The traditional algorithm with fixed transition probability matrix is improved by using an adaptive method, and it can adjust transition probabilities according ...

Secondly,a new method is proposed to modify the Markov transition probability in real time based on the likelihood values of the models,which enhances the ...

Aug 25, 2023 · Two transition correction functions are proposed for the interaction multiple models (IMM) to adaptively update the Markov transition probability matrix (TPM) ...

Interacting Multiple Model Algorithm with Adaptive Markov Transition ... Markov state transition probabilities is presented , which is based on the measurements.

In [7], Blom and Bar-Shalom proposed an IMM algorithm with Markov transition probability. This algorithm considers the interaction between each model to ...

A estimator of the time-varying Markov state transition probabilities is presented, which is based on the measurements. Then the Parameter Adaptive ...

This algorithm demonstrates better computa-tional stability and precision than those based on EKF, and avoids computing the Jacobi matrix by using the ...

This paper proposes a tracking algorithm for maneuvering targets based on the Interacting Multiple Model (IMM) and Modified Gain EKF (MGEKF) algorithm that ...

This paper concentrates on fault-tolerant algorithm design and algorithm analysi:: of IMM estimation with the switching of a Markov chain. Monte Carlo ...

An Improved Interacting Multiple Model Algorithm With Adaptive Transition Probability Matrix Based on the Situation.