Maneuvering Target Tracking using IMM Algorithm Based on Strong Tracking UKF

摘要

For tackling the accuracy problem of tracking a maneuvering target, an algorithm of strong tracking unscented Kalman filter-interacting multiple model (STUKF-IMM) is presented. Unscented Kalman filter (UKF) is lack of adaptive on-line adjustment ability that seriously decreases the estimation accuracy of system state. To deal with this problem, this paper combines the strengths of strong tracking filter (STF) and UKF. Each sampling point of UKF is updated by STF, the effects of noises on system state estimation are suppressed by optimizing filter gains, and the system state estimation converges to real values quickly. The simulation results show that the proposed method is more effective and better accuracy.