Set Value Observer Performance improvement with optimizing the free parameter in the MTT Problem
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- 英文论文题名：Set Value Observer Performance improvement with optimizing the free parameter in the MTT Problem
- 论文作者：Mohammad Ali Alirezapouri ; Hamid Khaloozadeh ; Ahmad Reza Vali ; Mohammad Reza Arvan
- 英文论文作者：Mohammad Ali Alirezapouri ; Hamid Khaloozadeh ; Ahmad Reza Vali ; Mohammad Reza Arvan ; Department of Control ; Faculty of Electrical Engineering ; Maleke-Ashtar University of technology ; Departments of System and Control ; Faculty of Electrical Engineering ; K.N.Toosi University of Technology
- 年：2017
- 作者机构：Department of Control,Faculty of Electrical Engineering,Maleke-Ashtar University of technology;Departments of System and Control,Faculty of Electrical Engineering,K.N.Toosi University of Technology;
- 英文论文关键词：Set value observer ; Maneuvering Target Tracking ; Free Parameters ; Optimal Filtering
- 会议召开时间：2017-07-26
- 会议录名称：第36届中国控制会议论文集（B）
- 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
- 语种：英文
- 分类号：TN713
- 学会代码：KZLL
- 会议名称：第36届中国控制会议
- 会议地点：中国辽宁大连
- 主办单位：中国自动化学会控制理论专业委员会
- 学会名称：中国自动化学会控制理论专业委员会
- 页数：6
- 文件大小：267k
- 原文格式：D
- 会议级别：全国
摘要
Observers based on set value theory(SVO) have a good performance in the maneuvering target tracking(MTT) problem. By assuming system disturbances, are unknown but bounded(UBB) the SVO or UBB filters can be used in maneuvering target tracking(MTT) problems. In the UBB filter implementation, free parameters appeared when bounding ellipsoids are used. Inappropriate choice of these free parameters, reduce accuracy and caused filter instability. To solve these problems, two methods(recursive parameters calculation(RPC) and calculates the optimal free parameters(OPC)) will be developed. Free parameters that calculated with OPC method, improves the accuracy of maneuvering targets state estimation and avoid algorithms instability in the MTT problem. The results of numerical simulations, confirms improved the efficiency and accuracy of the UBBF filter by using OPC method for free parameters calculation.
Observers based on set value theory(SVO) have a good performance in the maneuvering target tracking(MTT) problem. By assuming system disturbances, are unknown but bounded(UBB) the SVO or UBB filters can be used in maneuvering target tracking(MTT) problems. In the UBB filter implementation, free parameters appeared when bounding ellipsoids are used. Inappropriate choice of these free parameters, reduce accuracy and caused filter instability. To solve these problems, two methods(recursive parameters calculation(RPC) and calculates the optimal free parameters(OPC)) will be developed. Free parameters that calculated with OPC method, improves the accuracy of maneuvering targets state estimation and avoid algorithms instability in the MTT problem. The results of numerical simulations, confirms improved the efficiency and accuracy of the UBBF filter by using OPC method for free parameters calculation.
Observers based on set value theory(SVO) have a good performance in the maneuvering target tracking(MTT) problem. By assuming system disturbances, are unknown but bounded(UBB) the SVO or UBB filters can be used in maneuvering target tracking(MTT) problems. In the UBB filter implementation, free parameters appeared when bounding ellipsoids are used. Inappropriate choice of these free parameters, reduce accuracy and caused filter instability. To solve these problems, two methods(recursive parameters calculation(RPC) and calculates the optimal free parameters(OPC)) will be developed. Free parameters that calculated with OPC method, improves the accuracy of maneuvering targets state estimation and avoid algorithms instability in the MTT problem. The results of numerical simulations, confirms improved the efficiency and accuracy of the UBBF filter by using OPC method for free parameters calculation.
引文
[1]Mcintyre.G.A,and Hintz.K.j,“Comparison of several maneuvering target tracking models”,Proc.SPIE 3374,Signal Processing,Sensor Fusion,and Target Recognition VII,48(July 17,1998);doi:10.1117/12.327127
[2]Kreucher.C,Bell.K,Sobota.D,”A comparison of tracking algorithms for supermaneuverable targets”,Information Fusion(Fusion),201518th International Conference on
[3]Samira Rahnama,Mohammad Reza Arvan,“Comparison of extended and unscented Kalman smoother in deriving kinematic characteristics of a high maneuver flying target”,Modelling,Identification and Control(ICMIC),Proceedings of 2011 International Conference on
[4]H Khaloozadeh,A Karsaz,“Modified input estimation technique for tracking manoeuvring targets”,IET radar,sonar&navigation 3(1),30-41,2009
[5]Bahari.M.H,Naghibi.M.B,and Pariz.N,“Intelligent fading memory for high maneuvering target tracking”,International Journal of Physics Scince,Volume 4,No 10,2009
[6]Beheshtipour.Z,and Khaloozadeh.H,”An Innovative Fuzzy Covariance Presetting for High Maneuvering Targrt Tracking Problems”,Control and Decision Conference,PP.5623-5628,2009
[7]Schweppe,F.C,“Uncertain Dynamic Systems”,Prentice Hall Inc,Englewood Cliffs,1973
[8]Rahmati.H,Khaloozadeh.H,and Ayati.M,”Maneuvering Target Tracking Method based on Unknown but Bounded Uncertainties”,18th IFAc World Congress,2011
[9]Bo.Zhou,Jianda.Han,and Guangjun,Liu,“A UD factorization-Based nonlinear adaptive set-membership filter for ellipsoidal estimation”,International Journal of Robust and Noninear Control,2008
[10]Maksarov.DG,and Norton JP,“Computationally efficient algorithms for state estimation with ellipsoidal approximations.”,International Journal of Adaptive Control and Signal Processing,2002
[11]Durieu.C,Polyak.BT,and Walter.E,“Trace versus determinant in ellipsoidal outer bounding with application to state estimation’,13IFAC world congress,San Francisco,USA,Vol.1,1996,43-48
[2]Kreucher.C,Bell.K,Sobota.D,”A comparison of tracking algorithms for supermaneuverable targets”,Information Fusion(Fusion),201518th International Conference on
[3]Samira Rahnama,Mohammad Reza Arvan,“Comparison of extended and unscented Kalman smoother in deriving kinematic characteristics of a high maneuver flying target”,Modelling,Identification and Control(ICMIC),Proceedings of 2011 International Conference on
[4]H Khaloozadeh,A Karsaz,“Modified input estimation technique for tracking manoeuvring targets”,IET radar,sonar&navigation 3(1),30-41,2009
[5]Bahari.M.H,Naghibi.M.B,and Pariz.N,“Intelligent fading memory for high maneuvering target tracking”,International Journal of Physics Scince,Volume 4,No 10,2009
[6]Beheshtipour.Z,and Khaloozadeh.H,”An Innovative Fuzzy Covariance Presetting for High Maneuvering Targrt Tracking Problems”,Control and Decision Conference,PP.5623-5628,2009
[7]Schweppe,F.C,“Uncertain Dynamic Systems”,Prentice Hall Inc,Englewood Cliffs,1973
[8]Rahmati.H,Khaloozadeh.H,and Ayati.M,”Maneuvering Target Tracking Method based on Unknown but Bounded Uncertainties”,18th IFAc World Congress,2011
[9]Bo.Zhou,Jianda.Han,and Guangjun,Liu,“A UD factorization-Based nonlinear adaptive set-membership filter for ellipsoidal estimation”,International Journal of Robust and Noninear Control,2008
[10]Maksarov.DG,and Norton JP,“Computationally efficient algorithms for state estimation with ellipsoidal approximations.”,International Journal of Adaptive Control and Signal Processing,2002
[11]Durieu.C,Polyak.BT,and Walter.E,“Trace versus determinant in ellipsoidal outer bounding with application to state estimation’,13IFAC world congress,San Francisco,USA,Vol.1,1996,43-48