UIF-based cooperative tracking method for multi-agent systems with sensor faults

For maneuvering target tracking with sensor faults, consensus-based distributed state estimation problems are studied herein. The communication status of the nonlinear system composed of multiple agents is described using the graph theory. Considering the impacts caused by sensor failures on measurement equations, a weighted average consensus-based unscented information filter (UIF) algorithm is proposed to improve tracking accuracy. Moreover, the estimation error for the investigated nonlinear system has been analyzed based on the stochastic boundedness theory to evaluate the proposed algorithm’s performance and feasibility. Finally, simulation results are presented to assert the validity of the method.