Maneuvering target tracking with modified unbiased FIR filter

Abstract

In the field of maneuvering target tracking,the performance of Kalman filter( KF) and its variants is dependeds on the accuracy of the assumed process noise statistics. If the assumed process noise is not accurate,the performance of the KF and its improved algorithms will be degraded significantly. In some cases,the filters might even cannot be converged. Unbiased finite impulse response( UFIR) filter does not need the prior knowledge of the process noise statistics during filtering. Hence,it can be utilized to overcome the problem of the inaccurate assumed process noise statistics to realize the maneuvering target tracking. Since the generalized noise power gain( GNPG) of the existing UFIR filter cannot be adapted to the measurements innovation,an improved UFIR filter was proposed. The proposed UFIR dynamically adjusts GNPG according to the ratio of measurements innovations between the adjacent time such that it can improve the detecting ability of the UFIR filter for target maneuver. The simulation results illustrate that if assumed process noise is accurate,the performance of the existing UFIR filter and the proposed FIR filter is similar to KF; but if assumed process noise is not accurate,the performance of the proposed UFIR shows better than the other ones.