摘要
在实际目标跟踪系统中,测量设备都存在系统误差,会导致跟踪滤波精度显著下降。针对多测速系统,对其测速系统误差进行了简化数学建模;然后将其增广为状态变量,应用扩维无迹卡尔曼滤波对目标运动状态和系统误差进行联合估计,以实时校准系统误差、提高状态估计精度。在存在主副站2类系统误差的条件下,设定恒定和线性时变2类系统误差场景,对算法进行仿真分析。仿真结果表明,算法在2类系统误差情形下都能有效校准系统误差,位置、速度滤波精度可提高80%以上;尤其是当系统误差恒定时,算法可完全消除系统误差的影响。
The systematic errors of measurement equipment degrade tracking and filtering accuracy of space object tracking systems, This paper proposes a simplified mathematic model for the systematic errors of multiple range-rate measurement systems. The system errors are extended to state variables with augmented dimension UKF （Unscent-ed Kalman Filter） to jointly estimate the states of objects and systematic errors so as to calibrate the systematic er- rors and improve state estimation accuracy. Two scenarios with constant and linear time-varying errors are set for simulation and analysis of the algorithm under the condition that there exit only two types of errors of a master sta-tion and slave stations. Simulation results show that the proposed algorithm effectively calibrates systematic errors and improves tracking accuracy by at least 80% in both scenarios and the impact is significantly minimized when sys-tematic errors are constant.
出处
《飞行器测控学报》
2012年第5期49-53,共5页
Journal of Spacecraft TT&C Technology
关键词
系统误差建模
实时校准
扩维无迹卡尔曼滤波(UKF)
多测速系统
modeling of systematic error
realtime calibration
augmented dimension Unscented Kalman Filter（UKF）
multiple range-rate measurement system
