Maneuvering target tracking algorithm based on adaptive markov transition probabilitiy matrix and IMM-MGEKF

摘要

This paper proposes a tracking algorithm for maneuvering targets based on the Interacting Multiple Model (IMM) and Modified Gain EKF (MGEKF) algorithm that can modify the Markov transition probability matrix in real time. The algorithm improves the error caused by the transition probability matrix determined by the prior information in the classical IMM algorithm that does not match the current model well. The simulation results show that the maneuvering target tracking performance of this algorithm is better than the conventional IMM-EKF algorithm.