detection and Processing with Wavelets. IEEE Trans. Inform. Theory. 1992, 38(2): 617~643
94 S. Mallat, S. Zhong. Characterization of Signals from Multiscle Edges. IEEE Trans. Pattern Anal. Machine Intelligence. 1992, 14(7): 710~732
95 Xu Yansun et al. Wavelet Transform Domain Filters: a Spatially Selective NoiseFiltration Technique. IEEE Trans. Image Processing. 1994, 3(6): 747~758
96 D. L. Donoho. De-noising by Soft-thresholding. IEEE Trans. Inform. Theory. 1995, 41(3): 613~627
97刘志成,陈祥光,李宇峰等.传感器输出时间序列的实时小波滤波方法.北京化工大学学报, 2007, 34(1): 71~75
98钱峰,胡光岷.基于滑动时窗的小波变换实时算法.信号处理, 2007, 23(3): 361~364
99李佳,葛军,周起勃.基于小波分析的实时红外系统目标检测的研究与实现.红外技术, 2005, 27(3): 192~195
100都伊林,戴文琪双正交小波提升系数的递推算法与实现.现代电子技术, 2006, 8: 62~65
101郑丽英,熊金涛,李良超等.小波边界处理及实时去噪.雷达科学与技术, 2007, 5(4): 300~303
102杨维,宋国乡,张宪民.一种递归滤波的提升方法.空军工程大学学报, 2005, 6(6): 52~55
103蒋东方,陈明.一种实时小波降噪算法.仪器仪表学报, 2004, 25(6): 781~783
104饶贵安,康宜华,陈龙驹等.一种新的实时小波分析.仪器仪表学报, 2005, 26(2): 181~183
105刘鲁源,李士心,杨晔等.双正交小波在陀螺信号去噪中的应用.信号处理, 2002, 18(4): 386~388
106袁瑞铭,韦锡华,李自怡等.基于小波阈值滤波的光纤陀螺信号消噪算法.中国惯性技术学报, 2003, 11(5): 90~94
107刘镇平,张春熹,王妍.小波分析在捷联惯导陀螺信号滤波中的应用.中国惯性技术学报, 2005, 13(1): 77~80
108吴盘龙,张科,李言俊.多小波在光纤陀螺信号滤波中的应用研究.测控技术, 2005, 24(7): 60~62
109吉训生,王寿荣.小波变换在MEMS陀螺仪去噪声中的应用.传感技术学报, 2006, 19(1): 150~152
110蒋行国,杨文淑,包启亮等.基于小波变换的两种惯性传感器数据融合.光电工程, 2007, 34(1): 90~94
111时伟,吴美平,薛祖瑞.基于小波-Kalman混合滤波的激光陀螺信号处理.兵工自动化, 2005, 24(4): 57~58
112刘建娟,徐晓苏,刘锡祥.基于小波变换的自适应滤波技术在组合导航系统中的应用.中国惯性技术学报, 2005, 13(5): 34~38
113吴富梅,杨元喜.基于小波变换和序贯抗差估计的捷联惯导初始对准.武汉大学学报, 2007, 32(7): 617~620
114时伟,薛祖瑞,吴美平.基于小波检测的捷联惯导系统初始对准抗干扰新方法.中国惯性技术学报, 2005, 13(3): 14~16
115吴富梅,杨元喜.基于小波阈值消噪自适应滤波的GPS/INS组合导航.测绘学报, 2007, 36(2): 124~128
116刘百奇,房建成.一种改进的基于小波神经网络的SINS快速初始对准方法.中国惯性技术学报, 2007, 15(4): 394~397
117高亚楠,陈家斌.基于小波分析的光纤陀螺信号处理.火力与指挥控制, 2005, 30(5): 35~37
118 A. G. Bruce, Gao Hong-Ye. Understanding Waveshirnk: Variance and Bias Estimation. Biometrika, 1996, 83(4): 727~745
119 Gao Hong-Ye, A. G. Bruce. Waveshirnk and Semisoft Shrinkage. StaSci Research Report. 1995, No.39
120 Gao Hong-Ye. Wavelet Shrinkage Denoising Using the Non-negative Garrote. Journal of Computational and Graphical Statistic. 1998, 7(4): 469~488
121潘泉,张磊,孟晋丽等.小波滤波方法及应用.清华大学出版社, 2005:10
122 D. O. Jr. Benson. A Comparison of Two Approaches to Pure-inertial and Doppler-inertial Error Analysis. IEEE Transactions on Aerospace and Electronic Systems. 1975, 11: 447~455
123胡海,张星,刘鼎臣.海射精确制导弹道导弹引发未来海战的深刻变革.导弹与航天运载技术, 2004, 6: 57~60
124 Yi-Yuan Chen, Kuu-young Young. An Intelligent Radar Predictor for High-speed Moving-target Tracking. IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering. 2002, 3:1638~1641
125万德钧,房建成.惯性导航初始对准.东南大学出版社, 1998: 83~106
126 Babak. Hassibi, Ali H. Sayed, T. Kailath. Linear Estimation in Krein Spaces-Part II: Applications. IEEE Transactions on Automatic Control. 1996, 41(1): 34~49
127 A. P. Sage, GW. Husa. Adaptive Filtering with Unknown Prior Statistics. Proceedings of Joint Automatic Control Conference. 1969. 760~769
128张常云.自适应滤波方法研究.航空学报, 1998, 19(7): 96~99
129黄晓瑞,崔平远,崔祜涛. GPS/INS组合导航系统自适应滤波算法与仿真研究.飞行力学, 2001, 19(2): 69~72
130段战胜,韩崇昭,党宏社.一种带未知时变系统噪声水平的目标跟踪滤波器.系统仿真学报, 2004, 16(11): 2591~2593
131邓正隆.惯性技术.哈尔滨工业大学出版社, 2006: 147~177
132刘立恒.鲁棒滤波及其在导航系统中的应用.哈尔滨工业大学工学博士学位论文. 2003: 3~10
133张红梅.非线性滤波及其在姿态确定和导航中的应用.哈尔滨工业大学工学博士学位论文. 2004: 61~64
134陈哲.捷联惯导系统原理.宇航出版社, 1986: 9~161
2 H. A. Jr. Klotz, C. B. Derbak. GPS-aided Navigation and Unaided Navigation on the Joint Direct Attack Munition. IEEE Position Location and Navigation Symposium, 1998: 412~419
3 J. E. Kain, J. R. Cloutier. Rapid Transfer Alignment for Tactical Weapon Applications. AIAA-89-3581
4 K. J. Shortelle, W. R. Graham, C. Rabourn. F-16 Flight Tests of a Rapid Transfer Alignment Procedure. IEEE Position Location and Navigation Symposium. 1998: 379~386
5 W. R. Graham, K. J. Shortelle. Rapid Alignment Prototype (RAP) Flight Test Demonstration. System Dynamics International. 1997, No. ISG97-01: 30
6 W. R. Graham et al. Rapid Alignment Prototype (RAP) Flight test Demonstration. Proceedings of the Institute of Navigation (ION) National Technical Meeting, 1998
7 D. Jones, C. Roberts, D. Tarrant et al. Transfer Alignment Design and Evaluation Environment. IEEE Proceedings of Aerospace Control Systems. 1993: 753~757
8 P. Kim, L. Glaros. Concepts for Payload to Launch Vehicle Transfer Alignment During Boost and Freefall. IEEE Position Location and Navigation Symposium, 1992: 555
9 K. Spalding, S. L. Missouri. An Efficient Rapid Transfer Alignment Filter. AIAA-92-4598
10 You-Chol Lim, Joon Lyou. An Error Compensation Method for Transfer Alignment. Proceedings of IEEE Conference on Electrical and Electronic Technology. TENCON, 2001, Vol.2: 850~855
11 You-Chol Lim, Joon Lyou. Transfer Alignment Error Compensator Design Using H-filter. American Control Conference. 2002: 1460~1465
12 C. C. Ross, T. F. Elbert. A Transfer Alignment Algorithm Study Based on Actual Flight Test Data From a Tactical Air-to-ground Weapon Launch. IEEE Position Location and Navigation Symposium. 1994: 431~438
13 R. M. Rogers. Velocity-plus-rate Matching for Improved Tactical Weapon Rapid Transfer Alignment. AIAA Guidance, Navigation and Control Conference, 1991: 1580~1588
14 F. H. Schlee, N. F. Toda, M. A. Islam et al. Use of an External Cascade Kalman Filter to Improve the Performance of a Global Positioning System (GPS) Inertial Navigator. IEEE Aerospace and Electronics Conference. 1988, Vol.1: 345~350
15 Chun Yang, Ching-Fang Lin, D. Tarrant. Transfer Alignment Design and Evaluation. AIAA-93-3892
16 D. Goshen-Meskin, I. Y. Bar-Itzhack. Observability Analysis of Piece-wise Constant System, Part: Theory. IEEE Transactions on Aerospace and Electronic Systems. 1992, 28(4): 1056~1067
17 D. Goshen-Meskin, I. Y. Bar-Itzhack. Observability Analysis of Piece-wise Constant System, Part: Application to Inertial Navigation In-flight Alignment. IEEE Transactions on Aerospace and Electronic Systems. 1992, 28(4): 1068~1075
18 Boaz Porat, I. Y. Bar-Itzhack. Azimuth Observability Enhancement During INS In-flight Alignment. AIAA Journal of Guidance, Control and Dynamics. 1980, 3(4): 337~344
19 R. M. Rogers. Low Dynamic IMU Alignment. IEEE Position Location and Navigation Symposium. 1998: 272~279
20 Boaz Porat, I. Y. Bar-Itzhack. Effect of Acceleration Switching During INS In-flight Alignment. AIAA Journal of Guidance, Control and Dynamics. 1981, 4(4): 385~389
21 R. B. Miller. A New Strapdown Attitude Algorithm. AIAA Journal of Guidance, Control and Dynamics. 1983, 6(4): 287~291
22 J. G. Lee, Y. J. Yoon, J. D. Mark et al. Extension of Strapdown Attitude Algorithm for High-frequency Base Motion. AIAA Journal of Guidance, Control and Dynamics. 1990, 13(4): 738~743
23 Y. F. Jiang, Y. P. Lin. Improved Strapdown Coning Algorithms. IEEE Transaction on Aerospace and Electronic Systems. 1992, 28(2): 484~490
24 S. P. Dmitriyev, O. A. Stepanov, S. V. Shepel. Nonlinear Filtering Methods Application in INS Alignment. IEEE Transactions on Aerospace and ElectronicSystems. 1997, 33(1): 260~271
25 P. G. Savage. Strapdown Inertial Navigation Integration Algorithm Design, Part Ⅰ: Attitude Algorithms. AIAA Journal of Guidance, Control and Dynamics. 1998, 21(1): 19~28
26 P. G. Savage. Strapdown Inertial Navigation Integration Algorithm Design, PartⅡ: Velocity and Position Algorithm. AIAA Journal of Guidance, Control and Dynamics. 1998, 21(2): 208~221
27 Y. A. Litmanovich, V. M. Lesyuchevsky, V. Z. Gusinsky. Two New Classes of Strapdown Navigation Algorithms. AIAA Journal of Guidance, Control and Dynamics. 2000, 23(1): 34~44
28 K. M. Roscoe. Equivalency between Strapdown Inertial Navigation Coning and Sculling Integrals/Algorithms. AIAA Journal of Guidance, Control and Dynamics. 2001, 24(2): 201~205
29 D. Goshen-Meskin, I. Y. Bar-Itzhack. Unified Approach to Inertial Navigation System Error Modeling. AIAA Journal of Guidance, Control and Dynamics. 1992, 15(3): 648~653
30 R. M. Rogers. Weapon IMU Transfer Alignment Using Aircraft Position From Actual Flight Tests. IEEE Position Location and Navigation Symposium. 1996: 328~335
31 J. Kaiser, G. Beck, S. Berning. Vital Advanced Inertial Network. IEEE Position, Location and Navigation Symposium. 1998: 61~68
32张炎华,程加斌.鲁棒滤波及舰载武器捷联系统初始对准研究.上海交通大学学报, 1997, 31(4): 65~68
33赵伟,袁信,林雪原.采用H∞滤波器的GPS/INS全组合导航系统研究.航空学报, 2002, 23(3): 265~267
34岳晓奎,袁建平.滤波算法及其在GPS/SINS组合导航系统中的应用.航空学报, 2001, 22(4): 366~368 H∞
35白宇骏,徐晓苏,刘国燕.基于博弈论的鲁棒滤波器应用于GPS/INS组合系统的设计研究.中国惯性技术学报, 2003, 11(4): 7~10
36黄华,程向红,万德钧. H∞滤波技术在捷联惯性系统在线校正中的应用.中国惯性技术学报, 2003, 12(1): 10~14
37王艳东,范跃祖.滤波在惯导系统地面快速对准中的应用.北京航空航天大学学报, 2000, 26(5): 516~518 H∞
38聂莉娟,吴俊伟,田炜. H∞滤波及其在惯导初始对准中的应用.中国惯性技术学报, 2003, 11(6): 39~43
39刘立恒,邓正隆.惯导系统初始对准的H∞滤波器设计.中国惯性技术学报, 2003, 11(1): 15~18
40顾冬晴,秦永元.姿态匹配传递对准的H∞滤波器设计.空军工程大学学报, 2005, 6(2): 32~35
41戴邵武,张亦农.基于H∞的双滤波算法在GPS/SINS组合导航系统中的研究.中国惯性技术学报, 2005, 13(5): 39~44
42吴富梅,聂建亮,董海静.基于Elman神经网络和Kalman滤波的捷联惯导精对准.中国惯性技术学报, 2006, 14(5): 9~13
43胡健,周百令,马云峰.鲁棒最小方差滤波在惯导初始对准中的应用研究.舰船电子工程, 2007, 27(2): 76~78
44康国华,刘建业,刘瑞华等.闭环H∞滤波在无源北斗/SINS导航系统中的实现.控制与决策, 2007, 22(5): 566~568
45刘锡祥,徐晓苏,刘建娟等.组合导航中模糊自适应Kalman滤波算法分析.中国惯性技术学报, 2006, 14(3): 31~35
46施航,朱纪洪. GPS/INS组合导航方差配置鲁棒滤波研究.中国惯性技术学报, 2005, 13(5): 33~38
47 S. P. Dmitriyev, O. A. Stipanov, S. V. Shepel. Nonlinear Filtering Methods Application in INS Alignment. IEEE Transactions on Aerospace and Electronic Systems. 1997, 33(1): 260~272
48王丹力,张洪钺.惯导系统初始对准的非线性滤波算法.中国惯性技术学报, 1999, 7(3): 17~21
49 C. Musso, N. Oudjane. Particle Methods For Multimodal Filtering Application to Terrain Navigation. IEE, Savory Place, London, 1999
50 C. Musso, N. Oudjane. Recent Particle Filter Applied to Terrain Navigation. Proceedings of the Third International Conference on Information Fusion, July 2000, Vol. 2: 26~33
51 H. Carvalho, P. D. Moral. Optimal Nonlinear Filtering in GPS/INS Integration. IEEE Trans AES, 1997, 33(3): 835~849
52 B. Azimi-Sadjadi. Approximate Nonlinear Filtering with Applications to Navigation. University of Maryland, 2001
53熊凯,张洪钺.粒子滤波在惯导系统非线性对准中的应用.中国惯性技术学报, 2003, 11(6): 20~26
54 A. Doucet, S. Godsill, C. Andrieu. On Sequential Monte Carlo Sampling Methods for Bayesian Filtering. Statistics and Computing, 2000, 10(3): 197~208
55马孝忠,陈明,刘宗玉.激光捷联贯导系统/地形辅助导航系统中卡尔曼/粒子组合滤波算法设计及仿真.中国惯性技术学报, 2006, 14(1): 41~44
56丁杨斌,王新龙,王缜等. Unscented卡尔曼滤波在SINS静基座大方位失准角初始对准中的应用研究.宇航学报, 2006, 27(6): 1201~1204
57张红梅,邓正隆.一种新的惯性导航初始对准滤波方法.中国惯性技术学报, 2005, 13(1): 1~4
58顾冬晴,秦永元.船用捷联惯导系统运动中对准的UKF设计.系统工程与电子技术, 2006, 28(8): 1218~1220
59陈兵舫,张育林,杨乐平. H∞鲁棒滤波在惯导初始对准中的应用.中国惯性技术学报, 2000, 8(4): 58~62
60雷旭亮,宋金来,周一览.捷联式惯导系统快速初始对准方法研究.中国惯性技术学报, 2005, 13(4): 6~9
61夏恩松,王艳东.直接对准算法及遗传算法在SINS初始对准中的应用研究.宇航学报, 2006, 27(5): 1091~1095
62贺娟,崔平远,陈阳舟等.基于RBF网络的捷联惯导初始对准优化研究.计算机仿真, 2006, 23(4): 30~49
63张传斌,杨宁,田蔚风等.基于多模型估计提高捷联惯导系统初始对准的精度.上海交通大学学报, 2005, 39(9): 1481~1484
64 M. J. Grimble. Design of Optimal Linear Filters. Proc.1987 MTNS, Phoenix, Arizona, June 1987. H∞
65 U. Shaked. -Minimum Error State Estimation of Linear Stationary Process. IEEE Trans. Automatic Control. 1990, 35(5): 554~557 H∞
66 J. C. Doyle, K. Glover, P. P. Khargonekar. State Space Solutions to Standard H &H∞and Control Problems. IEEE Trans. Automatic Control. 1989, 34(8): 831~847
67 M. Fu. Interpolation Approach to H∞Optimal Estimation and Its Interconnection to Loop Transfer Recovery. Sys. Contr. Lett, 1991, 17(1): 29 ~ 36
68 KM. Nagpal, P. P. Khargonekar. Filtering and Smoothing in an H∞Setting.IEEE Trans. Automatic Control, 1991, 36(2): 152~166
69 S. Weiqian, M. N. Krishan, Khargonekar et al. Control and Filtering for Sampled-data Systems. IEEE Trans. Automatic Control. 1993, 38(8): 1162 ~1175 H∞
70 Peng Shi, C. E. de Souza, Lihua Xie. Robust Filtering for Uncertain Systems with Sampled-data Measurements. Proc. 32st IEEE Conf. Decision Control, San Antonio, TX , USA, Dec. 1993, 1: 793~798 H∞
71 Peng Shi. Robust Filtering for Uncertain Sampled-data Systems. International Journal of Systems Science, Dec, 1996, 27 (12): 1403 ~1415
72 Babak Hassibi, Ali H. Sayed, T. Kailath. Linear Estimation in Krein Spaces-Part I: Theory. IEEE Transactions on Automatic Control. 1996, 41(1): 18~33
73 L. Xie, C. E. de Souza, M. Fu. H∞-Estimation for Discrete-time Linear Uncertain Systems. Int. J. Robust. Nolinear Control. 1991, 1(1): 111~123
74 Y. Theodor, Uri Shaked, E. Carlos de Souza. A Game Theory Approach to Robust Discrete-time Estimation. IEEE Transaction on Signal Processing. 1994, 42(6): 1486~1495 H∞
75 P. Pramod Khargonekar, A. Mario Rotea. Mixed Filtering. Proceedings of the 31H 2/ H∞th Conference on Decision and Control. 1992, 2: 2299~2304
76 R. M. Palhares, P. L. D. Peres. LMI Approach to the Mixed H 2/ H∞Filtering Design for Discrete-Time Uncertain Systems. IEEE Transaction on Aerospace and Electronic Systems. 2001, 37(1): 292~296
77 Fuwen Yang, Y. S. Hung. Robust Filtering with Error Variance Constraints for Uncertain Discrete-time Systems. Proceedings of the 2000 IEEE International Conference on Control Application. ALASKA, 2000: 635~640 H∞
78 Zidong Wang, Biao Huang. Robust H2 /H∞Filtering for Linear with Error Variance Constraints. IEEE Trans on Signal Processing. 2000, 48(8): 2463~2467
79 L. Xie, C. Soh, C. E. Souza. Robust Kalman Filtering for Uncertain Discrete-time Systems. IEEE Trans. Autom. Control. 1994, 39(6): 1310~1314
80 Y. Theodor, U. Shaked. Robust Discrete-time Minimum-variance Filtering. IEEE Trans. Signal Process. 1996, 44(2): 181~189
81 X. Zhu, Y. C. Soh, L. Xie. Design and Analysis of Discrete-time Robust Kalman Filters. Automatica. 2002, 38(6): 1069~1077
82 M. Fu, C. E. Souza, Z. Q. Luo. Finite Horizon Robust Kalman Filter Design. IEEE Trans. Signal Process. 2001, 49(9): 2103~2112
83 T. H. Lee, W. S. Ra, T. S. Yoon et al. Robust Kalman Filtering via Krein Space Estimation. IEE Proc.Control Theory Appl. 2004, 151(1): 59~63
84 A. Grossman, J. Morlet. Decomposition of Hardy Functions into Square Integrable Wavelets of Constant Shape. SIAMJ. Math Anal. 1984, 15(4): 723~726
85 I. Daubechies. Orthonormal Bases of Compactly Supported Wavelets. Communications on Pure and Applied Mathematics. 1988, 41(7): 909~1006
86 S. A. Mallat. Theory for Multiresolution Signal Decomposition: the Wavelet Representation. IEEE Trans. Pattern Anal. Machine Intelligence. 1989, 11(7): 673~693
87 A. Cohen, I. Daubechies. Bi-orthogonal Bases of Compactly Supported Wavelets. Communications on Pure and Applied Mathematics. 1992, 45(5): 485~560
88 R. Coifman et al. Entropy Based Algorithm for Best Basis Selection. IEEE Trans. Inform. Theory. 1992, 38(2): 713~718
89 M. V. Wickerhauser. INRIA Lectures on Wavelet Packet Algorithms. Technical report, Washington University, 1991
90 W. Sweldens. The Lifting Scheme: A Custom-design Construction of Biorthogonal Wavelets. Applied and Computation Harmonic Analysis. 1996, 3(2): 186~200
91 W. Sweldens. The Lifting Scheme: A Construction of Second Generation Wavelets. SIAM Journal of Mathematical Analysis. 1998, 29(2): 511~546
92 A. Witkin. Scale Space Filtering. Proc. 8th Int. Joint Conf. Artificial Intelligence. Karlsrube, West Germany, 1983: 1019~1021
93 S. Mallat, W. L. Hwang. Singularty Detection and Processing with Wavelets. IEEE Trans. Inform. Theory. 1992, 38(2): 617~643
94 S. Mallat, S. Zhong. Characterization of Signals from Multiscle Edges. IEEE Trans. Pattern Anal. Machine Intelligence. 1992, 14(7): 710~732
95 Xu Yansun et al. Wavelet Transform Domain Filters: a Spatially Selective NoiseFiltration Technique. IEEE Trans. Image Processing. 1994, 3(6): 747~758
96 D. L. Donoho. De-noising by Soft-thresholding. IEEE Trans. Inform. Theory. 1995, 41(3): 613~627
97刘志成,陈祥光,李宇峰等.传感器输出时间序列的实时小波滤波方法.北京化工大学学报, 2007, 34(1): 71~75
98钱峰,胡光岷.基于滑动时窗的小波变换实时算法.信号处理, 2007, 23(3): 361~364
99李佳,葛军,周起勃.基于小波分析的实时红外系统目标检测的研究与实现.红外技术, 2005, 27(3): 192~195
100都伊林,戴文琪双正交小波提升系数的递推算法与实现.现代电子技术, 2006, 8: 62~65
101郑丽英,熊金涛,李良超等.小波边界处理及实时去噪.雷达科学与技术, 2007, 5(4): 300~303
102杨维,宋国乡,张宪民.一种递归滤波的提升方法.空军工程大学学报, 2005, 6(6): 52~55
103蒋东方,陈明.一种实时小波降噪算法.仪器仪表学报, 2004, 25(6): 781~783
104饶贵安,康宜华,陈龙驹等.一种新的实时小波分析.仪器仪表学报, 2005, 26(2): 181~183
105刘鲁源,李士心,杨晔等.双正交小波在陀螺信号去噪中的应用.信号处理, 2002, 18(4): 386~388
106袁瑞铭,韦锡华,李自怡等.基于小波阈值滤波的光纤陀螺信号消噪算法.中国惯性技术学报, 2003, 11(5): 90~94
107刘镇平,张春熹,王妍.小波分析在捷联惯导陀螺信号滤波中的应用.中国惯性技术学报, 2005, 13(1): 77~80
108吴盘龙,张科,李言俊.多小波在光纤陀螺信号滤波中的应用研究.测控技术, 2005, 24(7): 60~62
109吉训生,王寿荣.小波变换在MEMS陀螺仪去噪声中的应用.传感技术学报, 2006, 19(1): 150~152
110蒋行国,杨文淑,包启亮等.基于小波变换的两种惯性传感器数据融合.光电工程, 2007, 34(1): 90~94
111时伟,吴美平,薛祖瑞.基于小波-Kalman混合滤波的激光陀螺信号处理.兵工自动化, 2005, 24(4): 57~58
112刘建娟,徐晓苏,刘锡祥.基于小波变换的自适应滤波技术在组合导航系统中的应用.中国惯性技术学报, 2005, 13(5): 34~38
113吴富梅,杨元喜.基于小波变换和序贯抗差估计的捷联惯导初始对准.武汉大学学报, 2007, 32(7): 617~620
114时伟,薛祖瑞,吴美平.基于小波检测的捷联惯导系统初始对准抗干扰新方法.中国惯性技术学报, 2005, 13(3): 14~16
115吴富梅,杨元喜.基于小波阈值消噪自适应滤波的GPS/INS组合导航.测绘学报, 2007, 36(2): 124~128
116刘百奇,房建成.一种改进的基于小波神经网络的SINS快速初始对准方法.中国惯性技术学报, 2007, 15(4): 394~397
117高亚楠,陈家斌.基于小波分析的光纤陀螺信号处理.火力与指挥控制, 2005, 30(5): 35~37
118 A. G. Bruce, Gao Hong-Ye. Understanding Waveshirnk: Variance and Bias Estimation. Biometrika, 1996, 83(4): 727~745
119 Gao Hong-Ye, A. G. Bruce. Waveshirnk and Semisoft Shrinkage. StaSci Research Report. 1995, No.39
120 Gao Hong-Ye. Wavelet Shrinkage Denoising Using the Non-negative Garrote. Journal of Computational and Graphical Statistic. 1998, 7(4): 469~488
121潘泉,张磊,孟晋丽等.小波滤波方法及应用.清华大学出版社, 2005:10
122 D. O. Jr. Benson. A Comparison of Two Approaches to Pure-inertial and Doppler-inertial Error Analysis. IEEE Transactions on Aerospace and Electronic Systems. 1975, 11: 447~455
123胡海,张星,刘鼎臣.海射精确制导弹道导弹引发未来海战的深刻变革.导弹与航天运载技术, 2004, 6: 57~60
124 Yi-Yuan Chen, Kuu-young Young. An Intelligent Radar Predictor for High-speed Moving-target Tracking. IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering. 2002, 3:1638~1641
125万德钧,房建成.惯性导航初始对准.东南大学出版社, 1998: 83~106
126 Babak. Hassibi, Ali H. Sayed, T. Kailath. Linear Estimation in Krein Spaces-Part II: Applications. IEEE Transactions on Automatic Control. 1996, 41(1): 34~49
127 A. P. Sage, GW. Husa. Adaptive Filtering with Unknown Prior Statistics. Proceedings of Joint Automatic Control Conference. 1969. 760~769
128张常云.自适应滤波方法研究.航空学报, 1998, 19(7): 96~99
129黄晓瑞,崔平远,崔祜涛. GPS/INS组合导航系统自适应滤波算法与仿真研究.飞行力学, 2001, 19(2): 69~72
130段战胜,韩崇昭,党宏社.一种带未知时变系统噪声水平的目标跟踪滤波器.系统仿真学报, 2004, 16(11): 2591~2593
131邓正隆.惯性技术.哈尔滨工业大学出版社, 2006: 147~177
132刘立恒.鲁棒滤波及其在导航系统中的应用.哈尔滨工业大学工学博士学位论文. 2003: 3~10
133张红梅.非线性滤波及其在姿态确定和导航中的应用.哈尔滨工业大学工学博士学位论文. 2004: 61~64
134陈哲.捷联惯导系统原理.宇航出版社, 1986: 9~161
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