Decentralized observers for position and velocity estimation in vehicle formations with fixed topologies

This paper addresses the problem of decentralized state estimation in fixed topology formations of vehicles with applications to Autonomous Underwater Vehicles (AUVs). In the envisioned scenario, each vehicle in the formation estimates its own state relying only on locally available measurements and data communicated by neighboring agents, requiring lower computational and communication loads than centralized solutions. A method for designing local state observers featuring global error dynamics that converge globally asymptotically to zero is detailed, and an algorithm for improving its performance under stochastic disturbances and Gaussian uncertainties is presented. The proposed algorithm minimizes the H 2 norm of the global estimation error dynamics, expressed as an optimization problem subject to Bilinear Matrix Inequality (BMI) constraints. To assess the performance of the solution, realistic simulation results are presented and discussed for several formation topologies.