An Augmented State Target Tracking Algorithm with the Existence of Systematic Errors

摘要

The problem that how to track a threedimensional target with the existence of systematic errors is researched in this paper. Based on the extended Kalman filter(EKF), an augmented state extended Kalman filter(ASEKF) tracking algorithm is proposed. By introducing systematic errors into the state vector of EKF,the joint estimation of target state and systematic errors is performed. Especially, in order to initializes the state estimation, three methods is derived, which is realized by using empiric value, regarding the systematic errors and random errors as correlated and uncorrelated. The simulation results show that the ASEKF algorithm can estimate efficiently, and the initialization methods effectively improve the tracking precision.