Extended target tracking using an IMM based nonlinear Kalman filters
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KünyeZhou, Y., Xu, J., Jing, Y., & Dimirovski, G. M. (2010). Extended target tracking using an IMM based nonlinear Kalman filters. In 2010 American Control Conference (ACC) (pp. 6876-6881). Piscataway, NJ: IEEE. http://dx.doi.org/10.1109/ACC.2010.5531567
The unscented Kalman filter (UKF) and ensemble Kalman filter (EnKF) are developed to extended target tracking problem for high resolution sensors. The nonlinear Kalman filters are based on an ellipsoidal model, which is proposed to exploit sensor measurement of target extent. The ellipsoidal model can provide extra information to enhance tracking accuracy, data association performance, and target identification. In contrast to the most commonly used extended Kalman filter (EKF), the UKF and EnKF provide more accurate and reliable estimation performance, due to the presence of high nonlinearity of the model. Correspondingly, the EnKF has lower computational complexity than the UKF. An interacting multiple model (IMM) technique is combined with the filters to adapt the target maneuver and motion mode switching problem which is vital for nonlinear filtering. The developed IMM-UKF and IMM-EnKF algorithms on extended target tracking problem are validated and evaluated by computer simulations.