增广误差模型算法在目标跟踪中的应用
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摘要
针对目标机动运行过程中,滤波模型与机动状态模型失配的问题,提出了一种新的增广状态误差滤波模型。不同于现有增广方案,该模型从模型失配所致状态滤波误差的角度出发,将状态估计误差增广为一状态量,通过滤波估计后用其校正原状态量。算法分析表明,该增广滤波模型具有自适应调节多重渐消因子的等效特性,增强了对目标的跟踪能力。基于该增广状态误差滤波模型,给出了滤波算法设计并进行了仿真实验。实验结果表明,基于该模型的滤波算法在对机动目标进行跟踪时具有更强的鲁棒性。
A new augmented bias model is put forward for the target tracking regarding the problems of mismatches between filtering model and maneuvering state model during the course of target maneuvering.Unlike the current augmented models,in the proposed model,in the view of the state estimating error caused by model mismatches,the state error is considered as an augmented state vector.Then the state error is estimated to correct the original state.The analysis of the proposed augmented model algorithm shows that the filter contains the equivalent adaptive multiple fading factors,which enhances the tracking ability.The filter is designed for augmented bias model and a mathematical simulation is carried out.The simulation results show that the filtering algorithm based on this model has strong robustness in tracking maneuvering targets.
A new augmented bias model is put forward for the target tracking regarding the problems of mismatches between filtering model and maneuvering state model during the course of target maneuvering.Unlike the current augmented models,in the proposed model,in the view of the state estimating error caused by model mismatches,the state error is considered as an augmented state vector.Then the state error is estimated to correct the original state.The analysis of the proposed augmented model algorithm shows that the filter contains the equivalent adaptive multiple fading factors,which enhances the tracking ability.The filter is designed for augmented bias model and a mathematical simulation is carried out.The simulation results show that the filtering algorithm based on this model has strong robustness in tracking maneuvering targets.
引文
[1]Mcaulay R J,Denlinger E.A decision-directed adaptive tracker[J].IEEE Transactions on Aerospace&Electronic Systems,1973,AES-9(2):229-236.
[2]Singer R A.Estimating optimal tracking filter performance for manned maneuvering targets[J].IEEETransactions on Aerospace&Electronic Systems,1970,6(4):473-483.
[3]Li X R,Jilkov V P.Survey of maneuvering target tracking.Part V:multiple-model methods[J].IEEETransactions on Aerospace&Electronic Systems,2005,41(4):1255-1321.
[4]Blair W D,Watson G A,Rice T R.Tracking maneuvering targets with an interacting multiple model filter containing exponentially-correlated acceleration models[J].Asian Journal of Information Management,1991,3(1):224-228.
[5]Bar-Shalom Y,Birmiwal K.Variable dimension filter for maneuvering target tracking[J].IEEE Transactions on Aerospace&Electronic Systems,1982,AES-18(5):621-629.
[6]陈晓荣,陈淑芬.变维卡尔曼滤波实现运动目标的跟踪[J].仪器仪表学报,2006,27(9):1163-1166.Chen Xiaorong,Chen Shufen.Variable dimension of Kalman filter for target tracking[J].Chinese Journal of Scientific Instrument,2006,27(9):1163-1166(in Chinese).
[7]Deng Z L,Lu Y,Lei Y.Virtual noise and variable dimension Kalman filter for maneuvering target tracking[C]//International Conference on Remote Sensing.2012:909-917.
[8]Li X R,Jilkov V P.A survey of maneuvering target tracking-Part III:measurement models[J].IEEETransactions on Aerospace&Electronic Systems,2001,39(4):1333-1364.
[9]Wang L,Wu L,Yong G,et al.Online sensor fault detection based on an improved strong tracking filter[J].Sensors,2015,15(2):4578-4591.
[10]高琴,任郑兵,孙爱民.基于星敏感器的卫星姿态估计方法研究[J].导航定位与授时,2018,5(1):42-47.Gao Qin,Ren Zhengbing,Sun Aimin.Research on satellite attitude estimation based on star sensor[J].Navigation Positioning&Timing,2018,5(1):42-47(in Chinese).
[11]Gao M,Zhang H,Zhou Y,et al.Ground maneuvering target tracking based on the strong tracking and the cubature Kalman filter algorithms[J].Journal of Electronic Imaging,2016,25(2):023006.
[12]Zhou D H,Frank P M.Strong tracking filtering of nonlinear time-varying stochastic systems with coloured noise:application to parameter estimation and empirical robustness analysis[J].International Journal of Control,1996,65(2):295-307.
[13]Jwo D J,Huang C M.An adaptive fuzzy strong tracking Kalman filter for GPS/INS navigation[C]//IECON 2007-33rd Annual Conference of the IEEE Industrial Electronics Society,2007:2266-2271.
[14]Dee D P,Silva A M D.Data assimilation in the presence of forecast bias[J].Quarterly Journal of the Royal Meteorological Society,2010,124(545):269-295.
[2]Singer R A.Estimating optimal tracking filter performance for manned maneuvering targets[J].IEEETransactions on Aerospace&Electronic Systems,1970,6(4):473-483.
[3]Li X R,Jilkov V P.Survey of maneuvering target tracking.Part V:multiple-model methods[J].IEEETransactions on Aerospace&Electronic Systems,2005,41(4):1255-1321.
[4]Blair W D,Watson G A,Rice T R.Tracking maneuvering targets with an interacting multiple model filter containing exponentially-correlated acceleration models[J].Asian Journal of Information Management,1991,3(1):224-228.
[5]Bar-Shalom Y,Birmiwal K.Variable dimension filter for maneuvering target tracking[J].IEEE Transactions on Aerospace&Electronic Systems,1982,AES-18(5):621-629.
[6]陈晓荣,陈淑芬.变维卡尔曼滤波实现运动目标的跟踪[J].仪器仪表学报,2006,27(9):1163-1166.Chen Xiaorong,Chen Shufen.Variable dimension of Kalman filter for target tracking[J].Chinese Journal of Scientific Instrument,2006,27(9):1163-1166(in Chinese).
[7]Deng Z L,Lu Y,Lei Y.Virtual noise and variable dimension Kalman filter for maneuvering target tracking[C]//International Conference on Remote Sensing.2012:909-917.
[8]Li X R,Jilkov V P.A survey of maneuvering target tracking-Part III:measurement models[J].IEEETransactions on Aerospace&Electronic Systems,2001,39(4):1333-1364.
[9]Wang L,Wu L,Yong G,et al.Online sensor fault detection based on an improved strong tracking filter[J].Sensors,2015,15(2):4578-4591.
[10]高琴,任郑兵,孙爱民.基于星敏感器的卫星姿态估计方法研究[J].导航定位与授时,2018,5(1):42-47.Gao Qin,Ren Zhengbing,Sun Aimin.Research on satellite attitude estimation based on star sensor[J].Navigation Positioning&Timing,2018,5(1):42-47(in Chinese).
[11]Gao M,Zhang H,Zhou Y,et al.Ground maneuvering target tracking based on the strong tracking and the cubature Kalman filter algorithms[J].Journal of Electronic Imaging,2016,25(2):023006.
[12]Zhou D H,Frank P M.Strong tracking filtering of nonlinear time-varying stochastic systems with coloured noise:application to parameter estimation and empirical robustness analysis[J].International Journal of Control,1996,65(2):295-307.
[13]Jwo D J,Huang C M.An adaptive fuzzy strong tracking Kalman filter for GPS/INS navigation[C]//IECON 2007-33rd Annual Conference of the IEEE Industrial Electronics Society,2007:2266-2271.
[14]Dee D P,Silva A M D.Data assimilation in the presence of forecast bias[J].Quarterly Journal of the Royal Meteorological Society,2010,124(545):269-295.