Distributed Kalman Filter for Cooperative Localization with Integrated Measurements

Abstract

This correspondence is concerned with the problem of distributed Kalman filtering for cooperative localization with absolute and relative measurements. Each target state is estimated by using locally available absolute measurements and relative measurements with other targets in the neighborhood. Two distributed Kalman filters are developed by enforcing each target to transmit its local estimates to the neighbors in a directed graph. A sufficient condition is established to guarantee the stability of the error dynamics. Numerical simulations are provided to verify the effectiveness of the proposed filters.