Attitude angle aided IMMCKF algorithm

Abstract

To effectively solve the tracking problem of nonlinear maneuvering target, interacting multiple model cubature Kalman filter (immckf) algorithm brings cubature Kalman filter (ckf) into the interacting multiple model (imm) algorithm. This paper brings the attitude angle information into the immckf algorithm, and identifies the target maneuver mode through the fuzzy association between the attitude angle and the current motion mode of target; then the association result is used to fuse with the model probability of imm to enhance its model resolving power. A simulation of maneuvering target tracking shows that the attitude angle aided immckf (aa-immckf) algorithm can effectively improve the tracking accuracy and stability of the original immckf algorithm.