Recursive relocation of lost intelligent agent by Aitkin acceleration method and extended Kalman filtering algorithm

Abstract

The state space model of signal and noise is used to find the missing position of multiple mobile intelligent agents. The estimation value of other mobile agents and the observed value at the present time are used to update the estimation of the state variable, and the estimation value of the missing position of mobile agents is obtained. In order to improve the convergence speed of the iterative method, the extended Kalman filtering algorithm and the aitkin accelerating convergence method are used to recurse the location of the mobile agent with all the lost positions.