多传感器信息融合技术
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摘要
系统地介绍了多传感器信息融合技术的理论、模型和应用,并对多传感器信息融合的几种主要算法进行了全面的阐述和归纳,指出了信息融合研究中存在的主要问题,最后对信息融合技术的未来研究方向进行了展望。
The information fusion theory,and the model and applications of multi-sensor information fusion(MSIF) technique are introduced systematically in this paper.Main fusion algorithms are also discussed.Problems in the study of MSIF are pointed out and the development trends of MISF are predicted.
The information fusion theory,and the model and applications of multi-sensor information fusion(MSIF) technique are introduced systematically in this paper.Main fusion algorithms are also discussed.Problems in the study of MSIF are pointed out and the development trends of MISF are predicted.
引文
[1]周芳,韩立岩.多传感器信息融合技术综述[J].遥测遥控,2006,27(3):1-7
[2]臧大进.多传感器信息融合技术综述[J].工矿自动化,2005,6:30-32
[3]WALTZ E,BUEDE D M.Data fusion and decisionsupport for command and control[J].IEEE Trans on Syst,Man & Cybern,1986,16(6):865-879.
[4]COMPARATO V G.Fusion—The key to tactical mis-sion success[J].SPIE,1988,93(1):2-7.
[5]HAMILTON M K,KIPP T A.ATR architecture formultisensor fusion[J].SPIE,1996,275(5):126-133.
[6]王仲民,岳宏,刘继岩.移动机器人多传感器信息融合技术述评[J].传感器技术2005,24(4)5-7
[7]NEIRA J,TARDOS J D,Horn J et al.Fusing rangeand intensity image for mobile robot localization[J].IEEE Transon Robot Autom,1999,15(1):76-84.
[8]HERNANDEZ A I,GARRAULT G,MORA F et al.Multisensor fusion for atrial and ventricular activity detection incoronary care monitoring[J].IEEE Trans on Biomed Eng,1999,46(10):1186-1190.
[9]MURPHY R R.Sensor and information fusion forimproved vision-based veh icle guidance[J].IEEE Expert,1998,13(6):49-56.
[10]李圣怡,吴学忠,范大鹏.多传感器融合理论及在智能制造系统中的应用[M].长沙:国防科技大学出版社,1998.
[11]马平,吕锋等.多传感器信息融合基本原理及应用[J].控制工程,2006,13(1):48-51
[12]何友等.多传感器数据融合模型综述[J].清华大学学报.1996,36(9):14-20
[13]DAVID L HALL.An introduction to multisensor fusion[C].International workshop on data fusion in 2002,Beijing,China,2002
[14]王军,苏剑波,席裕庚.多传感器融合综述[J].数据采集与处理.2004,19(1):72-76
[15]VALET,L,MAURIS G and et al A Statistical Over-view of Recent Literature in Information Fusion[G].ISIF2000:Moc3-22-Moc3-29
[16]付华等.基于Bayes估计理论的数据融合方法[J].自动化技术与应用,2005,4(24):10-12
[17]DAVISON A J,NOBUYUKI K.3D Simultaneouslocalization and map building using active vision for a robotmoving on undulating terrain[C].Proceedings of the IEEEInternational Conference on Computer Vision and Recognization.USA:Hawaii,2001,384-389.
[18]李洪波.自适应Kalman滤波在多传感器数据融合中应用[J].国外电子测量技术,2006(6):69-71
[19]DON LERRO,BAR-SHALOM Y.Tracking withdebiased consistent converted measurements versus EKF[J].IEEETrans.on AES,1993,29(3):1015-1022
[20]MO L,SONG X,ZHOU Y,SUN Z,Bar-Shalom Y.Unbiased converted measurements for tracking[J].IEEE Trans.on AES,1998,34(3):1023-1027
[21]DOUCET A.et al.Particle filters for State Estimationof Jump Markov Linear Systems[J].IEEE Trans.On Signal Processing,March 2001,49(3):613-624.
[22]JULIER S J,JEFFERY K.UHLMANN.A Consistent,Debiased Method for Converting Between Polar and Cartesian Coordinate Systems[C].Proceedings of SPIE:Acquisition,Track-ing,and Pointing XI,1997:110-121.
[23]刘素一,张海霞等.基于小波变换和Kalman滤波的多传感器数据融合[J].传感器与仪器仪表.2006,22(6-1),179-181.
[24]FIXSEN D,MAHLER R.The modified Dempster-Shaferapp roach to Classification[J].IEEE Transaction on Systems Manand Cybernetics,1997,27(1):96-104.
[25]SASIADEK J Z.SENSOR FUSION.Annual Reviewsin Control.2002,26:203-228.
[2 6]郭丽梅,罗大庸.基于模糊神经网络的多传感器自适应融合[J].系统工程与电子技术,2004,26(2):215-218
[2 7]杨鹃,孙华等.模糊神经网络信息融合方法在机器人避障中的应用[J].自动化技术与应用,2005,24(2):22-24
[2 8]付华,孙树生等.基于模糊神经网络的信息融合方法在矿井供风系统中的应用[J],煤炭学报,2006,31(2):264-267
[29]李强,杨晓京,魏岚.基于神经网络信息融合的智能机器人[J].机电工程技术,2006,35(6).
[30]E.E.OSUNA,R.FREUND,F.GIROSI..Support vectormachine training and applications,Technical Report[R].Massa-chusetts Institute of Technology,Artificial Intelligence Laboratory,AI Memo No.1602,1997.
[31]张学工.关于统计学习理论与支持向量机[J].自动化学报,2000,26(1):32-42.
[32]BEN-YACOUB S,A BDELJAOUED Y,M AYO RANE.Fusion of face and speech data for person identity verification[J].IEEE Trans on Neural Networks,1999,10(5):1065-1074
[3 3]陶秀凤,周鸣争.基于支持向量机的多传感器信息融合算法[J].计算机技术与发展.2006,16(6):177-183
[34]金龙,陈小宏,王守东.基于支持向量机与信息融合的地震油气预测方法[J].石油地球物理勘探,2006,41(2):76-81
[3 5]王晨,赵杰等.一种基于支持向量机的数据融合方法的研究[J].机械与电子,2004(8):8-11
[36]潘泉,于昕等.信息融合理论的基本方法与进展[J].自动化学报.2004(4):559-609
[37]高翔,王勇.数据融合技术综述[J].计算机测量与控制.2002.10(11):706-709
[38]何友,关欣,王国宏.多传感器信息融合研究进展与展望[J].宇航学报,2005,26(4):524-52
[2]臧大进.多传感器信息融合技术综述[J].工矿自动化,2005,6:30-32
[3]WALTZ E,BUEDE D M.Data fusion and decisionsupport for command and control[J].IEEE Trans on Syst,Man & Cybern,1986,16(6):865-879.
[4]COMPARATO V G.Fusion—The key to tactical mis-sion success[J].SPIE,1988,93(1):2-7.
[5]HAMILTON M K,KIPP T A.ATR architecture formultisensor fusion[J].SPIE,1996,275(5):126-133.
[6]王仲民,岳宏,刘继岩.移动机器人多传感器信息融合技术述评[J].传感器技术2005,24(4)5-7
[7]NEIRA J,TARDOS J D,Horn J et al.Fusing rangeand intensity image for mobile robot localization[J].IEEE Transon Robot Autom,1999,15(1):76-84.
[8]HERNANDEZ A I,GARRAULT G,MORA F et al.Multisensor fusion for atrial and ventricular activity detection incoronary care monitoring[J].IEEE Trans on Biomed Eng,1999,46(10):1186-1190.
[9]MURPHY R R.Sensor and information fusion forimproved vision-based veh icle guidance[J].IEEE Expert,1998,13(6):49-56.
[10]李圣怡,吴学忠,范大鹏.多传感器融合理论及在智能制造系统中的应用[M].长沙:国防科技大学出版社,1998.
[11]马平,吕锋等.多传感器信息融合基本原理及应用[J].控制工程,2006,13(1):48-51
[12]何友等.多传感器数据融合模型综述[J].清华大学学报.1996,36(9):14-20
[13]DAVID L HALL.An introduction to multisensor fusion[C].International workshop on data fusion in 2002,Beijing,China,2002
[14]王军,苏剑波,席裕庚.多传感器融合综述[J].数据采集与处理.2004,19(1):72-76
[15]VALET,L,MAURIS G and et al A Statistical Over-view of Recent Literature in Information Fusion[G].ISIF2000:Moc3-22-Moc3-29
[16]付华等.基于Bayes估计理论的数据融合方法[J].自动化技术与应用,2005,4(24):10-12
[17]DAVISON A J,NOBUYUKI K.3D Simultaneouslocalization and map building using active vision for a robotmoving on undulating terrain[C].Proceedings of the IEEEInternational Conference on Computer Vision and Recognization.USA:Hawaii,2001,384-389.
[18]李洪波.自适应Kalman滤波在多传感器数据融合中应用[J].国外电子测量技术,2006(6):69-71
[19]DON LERRO,BAR-SHALOM Y.Tracking withdebiased consistent converted measurements versus EKF[J].IEEETrans.on AES,1993,29(3):1015-1022
[20]MO L,SONG X,ZHOU Y,SUN Z,Bar-Shalom Y.Unbiased converted measurements for tracking[J].IEEE Trans.on AES,1998,34(3):1023-1027
[21]DOUCET A.et al.Particle filters for State Estimationof Jump Markov Linear Systems[J].IEEE Trans.On Signal Processing,March 2001,49(3):613-624.
[22]JULIER S J,JEFFERY K.UHLMANN.A Consistent,Debiased Method for Converting Between Polar and Cartesian Coordinate Systems[C].Proceedings of SPIE:Acquisition,Track-ing,and Pointing XI,1997:110-121.
[23]刘素一,张海霞等.基于小波变换和Kalman滤波的多传感器数据融合[J].传感器与仪器仪表.2006,22(6-1),179-181.
[24]FIXSEN D,MAHLER R.The modified Dempster-Shaferapp roach to Classification[J].IEEE Transaction on Systems Manand Cybernetics,1997,27(1):96-104.
[25]SASIADEK J Z.SENSOR FUSION.Annual Reviewsin Control.2002,26:203-228.
[2 6]郭丽梅,罗大庸.基于模糊神经网络的多传感器自适应融合[J].系统工程与电子技术,2004,26(2):215-218
[2 7]杨鹃,孙华等.模糊神经网络信息融合方法在机器人避障中的应用[J].自动化技术与应用,2005,24(2):22-24
[2 8]付华,孙树生等.基于模糊神经网络的信息融合方法在矿井供风系统中的应用[J],煤炭学报,2006,31(2):264-267
[29]李强,杨晓京,魏岚.基于神经网络信息融合的智能机器人[J].机电工程技术,2006,35(6).
[30]E.E.OSUNA,R.FREUND,F.GIROSI..Support vectormachine training and applications,Technical Report[R].Massa-chusetts Institute of Technology,Artificial Intelligence Laboratory,AI Memo No.1602,1997.
[31]张学工.关于统计学习理论与支持向量机[J].自动化学报,2000,26(1):32-42.
[32]BEN-YACOUB S,A BDELJAOUED Y,M AYO RANE.Fusion of face and speech data for person identity verification[J].IEEE Trans on Neural Networks,1999,10(5):1065-1074
[3 3]陶秀凤,周鸣争.基于支持向量机的多传感器信息融合算法[J].计算机技术与发展.2006,16(6):177-183
[34]金龙,陈小宏,王守东.基于支持向量机与信息融合的地震油气预测方法[J].石油地球物理勘探,2006,41(2):76-81
[3 5]王晨,赵杰等.一种基于支持向量机的数据融合方法的研究[J].机械与电子,2004(8):8-11
[36]潘泉,于昕等.信息融合理论的基本方法与进展[J].自动化学报.2004(4):559-609
[37]高翔,王勇.数据融合技术综述[J].计算机测量与控制.2002.10(11):706-709
[38]何友,关欣,王国宏.多传感器信息融合研究进展与展望[J].宇航学报,2005,26(4):524-52
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