Maneuvering target tracking using an adaptive interacting multiple model algorithm

Abstract

An adaptive interacting multiple model algorithm (AIMM) is presented in this paper to track a maneuvering target. Each model is assigned a fixed deterministic acceleration to cope with the different target accelerations. A rough estimate of the target acceleration is taken from a biased filter which uses combined information from the models. This estimated acceleration is then taken into account in the models. Different maneuvering target scenarios were generated to compare the performance of the AIMM algorithm with the IMM algorithm.