Kullback-Leibler differential entropy equation based CIMM-PDA for reliable positioning

An interactive multi-model probability data association based on Kullback-Leibler differential entropy for reliable positioning is proposed to stably track noise. When the changes in measurement noise and process noise occurs, the interactive multi-models can fuse the estimated results and by combination of probabilities in models, noise can be dynamically tracked, to improve the reliability and accuracy of positioning procedures. The simulation results show that with the increase of measurement noise, the KL-CIMM-PDA method is more stable and more adaptive to track noise than the CIMM-PDA method and compared with the IMM-UKF, the accuracy of the KL-CIMM-PDA is improved by 26.7%.