轨道交通线路几何安全状态动态检测技术研究
|
摘要
铁路作为我国最重要的交通运输基础设施,其高效安全的运营对国民经济的发展和人民生命财产的安全具有重要意义。历史数据表明,线路几何尺寸是表征轨道交通安全状态最为重要的参数。随着轨道交通向高速、高密度方向发展,车载式动态检测技术已成为线路几何参数的主要检测手段,其核心是非接触式检测技术和高精度动态测量基准技术。本论文以线路全断面动态检测为例,详细论述了线路几何安全状态的非接触式动态检测和高精度动态测量基准获取的原理方法,为解决轨道交通基础设施线路几何安全状态的动态检测奠定了基础,具有重要的理论和工程实践意义。
论文提出了一种新的基于车路振动模型的惯性基准算法,此算法充分利用了线路、车辆、陀螺仪和加速度计的已知特性,通过KF/UKF滤波算法,大大提高了传统惯性基准的测量精度。仿真数据表明,这种新算法具有收敛性好、实时性高等优点。同时,提出了一种地面辅助的瞬时位置姿态测量方法,此方法利用地面定点固定的反射镜组和车载的激光器及成像检测设备,定点测量出运动车辆相对于地面基准的瞬时位置和角度。基于以上两种新方法,论文提出了车载惯性基准与地面辅助瞬时位置姿态测量相融合的动态基准测量方案,定点修正了传统惯性基准测量随时间漂移的累计误差问题。
最后,论文论述了非接触式的基于光传播时问原理的旋转激光扫描测距传感器应用于线路全断面车载动态测量的基本原理及方法,提出了一种新的基于一维坐标的高精度标定方法,其精度比常规的三维坐标法大大提高。同时,利用文中提出的新惯性基准算法及地面辅助的瞬时位置姿态测量方法,实现了对轨道交通基础设施全断面的高精度动态检测,并在北京地铁5号线、10号线、机场线和京津城际客运专线的全断面限界检测验收工作中得到了应用,取得了较好的效果。
As an important national transportation infrastructure,railway and its traffic safety are of great importance to national economy and people's daily lives.Historical data show that geometries of railway lines are the most important parameters indicating the status of traffic safety.As railway develops toward higher speed and heavier traffic density,on-board kinematical detection methods have become the major means in safety monitoring.Its key technical problems include non-contact detection and high-accuracy referencing technologies for kinematical measurement.The kinematical measurement of complete line-profile is taken as an example in this dissertation and the principles of non-contact detection of line safety and high-accuracy reference acquisition for kinematical measurement are discussed in both theoretical and practical points of view, providing a basic solution for key problems in kinematical detections of railway safety and thus having great significance in both theoretical and practical aspects.
A new algorithm is proposed in the dissertation for inertial referencing based on vehicle-track vibration model.This algorithm utilizes KF/UKF algorithm and makes full use of known features of tracks,vehicles and sensors,resulting in significantly improved measurement accuracy over the traditional inertial referencing system. Numerical simulations show that this new algorithm has advantages of good convergence and real-time processing ability.A ground-assistant position-pose measurement method,with a reflecting mirror set on ground and laser,imaging and detection equipment on board,is also proposed to measure the instantaneous position and angular displacements of a moving rail-guided vehicle with respect to ground referencing points.Based on these two new methods,a kinematical referencing strategy, consisting of both ground-assistant instantaneous position-pose measurement and on-board inertial referencing techniques,is then proposed in the dissertation to provide corrections at fixed points for errors accumulated over time in traditional inertial referencing
Finally,the application principles and methods for propagation-time-based laser scanner used in the field of complete line-profile measurements are studied.A new calibration method based on 1-D coordinates is proposed,with much higher accuracy than traditional 3-D coordinates-based methods.Furthermore,the proposed new methods for inertial referencing and ground-assistant instantaneous position-pose measurement are used to make high-accuracy kinematical measurements for railway infrastructure,and good results are obtained in engineering projects of complete line-profile measurement in Line 5,Line 10 and Airport Line of Beijing Metro and Beijing-Tianjin high-speed railway.
论文提出了一种新的基于车路振动模型的惯性基准算法,此算法充分利用了线路、车辆、陀螺仪和加速度计的已知特性,通过KF/UKF滤波算法,大大提高了传统惯性基准的测量精度。仿真数据表明,这种新算法具有收敛性好、实时性高等优点。同时,提出了一种地面辅助的瞬时位置姿态测量方法,此方法利用地面定点固定的反射镜组和车载的激光器及成像检测设备,定点测量出运动车辆相对于地面基准的瞬时位置和角度。基于以上两种新方法,论文提出了车载惯性基准与地面辅助瞬时位置姿态测量相融合的动态基准测量方案,定点修正了传统惯性基准测量随时间漂移的累计误差问题。
最后,论文论述了非接触式的基于光传播时问原理的旋转激光扫描测距传感器应用于线路全断面车载动态测量的基本原理及方法,提出了一种新的基于一维坐标的高精度标定方法,其精度比常规的三维坐标法大大提高。同时,利用文中提出的新惯性基准算法及地面辅助的瞬时位置姿态测量方法,实现了对轨道交通基础设施全断面的高精度动态检测,并在北京地铁5号线、10号线、机场线和京津城际客运专线的全断面限界检测验收工作中得到了应用,取得了较好的效果。
As an important national transportation infrastructure,railway and its traffic safety are of great importance to national economy and people's daily lives.Historical data show that geometries of railway lines are the most important parameters indicating the status of traffic safety.As railway develops toward higher speed and heavier traffic density,on-board kinematical detection methods have become the major means in safety monitoring.Its key technical problems include non-contact detection and high-accuracy referencing technologies for kinematical measurement.The kinematical measurement of complete line-profile is taken as an example in this dissertation and the principles of non-contact detection of line safety and high-accuracy reference acquisition for kinematical measurement are discussed in both theoretical and practical points of view, providing a basic solution for key problems in kinematical detections of railway safety and thus having great significance in both theoretical and practical aspects.
A new algorithm is proposed in the dissertation for inertial referencing based on vehicle-track vibration model.This algorithm utilizes KF/UKF algorithm and makes full use of known features of tracks,vehicles and sensors,resulting in significantly improved measurement accuracy over the traditional inertial referencing system. Numerical simulations show that this new algorithm has advantages of good convergence and real-time processing ability.A ground-assistant position-pose measurement method,with a reflecting mirror set on ground and laser,imaging and detection equipment on board,is also proposed to measure the instantaneous position and angular displacements of a moving rail-guided vehicle with respect to ground referencing points.Based on these two new methods,a kinematical referencing strategy, consisting of both ground-assistant instantaneous position-pose measurement and on-board inertial referencing techniques,is then proposed in the dissertation to provide corrections at fixed points for errors accumulated over time in traditional inertial referencing
Finally,the application principles and methods for propagation-time-based laser scanner used in the field of complete line-profile measurements are studied.A new calibration method based on 1-D coordinates is proposed,with much higher accuracy than traditional 3-D coordinates-based methods.Furthermore,the proposed new methods for inertial referencing and ground-assistant instantaneous position-pose measurement are used to make high-accuracy kinematical measurements for railway infrastructure,and good results are obtained in engineering projects of complete line-profile measurement in Line 5,Line 10 and Airport Line of Beijing Metro and Beijing-Tianjin high-speed railway.
引文
[1]董希明.机车车辆应用可靠性工程[M].北京:中国铁道出版社,2002.
[2]蒋兆远等.机车安全运行专家系统[M].北京:科学出版社,2005.
[3]方晨.客运列车乘务安全[M].北京:中国铁道出版社,2005.
[4]王凯全等.事故理论与分析技术[M].北京:化学工业出版社,2004.
[5]金龙哲,宋存义.安全科学原理[M].北京:化学工业出版社,2004.
[6]林柏泉等.安全系统工程[M].江苏:中国矿业大学出版社,2005.
[7]邵辉,王凯全.安全心理学[M].北京:化学工业出版社,2004.
[8]FRA.Accident Incident Database[EB/OL].www.safetydata.fra.dot.gov/officeofsafety.
[9]行车事故案例汇编及典型行车事故案例分析[R].铁道部安全检查司,2004.
[10]梁炯筠.锚固与注浆技术手册[M].北京:中国电力出版社,1999.
[11]杜嘉鸿等.地下建筑注浆工程简明手册[M].北京:科学出版社,1992.
[12]综合检测列车国际交流材料汇编[R].铁道部,2005.
[13]客运专线综合检测列车(引进)技术条件[R].铁道部,2006.
[14]赵国堂.客运专线轨道动态检测中应注意的几个技术问题[J].中国铁路,2005,(4):19-21.
[15]邓学通,叶一鸣.准高速轨检车检测原理及应用[M].北京:中国铁道出版社,2004.
[16]柴东明等.GJ-4型轨检车的检测原理[J].铁道建筑,2000,(1):38-39.
[17]杜鹤亭等.安全综合检测车的研制[J].中国铁道科学,2003,24(1):49-53.
[18]小野重亮等.高速轨道检查技术[J].中国铁路,2006,9:50-52.
[19]朱洪涛.弦测法检测轨向不平顺的研究[J].铁道建筑,2005,10:63-64.
[20]朱洪涛.轨检仪弦测法“以小推大”检查轨道轨向不平顺的理论研究[J].铁道学报,2007,29(1):36-40.
[21]杜鹤亭.长波长轨道不平顺检测中的数字滤波方法[J].中国铁道科学,2000,21(4):58-65.
[22]秦至红,宁升安.BJSD-2型激光限界检测仪在隧道施工检测中的应用[J].铁路航测,2002,28(3):43-44.
[23]李元军,陈昭明.便携式线路限界检测仪的设计和实现[J].铁道技术监督,2005,(6):38-39.
[24]高俊强,陶建岳.利用免棱镜全站仪进行地铁隧道断面测量与计算[J].测绘通报,2005(6):41-43.
[25]朱力强.隧道限界检测车图像采集系统的研制[D].北京:北京交通大学,1997.
[26]Talaya J,Alamus R and Bosch E.Integration of a Terrestrial Laser Scanner with GPS/IMU Orientation Sensors[C].ISPRS,2004:12-23.
[27]李儒英,吴积钦,曾明.基于激光测量的地铁限界检测系统[J].都市快轨交通,2007,20(5):70-73.
[28]杨凤春,吴旺青,于国丞.激光扫描在轨道限界检测中的应用[J].现代城市轨道交通,2007(2):31-32.
[29]李忠科等.牙模激光三维扫描仪结构与标定方法研究[J].电子测量与仪器学报,2004,18(2).1096-1101.
[30]Forsyth D A and Forsyth J．计算机视觉—一种现代方法[M]．北京：电子工业出版社,2004．
[31]Draper C S,Wrigley W,Grohe L R.The floating integrating gyro and its application to geometrical stabilization problems on moving bases [J].Aero.Eng.Rev.,1956,15(6):99—105.
[32]Draper C S,Woodbury R B.Geometrical stabilization based on servo driven gimbals and integrating byro units [J].AGARD Symp.Guidance and Control,Venice,Sept.1956.
[33]Darper C S.Inertial Guidance [M].New York:Pergamon,Oxford,1960.
[34]Bortz J E.A new mathematical formulation for strapdown inertial navigation [J].IEEE Transactions on Aerospace and Electronic Systems,1971,7(1):61—66.
[35]Gilmore J P.Modular strapdown guidance unit with embedded microprocessors [J]Journal of Guidance,Control and Dynamics,1980,3(1):201—205.
[36]Miller R B.A new strapdown attitude algorithm [J].Journal of Guidance,Control and Dynamics,1983,6(4):287-291.
[37]Lee J G Yoon Y J.Extension of strapdown attitude algorithm for high-frequency base motion [J].Journal of Guidance,Control and Dynamics,1990,13(4):738-743.
[38]Jian Y E,Lin Y P.Imporved strapdown coning algorithms [J].IEEE Trans.On AES,1992,28(2):484-489.
[39]Musoff H,Murphy J H.Study of strapdown navigation attitude algorithms [J].Journal of Guidance,Control and Dynamics,1995,18(2):287-290.
[40]Savage P G Strapdown inertial navigation integration algorithm design part 1:attitude algorithms [J].Journal of Guidance,Control and Dynamics,1998,21(1):19-28.
[41]Savage P G Strapdown inertial navigation integration algorithm design part 2:velocity and position Algorithms [J].Journal of Guidance,Control and Dynamics,1998,21(2):208-229.
[42]Fenton R E,Melocik G C,and Olson K W.On the steering of automated vehicles:theory and experiment [J].IEEE Trans.Automat.Contr.,1976,21(7):306-315.
[43]Williams D E and Haddad W M.Nonlinear control of roll moment distribution to influence vehicle yaw characteristics [J].IEEE Trans.Contr.Syst.Technol.,1995,3(3):110-116.
[44]Patwardhan S,Tan H S,and Guldner J.A general framework for automatic steering control:system analysis [C].Proc.Amer.Contr.Conf.,1997,3:1598-1602.
[45]Farrell J,Barth M,Galijan R,and Sinko J.GPS/INS based lateral and longitudinal control demonstration:Final report [R].California PATH Res.Rep.,1998.
[46]Sasiadek J Z and Wang Q.Sensor fusion based on fuzzy Kalman filtering for autonomous robot vehicle[C].Proc.1999 IEEE Int.Conf.Robotics and Automation,Detroit,MI,May 1999:2970-2975.
[47]Güvenc B A and Güvenc L.Robust two degree-of-freedom add-on controller design for automatic steering [J].IEEE Trans.Contr.Syst.Technol.,2002,10(1):137—148.
[48]Jose I Hernandez and Chen-Yuan Kuo.Steering Control of Automated Vehicles Using Absolute Positioning GPS and Magnetic Markers [J].IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY,2003,52(1):150-161.
[49]Jose I Hernandez and Chen Yuan Kuo.Lateral Control of Higher Order Nonlinear Vehicle Model in Emergency Maneuvers Using Absolute Positioning GPS and Magnetic Markers [J].IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY,2004,53(2):372-384.
[50]Barshan B and Durrant-Whyte H F.An Inertial Navigation System for Mobile Robot [C]. Proceeding of 1993 IEEE / RSJ International Conference on Intelligent Robots and Systems,Yokohama,Japan,1993:2243-2247.
[51]Barshan B and Durrant-Whyte H.F.Evaluation of a Solid - State Gyroscope for Mobile Robots Application[J].IEEE Transactions on Instrumentation and Measurement,1994,44(1):61-67.
[52]Barshan B and Durrant-Whyte H F.Inertial Navigation Systems for Mobile Robots[J].IEEE Transactions on Robotics and Automation,1995,11(3):328-342.
[53]Borenstein J and Feng L.Gyrodometry:A New Method for Combining Data from Gyros and Odometry in Mobile robots[C].Proceeding of the 1996 IEEE International Conference on Robotics and Automation,Minneapolis,Minnesota,April 1996:423-428.
[54]Borenstein J and Feng L.Measurement and Correction of Systematic odometry Errors in Mobile Robots[J].IEEE Journal of Robotics and Automation,1996,12(6):869-880.
[55]Borenstein J.Experimental Evaluation of the Fiber Optics Gyroscope for Improving Dead-reckoning Accuracy in Mobile Robots[C].Proceeding Of the IEEE International Conference on Robotics and Automation,1998:56-61.
[56]余祖俊,朱力强,赵沽婷.轨道交通线路全断面车载式动态检测系统研究[J].北京交通大学学报,2007,31(6):1-5.
[57]秦永元.惯性导航[M].北京:科学出版社,2006.
[58]邓正隆.惯性技术[M].哈尔滨:哈尔滨工业大学出版社,2006.
[59]Garg V K,Dukkipai R V.Dynamics of railway vehicle system[J].Academic Press,Canada,1984,21(9):102-108.
[60]夏禾,张楠.车辆与结构动力相互作用[M].北京:科学出版社,2005.
[61]翟婉明.车辆-轨道耦合动力学[M].北京:科学出版社,2007.
[62]刘嘉.车桥耦合振动及其智能控制的研究[M].武汉:武汉理工大学,2004:11-14.
[63]罗林,罗文灿等.干线轨道不平顺紧急补修标准的研究[J].中国铁道科学,1990,11(2):1-24.
[64]罗文灿,朱开明,罗林.干线轨道不平顺速度管理标准建议值的研究[J].中国铁道科学,1994,15(1):82-103.
[65]张格明.160km/h线路轨道不平顺管理标准的研究[J].中国铁道科学,1995,16(4):31-41.
[66]蔡成标,婉明,其昌.轨道儿何不平顺安全限值的研究[J].铁道学报,1995,17(4):82-87.
[67]林玉森.轨道不平顺激励下高速铁路桥上列车走行性研究[M].成都:西南交通大学出版社,2001:28-46.
[68]夏学文,谢世浩.用时序分析法建立轨道谱[J].铁道学报,1991,3(9):65-76.
[69]陈果,翟婉明.铁路轨道不平顺随机过程的数值模拟[J].西南交通大学学报,1999,34(2):138-142.
[70]Wiener N.Extrapolation,interpolation,and smoothing of stationary time series with engineering application[M].New York:John Wiley & Sons,1949.
[71]张有为.维纳与卡尔曼滤波理论导论[M].北京:人民教育出版社,1980.
[72]Kalman R E.A new approach to linear filtering and prediction problems[J].Trans.ASME Basic Eng.,1960,82(D):34-35.
[73]Llinas J,Waltz E.Multisensor Data Fusion[M].Norwood,Massachusetts:Artech House,1990.
[74]Hall D L.Mathematical Techniques in Multisensor Data Fusion[M].Boston:Artech House, 1992.
[75]崔平远,黄晓瑞.基于联合卡尔曼滤波的多传感器信息融合算法及其应用[J].电机与控制学报,2001,5(3):204-207.
[76]韩崇昭等.多源信息融合[M].北京:清华大学出版社,2006.
[77]Lawrence R E,Kaufman H.The Kalman filter for the equalization of a digital communication channel[J].IEEE Trans.Commun Technol,1971,19(6):1137-1141.
[78]张友民等.卡尔曼滤波计算方法研究进展[J].控制理论与应用,1995,12(5):17-27.
[79]Chen G.Approximate Kalman Filtering[M].Houston:World Scientific,1993.
[80]张英俊.基于卡尔曼滤波的飞行器定位算法研究[D].哈尔滨:哈尔滨工业大学,2005.
[81]曲寒冰.卡尔曼滤波器在转台测角系统中的应用[D].哈尔滨:哈尔滨工业大学,2003.
[82]陈银溢.微惯性航向姿态系统研究[D].山西:中北大学,2005.
[83]秦永元.卡尔曼滤波与组合导航原理[M].西安:西北工业大学出版社,1998.
[84]Mohinder S G.Application of Kalman filtering to the calibration and alignment of inertial navigation system[J].IEEE Trans.on Automatic Control,1991:14-18.
[85]赵延.机动目标自适应卡尔曼滤波算法研究[D].成都:电子科技大学,2004.
[86]李涛.非线性滤波方法在导航系统中的应用研究[D].长沙:国防科技大学,2003.
[87]Kushner H.Dynamical equations for optimum nonlinear filtering[J].J of Differential Equations,1967,26(3):179-190.
[88]Uhlmann J.Algorithm for multiple target tracking[J].American Science,1992,80(2):128-141.
[89]Sorenson H.Kalman filtering.Theory and application[M].New York:IEEE Press,1985.
[90]Lerro Dar,Shalom Y K.Tracking with Debiased Consistent Converted Measurement vs EKF[J].IEEE Trans.on Aerospace and Electronics Systems,1993,29(3):1015-1022.
[91]Maybeck P S.Stochastic models estimation and control[D].New York:Academic,1982.
[92]Caballero-Gil PFSA.A wide family of nonlinear filter functions with a large linear span[J].Information Sciences,2003,164(124):197-207.
[93]Martinerie F,Forster P.Data association and tracking using hidden Markov models and dynamic programming[D],in Proc.Cone ICASSP,1992.
[94]Rabiner L R.A tutorial on hidden Markov models and selected applications in speech recognition[J].Proc.IEEE,1989,77(2):257-285.
[95]Rabiner L R,Juang B H.An introduction to hidden Markov models[J].IEEE Acoust.Speech,Signal Processing Mag.,1986,3(1):4-16.
[96]Streit RL,Barrett RF.Frequency line tracking using hidden Markov models[J].IEEE Trans.Acoust.,Speech,Signal Processing,1990,38(4):586-598.
[97]Jazwinski AH.Stochastic processes and filtering theory[D].New York:Academic,1970.
[98]Gordon NJ,Salmond DJ,Smith AFM.Novel approach to nonlinear/non-Gaussian Bayesian state estimation[C].IEEE Proc on Radar and Signal Processing,1993,140(2):107-113.
[99]Doucet A,De Freitas A,Gordon N.Sequential monte carlo methods in practice[M].New York:Springer-Verlag,2001.
[100]Arulampalam S,Maskell S,Gordon N.A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking[J].IEEE Trans on Signal Processing,2002,50(2):174-188.
[101]Arulampalam S,Ristic B.Comparison of the particle filter with range parameterized and modified polar EKF for angle-only tracking[C].Proc.SPIE,2000,40(48):288-299.
[102]Doucet A,De Freitas J F G,Gordon N J.An introduction to sequential Monte Carlo methods[M].New York:Springer-Verlag,2001.
[103]Doucet A,Godsill S,and Andrieu C.On sequential Monte Carlo sampling methods for Bayesian filtering[J].Statist.Comput,2000,10(3):197-208.
[104]Gordon N,Salmond D and Smith A F M.Novel approach to nonlinearand non-Gaussian Bayesian state estimation[C].Proc.Inst.Elect.Eng.,F,1993:107-113.
[105]MacCormick J and Blake A.A probabilistic exclusion principle for tracking multiple objects[C].Proc.Int.Conf.Comput.Vision,1999:572-578.
[106]Carpenter J,Clifford P and Fearnhead P.Improved particle filter for nonlinear problems[C].Proc.Inst.Elect.Eng.,Radar,Sonar and Navigation,1999:2-7.
[107]Crisan D,Del Moral P,and Lyons T J.Non-linear filtering using branching and interacting particle systems[J].Markov Processes Related Fields,1999,5(3):293-319.
[108]Del Moral P.Non-linear filtering:Interacting particle solution[J].Markov Processes Related Fields,1999,2(4):555-580.
[109]Kanazawa K,Koller D and Russell S.J.Stochastic simulation algorithmsfor dynamic probabilistic networks[C].Proc.Eleventh Annu.Conf.Uncertainty AI,1995:346-351.
[110]Doucet A.On sequential Monte Carlo methods for Bayesian filtering[D].Dept.Eng.,Univ.Cambridge,UK,Tech.Rep.,1998.
[111]Doucet A,Gordon N and Krishnamurthy V.Particle filters for state estimation of jump Markov linear systems[J].IEEE Trans.Signal Processing,2001,49(2):613-624.
[112]Van der Merwe R,Doucet A,de Freitas J F G and Wan E.The unscented particle filter[C].Adv.Neural Inform.Process.Syst.,Dec.2000:1-45.
[113]Liu J S and Chen R.Sequential Monte Carlo methods for dynamical systems[J].J.Amer.Statist.Assoc,1998,93:1032-1044.
[114]K itagawa G.Monte Carlo filter and smoother for non-Gaussian nonlinear state space models[J].J.Comput.Graph.Statist.,1996,5(1):1-25.
[115]Godsill S,Doucet A and West M.Methodology for Monte Carlo smoothing with application to time-varying autoregressions[C].Proc.Int.Symp.Frontiers Time Series Modeling,2000.
[116]Carlin B P,Poison N G and Stoffer D S.A Monte Carlo approach to nonnormal and nonlinear state-space modeling[J].J.Amer.Statist.Assoc,1992,87(4):493-500.
[117]Gilks W R and Berzuini C.Following a moving target-Monte Carlo inference for dynamic Bayesian models[J].J.R.Statist.Soc.B,2001,63(3):127-146.
[118]Musso C,Oudjane N and LeGland F.Improving regularised particle filters.Sequential Monte Carlo Methods in Practice[M].New York:Springer-Verlag,2001.
[119]Thrun S,Fox D,Burgard W.Robust monte carlo localization for mobile robots[J].Artificial Intelligence,2001.128 (122):99-141.
[120]Doucet A,de Freitas J F G and Gordon N J.An introduction to sequential Monte Carlo methods[M].Sequential Monte Carlo Methods in Practice.New York:Springer-Verlag,2001.
[121]Doucet A,Godsill S and Andrieu C.On sequential Monte Carlo sampling methods for Bayesian filtering[J].Statist.Comput.,2000,10(3):197-208.
[122]Iltis R A.A sequential Monte Carlo filter for joint linear/nonlinear state estimation with application to DS-CDMA[J].IEEE Transactions on Signal Processing,2003,51(2):417-426.
[123]Doucet A,Godsill S and Andrieu C.On sequential Monte Carlo sampling methods for Bayesian filtering[J].Statist.Comput.,2000,10(3):197-208.
[124]Doucet A,Gordon N and Krishnamurthy V.Particle filters for state estimation of jump Markov linear systems[J].IEEE Trans.Signal Processing,2001,49(2):613-624.
[125]Storvik G.Particle filters for state-space models with the presence of unknown static parameters[J].IEEE Trans.Signal Processing,2002,50(1):281-289.
[126]Andrieu C and Doucet A.Particle filtering for partially observed Gaussian state space models[J].J.R.Statist.Soc.,Series B,2002:827-836.
[127]Wan E A and Rudolph van der Menve.The Unscented Kalman Filter for Nonlinear Estimation[C].The Proceedings of IEEE symposium on adaptive systems for signal processing communications and control,Lake Louise,Alberta Canada,2000:153-158.
[128]Van der Merwe R and Wan E.Efficient derivative-free Kalman filters for online learning[C].Proc.Eur.Symp.Artif.Neural Netw.,Bruges,Belgium,2001:205-210.
[129]Julier S J and Uhlmann J K.The scaled unscented transformation[C].Proc.Amer.Control Conf.,2002:4555-4559.
[130]Merwe R and Wan E.The square-root unscented Kalman filter for state and parameter-estimation[C].Proc.IEEE Int.Conf.Acoust.,Speech,and Signal Process,2001,6:3461-3464.
[131]Julier S J and Uhlmann J K.Unscented filtering and nonlinear estimation[C].Proc.IEEE,2004,92(3):401-422.
[132]St-Pierre M and Gingras D.Comparison between the unscented Kalman filter and the extended Kalman filter for the position estimation module of an integrated navigation information system[C].2004 IEEE Intelligent Vehicles Symposium,2004:831-835.
[133]Sarkka S.On Unscented Kalman Filtering for State Estimation of Continuous-Time Nonlinear Systems[J].IEEE Transactions on Automatic Control,2007,52(9):1631-1641.
[134]Hao Yanling,Xiong Zhilan,Feng Sun,Xiaogang Wang.Comparison of Unscented Kalman Filters[C].Mechatronics and Automation,ICMA 2007.International Conference.2007:895 -899.
[135]Julier J and Uhlmann J K.A General Method for Approximating Nonlinear Transformations of Probability Distributions[R].Technical Report,Robotics Research Group,Department of Engineering Science,University of Oxford,1996.
[136]余祖俊,杨娅楠,朱力强.三维激光扫描测量系统标定方法研究[J].电子测量与仪器学报,2007,21(6):31-35.
[137]范志刚,何瑾,许世文,张凤生,桂兵,徐红,邱俊文,董密林.基于全息透镜的风洞天平六自由度测控系统[J].光子学报,2002,31(0Z2):179-184.
[138]范志刚.光电测试技术[M].北京:电子工业出版社,2004.
[139]Sharon S W,James I C,Kevin J S,Walter C D.Optical position measurement for a large gap magnetic suspension system[M].Hampton,Virginia,1994:1-53.
[140]阮晓东,李世伦等.用立体视觉测量多自由度机械装置姿态的研究[J].中国机械工程, 2000,11(5):571-573.
[141]Eui Won Bae,Jong-Ahn Kim,Soo Hyun Kim.Multi-degree-of-freedom displacement measurement system for milli-structures[J].Meas.Sci.Technol.,2001,12(9):1495-1502.
[142]Jong-Ahn Kim,et al.Design methods for six-degree-of-freedom displacement measurement systems using cooperative targets[J].Precion Engineering,2002,26(1):99-104.
[143]赵转萍,吕晓明等.运动目标六自由度单束激光跟踪测量方法研究[J].仪器仪表学报,2001.22(z3):35-37.
[144]FAN K C.A six-degree-of-freedom measurement system for the motion accuracy of linear stages[J].International Journal of Machine Tools and Manufacturing,1998,38(3):155-164.
[145]冯其波.激光多自由度测量方法综述[J].激光与红外,2000,30(6):311-333.
[146]李国顺.激光四光束与PSD测量运动物体瞬时位置姿态系统的研究[J].国防科技大学学报,2000,22(1):69-72.
[147]胡保洁等.基于立体视觉的目标姿态测量技术[J].计算机测量与控制,2007,15(1):27-28.
[148]付旭等.基于EKF的多MEMS传感器姿态测量系统[J].清华大学学报(自然科学版),2006.46(11):1857-1859.
[149]Karatsinides S P.Enhancing filter robustness in cascaded GPS-INS integrations[J].IEEE Transactions on Aerospace and Electronic Systems,1994,30(4):1001-1008.
[150]Carvalho M,Monin A,Salut G.Optimal nonlinear filtering in GPS/INS integration[J].IEEE Transactions on Aerospace and Electronic Systems,1997,33(3):835-850.
[151]Eck C,Geering H L,Bose S C.Model based INS/GPS navigation.Proceedings of the 7th Saint-Petersburg International Conference on Integrated Navigation System[J].Saint Petersburg Russia,2000,29(31):95-102.
[152]余祖俊,赵洁婷,朱力强,卫研研.轨道车辆瞬时姿态的测量方案研究[J].电子测量与仪器学报,2007,21(5):45-48.
[153]Edward P,Owen R,Mitchell,Mark L.Subpixel Measurements Using a Moment-Based Edge Operator[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1989,11(12):1293-1309.
[154]Qurban Memony,Sohaib Khanz.Camera calibration and three-dimensional world reconstruction of stereo-vision using neural networks[J].International Journal of Systems Science,2001,32(9):1155-1159.
[155]宣雷,徐建华.摄像机参数的测定方法与参数估计[J].模式识别与人工智能,1993,6(1):67-70.
[156]丁振良.误差理论及数据处理[M].哈尔滨:哈尔滨工业大学出版社,1987.
[157]中华人民共和国铁路技术管理规程[M],北京:中国铁道出版社,1999.
[158]CJJ96-2003,地铁限界标准[S].北京:中国建筑工业出版社,2003.
[2]蒋兆远等.机车安全运行专家系统[M].北京:科学出版社,2005.
[3]方晨.客运列车乘务安全[M].北京:中国铁道出版社,2005.
[4]王凯全等.事故理论与分析技术[M].北京:化学工业出版社,2004.
[5]金龙哲,宋存义.安全科学原理[M].北京:化学工业出版社,2004.
[6]林柏泉等.安全系统工程[M].江苏:中国矿业大学出版社,2005.
[7]邵辉,王凯全.安全心理学[M].北京:化学工业出版社,2004.
[8]FRA.Accident Incident Database[EB/OL].www.safetydata.fra.dot.gov/officeofsafety.
[9]行车事故案例汇编及典型行车事故案例分析[R].铁道部安全检查司,2004.
[10]梁炯筠.锚固与注浆技术手册[M].北京:中国电力出版社,1999.
[11]杜嘉鸿等.地下建筑注浆工程简明手册[M].北京:科学出版社,1992.
[12]综合检测列车国际交流材料汇编[R].铁道部,2005.
[13]客运专线综合检测列车(引进)技术条件[R].铁道部,2006.
[14]赵国堂.客运专线轨道动态检测中应注意的几个技术问题[J].中国铁路,2005,(4):19-21.
[15]邓学通,叶一鸣.准高速轨检车检测原理及应用[M].北京:中国铁道出版社,2004.
[16]柴东明等.GJ-4型轨检车的检测原理[J].铁道建筑,2000,(1):38-39.
[17]杜鹤亭等.安全综合检测车的研制[J].中国铁道科学,2003,24(1):49-53.
[18]小野重亮等.高速轨道检查技术[J].中国铁路,2006,9:50-52.
[19]朱洪涛.弦测法检测轨向不平顺的研究[J].铁道建筑,2005,10:63-64.
[20]朱洪涛.轨检仪弦测法“以小推大”检查轨道轨向不平顺的理论研究[J].铁道学报,2007,29(1):36-40.
[21]杜鹤亭.长波长轨道不平顺检测中的数字滤波方法[J].中国铁道科学,2000,21(4):58-65.
[22]秦至红,宁升安.BJSD-2型激光限界检测仪在隧道施工检测中的应用[J].铁路航测,2002,28(3):43-44.
[23]李元军,陈昭明.便携式线路限界检测仪的设计和实现[J].铁道技术监督,2005,(6):38-39.
[24]高俊强,陶建岳.利用免棱镜全站仪进行地铁隧道断面测量与计算[J].测绘通报,2005(6):41-43.
[25]朱力强.隧道限界检测车图像采集系统的研制[D].北京:北京交通大学,1997.
[26]Talaya J,Alamus R and Bosch E.Integration of a Terrestrial Laser Scanner with GPS/IMU Orientation Sensors[C].ISPRS,2004:12-23.
[27]李儒英,吴积钦,曾明.基于激光测量的地铁限界检测系统[J].都市快轨交通,2007,20(5):70-73.
[28]杨凤春,吴旺青,于国丞.激光扫描在轨道限界检测中的应用[J].现代城市轨道交通,2007(2):31-32.
[29]李忠科等.牙模激光三维扫描仪结构与标定方法研究[J].电子测量与仪器学报,2004,18(2).1096-1101.
[30]Forsyth D A and Forsyth J．计算机视觉—一种现代方法[M]．北京：电子工业出版社,2004．
[31]Draper C S,Wrigley W,Grohe L R.The floating integrating gyro and its application to geometrical stabilization problems on moving bases [J].Aero.Eng.Rev.,1956,15(6):99—105.
[32]Draper C S,Woodbury R B.Geometrical stabilization based on servo driven gimbals and integrating byro units [J].AGARD Symp.Guidance and Control,Venice,Sept.1956.
[33]Darper C S.Inertial Guidance [M].New York:Pergamon,Oxford,1960.
[34]Bortz J E.A new mathematical formulation for strapdown inertial navigation [J].IEEE Transactions on Aerospace and Electronic Systems,1971,7(1):61—66.
[35]Gilmore J P.Modular strapdown guidance unit with embedded microprocessors [J]Journal of Guidance,Control and Dynamics,1980,3(1):201—205.
[36]Miller R B.A new strapdown attitude algorithm [J].Journal of Guidance,Control and Dynamics,1983,6(4):287-291.
[37]Lee J G Yoon Y J.Extension of strapdown attitude algorithm for high-frequency base motion [J].Journal of Guidance,Control and Dynamics,1990,13(4):738-743.
[38]Jian Y E,Lin Y P.Imporved strapdown coning algorithms [J].IEEE Trans.On AES,1992,28(2):484-489.
[39]Musoff H,Murphy J H.Study of strapdown navigation attitude algorithms [J].Journal of Guidance,Control and Dynamics,1995,18(2):287-290.
[40]Savage P G Strapdown inertial navigation integration algorithm design part 1:attitude algorithms [J].Journal of Guidance,Control and Dynamics,1998,21(1):19-28.
[41]Savage P G Strapdown inertial navigation integration algorithm design part 2:velocity and position Algorithms [J].Journal of Guidance,Control and Dynamics,1998,21(2):208-229.
[42]Fenton R E,Melocik G C,and Olson K W.On the steering of automated vehicles:theory and experiment [J].IEEE Trans.Automat.Contr.,1976,21(7):306-315.
[43]Williams D E and Haddad W M.Nonlinear control of roll moment distribution to influence vehicle yaw characteristics [J].IEEE Trans.Contr.Syst.Technol.,1995,3(3):110-116.
[44]Patwardhan S,Tan H S,and Guldner J.A general framework for automatic steering control:system analysis [C].Proc.Amer.Contr.Conf.,1997,3:1598-1602.
[45]Farrell J,Barth M,Galijan R,and Sinko J.GPS/INS based lateral and longitudinal control demonstration:Final report [R].California PATH Res.Rep.,1998.
[46]Sasiadek J Z and Wang Q.Sensor fusion based on fuzzy Kalman filtering for autonomous robot vehicle[C].Proc.1999 IEEE Int.Conf.Robotics and Automation,Detroit,MI,May 1999:2970-2975.
[47]Güvenc B A and Güvenc L.Robust two degree-of-freedom add-on controller design for automatic steering [J].IEEE Trans.Contr.Syst.Technol.,2002,10(1):137—148.
[48]Jose I Hernandez and Chen-Yuan Kuo.Steering Control of Automated Vehicles Using Absolute Positioning GPS and Magnetic Markers [J].IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY,2003,52(1):150-161.
[49]Jose I Hernandez and Chen Yuan Kuo.Lateral Control of Higher Order Nonlinear Vehicle Model in Emergency Maneuvers Using Absolute Positioning GPS and Magnetic Markers [J].IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY,2004,53(2):372-384.
[50]Barshan B and Durrant-Whyte H F.An Inertial Navigation System for Mobile Robot [C]. Proceeding of 1993 IEEE / RSJ International Conference on Intelligent Robots and Systems,Yokohama,Japan,1993:2243-2247.
[51]Barshan B and Durrant-Whyte H.F.Evaluation of a Solid - State Gyroscope for Mobile Robots Application[J].IEEE Transactions on Instrumentation and Measurement,1994,44(1):61-67.
[52]Barshan B and Durrant-Whyte H F.Inertial Navigation Systems for Mobile Robots[J].IEEE Transactions on Robotics and Automation,1995,11(3):328-342.
[53]Borenstein J and Feng L.Gyrodometry:A New Method for Combining Data from Gyros and Odometry in Mobile robots[C].Proceeding of the 1996 IEEE International Conference on Robotics and Automation,Minneapolis,Minnesota,April 1996:423-428.
[54]Borenstein J and Feng L.Measurement and Correction of Systematic odometry Errors in Mobile Robots[J].IEEE Journal of Robotics and Automation,1996,12(6):869-880.
[55]Borenstein J.Experimental Evaluation of the Fiber Optics Gyroscope for Improving Dead-reckoning Accuracy in Mobile Robots[C].Proceeding Of the IEEE International Conference on Robotics and Automation,1998:56-61.
[56]余祖俊,朱力强,赵沽婷.轨道交通线路全断面车载式动态检测系统研究[J].北京交通大学学报,2007,31(6):1-5.
[57]秦永元.惯性导航[M].北京:科学出版社,2006.
[58]邓正隆.惯性技术[M].哈尔滨:哈尔滨工业大学出版社,2006.
[59]Garg V K,Dukkipai R V.Dynamics of railway vehicle system[J].Academic Press,Canada,1984,21(9):102-108.
[60]夏禾,张楠.车辆与结构动力相互作用[M].北京:科学出版社,2005.
[61]翟婉明.车辆-轨道耦合动力学[M].北京:科学出版社,2007.
[62]刘嘉.车桥耦合振动及其智能控制的研究[M].武汉:武汉理工大学,2004:11-14.
[63]罗林,罗文灿等.干线轨道不平顺紧急补修标准的研究[J].中国铁道科学,1990,11(2):1-24.
[64]罗文灿,朱开明,罗林.干线轨道不平顺速度管理标准建议值的研究[J].中国铁道科学,1994,15(1):82-103.
[65]张格明.160km/h线路轨道不平顺管理标准的研究[J].中国铁道科学,1995,16(4):31-41.
[66]蔡成标,婉明,其昌.轨道儿何不平顺安全限值的研究[J].铁道学报,1995,17(4):82-87.
[67]林玉森.轨道不平顺激励下高速铁路桥上列车走行性研究[M].成都:西南交通大学出版社,2001:28-46.
[68]夏学文,谢世浩.用时序分析法建立轨道谱[J].铁道学报,1991,3(9):65-76.
[69]陈果,翟婉明.铁路轨道不平顺随机过程的数值模拟[J].西南交通大学学报,1999,34(2):138-142.
[70]Wiener N.Extrapolation,interpolation,and smoothing of stationary time series with engineering application[M].New York:John Wiley & Sons,1949.
[71]张有为.维纳与卡尔曼滤波理论导论[M].北京:人民教育出版社,1980.
[72]Kalman R E.A new approach to linear filtering and prediction problems[J].Trans.ASME Basic Eng.,1960,82(D):34-35.
[73]Llinas J,Waltz E.Multisensor Data Fusion[M].Norwood,Massachusetts:Artech House,1990.
[74]Hall D L.Mathematical Techniques in Multisensor Data Fusion[M].Boston:Artech House, 1992.
[75]崔平远,黄晓瑞.基于联合卡尔曼滤波的多传感器信息融合算法及其应用[J].电机与控制学报,2001,5(3):204-207.
[76]韩崇昭等.多源信息融合[M].北京:清华大学出版社,2006.
[77]Lawrence R E,Kaufman H.The Kalman filter for the equalization of a digital communication channel[J].IEEE Trans.Commun Technol,1971,19(6):1137-1141.
[78]张友民等.卡尔曼滤波计算方法研究进展[J].控制理论与应用,1995,12(5):17-27.
[79]Chen G.Approximate Kalman Filtering[M].Houston:World Scientific,1993.
[80]张英俊.基于卡尔曼滤波的飞行器定位算法研究[D].哈尔滨:哈尔滨工业大学,2005.
[81]曲寒冰.卡尔曼滤波器在转台测角系统中的应用[D].哈尔滨:哈尔滨工业大学,2003.
[82]陈银溢.微惯性航向姿态系统研究[D].山西:中北大学,2005.
[83]秦永元.卡尔曼滤波与组合导航原理[M].西安:西北工业大学出版社,1998.
[84]Mohinder S G.Application of Kalman filtering to the calibration and alignment of inertial navigation system[J].IEEE Trans.on Automatic Control,1991:14-18.
[85]赵延.机动目标自适应卡尔曼滤波算法研究[D].成都:电子科技大学,2004.
[86]李涛.非线性滤波方法在导航系统中的应用研究[D].长沙:国防科技大学,2003.
[87]Kushner H.Dynamical equations for optimum nonlinear filtering[J].J of Differential Equations,1967,26(3):179-190.
[88]Uhlmann J.Algorithm for multiple target tracking[J].American Science,1992,80(2):128-141.
[89]Sorenson H.Kalman filtering.Theory and application[M].New York:IEEE Press,1985.
[90]Lerro Dar,Shalom Y K.Tracking with Debiased Consistent Converted Measurement vs EKF[J].IEEE Trans.on Aerospace and Electronics Systems,1993,29(3):1015-1022.
[91]Maybeck P S.Stochastic models estimation and control[D].New York:Academic,1982.
[92]Caballero-Gil PFSA.A wide family of nonlinear filter functions with a large linear span[J].Information Sciences,2003,164(124):197-207.
[93]Martinerie F,Forster P.Data association and tracking using hidden Markov models and dynamic programming[D],in Proc.Cone ICASSP,1992.
[94]Rabiner L R.A tutorial on hidden Markov models and selected applications in speech recognition[J].Proc.IEEE,1989,77(2):257-285.
[95]Rabiner L R,Juang B H.An introduction to hidden Markov models[J].IEEE Acoust.Speech,Signal Processing Mag.,1986,3(1):4-16.
[96]Streit RL,Barrett RF.Frequency line tracking using hidden Markov models[J].IEEE Trans.Acoust.,Speech,Signal Processing,1990,38(4):586-598.
[97]Jazwinski AH.Stochastic processes and filtering theory[D].New York:Academic,1970.
[98]Gordon NJ,Salmond DJ,Smith AFM.Novel approach to nonlinear/non-Gaussian Bayesian state estimation[C].IEEE Proc on Radar and Signal Processing,1993,140(2):107-113.
[99]Doucet A,De Freitas A,Gordon N.Sequential monte carlo methods in practice[M].New York:Springer-Verlag,2001.
[100]Arulampalam S,Maskell S,Gordon N.A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking[J].IEEE Trans on Signal Processing,2002,50(2):174-188.
[101]Arulampalam S,Ristic B.Comparison of the particle filter with range parameterized and modified polar EKF for angle-only tracking[C].Proc.SPIE,2000,40(48):288-299.
[102]Doucet A,De Freitas J F G,Gordon N J.An introduction to sequential Monte Carlo methods[M].New York:Springer-Verlag,2001.
[103]Doucet A,Godsill S,and Andrieu C.On sequential Monte Carlo sampling methods for Bayesian filtering[J].Statist.Comput,2000,10(3):197-208.
[104]Gordon N,Salmond D and Smith A F M.Novel approach to nonlinearand non-Gaussian Bayesian state estimation[C].Proc.Inst.Elect.Eng.,F,1993:107-113.
[105]MacCormick J and Blake A.A probabilistic exclusion principle for tracking multiple objects[C].Proc.Int.Conf.Comput.Vision,1999:572-578.
[106]Carpenter J,Clifford P and Fearnhead P.Improved particle filter for nonlinear problems[C].Proc.Inst.Elect.Eng.,Radar,Sonar and Navigation,1999:2-7.
[107]Crisan D,Del Moral P,and Lyons T J.Non-linear filtering using branching and interacting particle systems[J].Markov Processes Related Fields,1999,5(3):293-319.
[108]Del Moral P.Non-linear filtering:Interacting particle solution[J].Markov Processes Related Fields,1999,2(4):555-580.
[109]Kanazawa K,Koller D and Russell S.J.Stochastic simulation algorithmsfor dynamic probabilistic networks[C].Proc.Eleventh Annu.Conf.Uncertainty AI,1995:346-351.
[110]Doucet A.On sequential Monte Carlo methods for Bayesian filtering[D].Dept.Eng.,Univ.Cambridge,UK,Tech.Rep.,1998.
[111]Doucet A,Gordon N and Krishnamurthy V.Particle filters for state estimation of jump Markov linear systems[J].IEEE Trans.Signal Processing,2001,49(2):613-624.
[112]Van der Merwe R,Doucet A,de Freitas J F G and Wan E.The unscented particle filter[C].Adv.Neural Inform.Process.Syst.,Dec.2000:1-45.
[113]Liu J S and Chen R.Sequential Monte Carlo methods for dynamical systems[J].J.Amer.Statist.Assoc,1998,93:1032-1044.
[114]K itagawa G.Monte Carlo filter and smoother for non-Gaussian nonlinear state space models[J].J.Comput.Graph.Statist.,1996,5(1):1-25.
[115]Godsill S,Doucet A and West M.Methodology for Monte Carlo smoothing with application to time-varying autoregressions[C].Proc.Int.Symp.Frontiers Time Series Modeling,2000.
[116]Carlin B P,Poison N G and Stoffer D S.A Monte Carlo approach to nonnormal and nonlinear state-space modeling[J].J.Amer.Statist.Assoc,1992,87(4):493-500.
[117]Gilks W R and Berzuini C.Following a moving target-Monte Carlo inference for dynamic Bayesian models[J].J.R.Statist.Soc.B,2001,63(3):127-146.
[118]Musso C,Oudjane N and LeGland F.Improving regularised particle filters.Sequential Monte Carlo Methods in Practice[M].New York:Springer-Verlag,2001.
[119]Thrun S,Fox D,Burgard W.Robust monte carlo localization for mobile robots[J].Artificial Intelligence,2001.128 (122):99-141.
[120]Doucet A,de Freitas J F G and Gordon N J.An introduction to sequential Monte Carlo methods[M].Sequential Monte Carlo Methods in Practice.New York:Springer-Verlag,2001.
[121]Doucet A,Godsill S and Andrieu C.On sequential Monte Carlo sampling methods for Bayesian filtering[J].Statist.Comput.,2000,10(3):197-208.
[122]Iltis R A.A sequential Monte Carlo filter for joint linear/nonlinear state estimation with application to DS-CDMA[J].IEEE Transactions on Signal Processing,2003,51(2):417-426.
[123]Doucet A,Godsill S and Andrieu C.On sequential Monte Carlo sampling methods for Bayesian filtering[J].Statist.Comput.,2000,10(3):197-208.
[124]Doucet A,Gordon N and Krishnamurthy V.Particle filters for state estimation of jump Markov linear systems[J].IEEE Trans.Signal Processing,2001,49(2):613-624.
[125]Storvik G.Particle filters for state-space models with the presence of unknown static parameters[J].IEEE Trans.Signal Processing,2002,50(1):281-289.
[126]Andrieu C and Doucet A.Particle filtering for partially observed Gaussian state space models[J].J.R.Statist.Soc.,Series B,2002:827-836.
[127]Wan E A and Rudolph van der Menve.The Unscented Kalman Filter for Nonlinear Estimation[C].The Proceedings of IEEE symposium on adaptive systems for signal processing communications and control,Lake Louise,Alberta Canada,2000:153-158.
[128]Van der Merwe R and Wan E.Efficient derivative-free Kalman filters for online learning[C].Proc.Eur.Symp.Artif.Neural Netw.,Bruges,Belgium,2001:205-210.
[129]Julier S J and Uhlmann J K.The scaled unscented transformation[C].Proc.Amer.Control Conf.,2002:4555-4559.
[130]Merwe R and Wan E.The square-root unscented Kalman filter for state and parameter-estimation[C].Proc.IEEE Int.Conf.Acoust.,Speech,and Signal Process,2001,6:3461-3464.
[131]Julier S J and Uhlmann J K.Unscented filtering and nonlinear estimation[C].Proc.IEEE,2004,92(3):401-422.
[132]St-Pierre M and Gingras D.Comparison between the unscented Kalman filter and the extended Kalman filter for the position estimation module of an integrated navigation information system[C].2004 IEEE Intelligent Vehicles Symposium,2004:831-835.
[133]Sarkka S.On Unscented Kalman Filtering for State Estimation of Continuous-Time Nonlinear Systems[J].IEEE Transactions on Automatic Control,2007,52(9):1631-1641.
[134]Hao Yanling,Xiong Zhilan,Feng Sun,Xiaogang Wang.Comparison of Unscented Kalman Filters[C].Mechatronics and Automation,ICMA 2007.International Conference.2007:895 -899.
[135]Julier J and Uhlmann J K.A General Method for Approximating Nonlinear Transformations of Probability Distributions[R].Technical Report,Robotics Research Group,Department of Engineering Science,University of Oxford,1996.
[136]余祖俊,杨娅楠,朱力强.三维激光扫描测量系统标定方法研究[J].电子测量与仪器学报,2007,21(6):31-35.
[137]范志刚,何瑾,许世文,张凤生,桂兵,徐红,邱俊文,董密林.基于全息透镜的风洞天平六自由度测控系统[J].光子学报,2002,31(0Z2):179-184.
[138]范志刚.光电测试技术[M].北京:电子工业出版社,2004.
[139]Sharon S W,James I C,Kevin J S,Walter C D.Optical position measurement for a large gap magnetic suspension system[M].Hampton,Virginia,1994:1-53.
[140]阮晓东,李世伦等.用立体视觉测量多自由度机械装置姿态的研究[J].中国机械工程, 2000,11(5):571-573.
[141]Eui Won Bae,Jong-Ahn Kim,Soo Hyun Kim.Multi-degree-of-freedom displacement measurement system for milli-structures[J].Meas.Sci.Technol.,2001,12(9):1495-1502.
[142]Jong-Ahn Kim,et al.Design methods for six-degree-of-freedom displacement measurement systems using cooperative targets[J].Precion Engineering,2002,26(1):99-104.
[143]赵转萍,吕晓明等.运动目标六自由度单束激光跟踪测量方法研究[J].仪器仪表学报,2001.22(z3):35-37.
[144]FAN K C.A six-degree-of-freedom measurement system for the motion accuracy of linear stages[J].International Journal of Machine Tools and Manufacturing,1998,38(3):155-164.
[145]冯其波.激光多自由度测量方法综述[J].激光与红外,2000,30(6):311-333.
[146]李国顺.激光四光束与PSD测量运动物体瞬时位置姿态系统的研究[J].国防科技大学学报,2000,22(1):69-72.
[147]胡保洁等.基于立体视觉的目标姿态测量技术[J].计算机测量与控制,2007,15(1):27-28.
[148]付旭等.基于EKF的多MEMS传感器姿态测量系统[J].清华大学学报(自然科学版),2006.46(11):1857-1859.
[149]Karatsinides S P.Enhancing filter robustness in cascaded GPS-INS integrations[J].IEEE Transactions on Aerospace and Electronic Systems,1994,30(4):1001-1008.
[150]Carvalho M,Monin A,Salut G.Optimal nonlinear filtering in GPS/INS integration[J].IEEE Transactions on Aerospace and Electronic Systems,1997,33(3):835-850.
[151]Eck C,Geering H L,Bose S C.Model based INS/GPS navigation.Proceedings of the 7th Saint-Petersburg International Conference on Integrated Navigation System[J].Saint Petersburg Russia,2000,29(31):95-102.
[152]余祖俊,赵洁婷,朱力强,卫研研.轨道车辆瞬时姿态的测量方案研究[J].电子测量与仪器学报,2007,21(5):45-48.
[153]Edward P,Owen R,Mitchell,Mark L.Subpixel Measurements Using a Moment-Based Edge Operator[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1989,11(12):1293-1309.
[154]Qurban Memony,Sohaib Khanz.Camera calibration and three-dimensional world reconstruction of stereo-vision using neural networks[J].International Journal of Systems Science,2001,32(9):1155-1159.
[155]宣雷,徐建华.摄像机参数的测定方法与参数估计[J].模式识别与人工智能,1993,6(1):67-70.
[156]丁振良.误差理论及数据处理[M].哈尔滨:哈尔滨工业大学出版社,1987.
[157]中华人民共和国铁路技术管理规程[M],北京:中国铁道出版社,1999.
[158]CJJ96-2003,地铁限界标准[S].北京:中国建筑工业出版社,2003.