This paper introduces a novel approach for tracking maneuvering targets in highly variable environments. An adaptive interacting multiple model algorithm, which is a combination of the modified adaptive Kalman algorithm and the interacting multiple model algorithm, is proposed to enhance tracking performance. One notable aspect of this method is its ability to continuously adjust the residual values of each sub-filter in the interacting multiple model algorithm, leading to improved adaptation to the target’s high mobility and increased accuracy in position estimation. In comparison to the classical interacting multiple model algorithm, the results from both simulation and real data suggest that the proposed adaptive interacting multiple model algorithm has shown a 38.3% increase in overall tracking accuracy in position and approximately 28% in velocity.