Distributed Nonlinear Estimation: A Recursive Optimization Approach

This paper is concerned with the distributed estimation problem for nonlinear systems with unknown but bounded noises, where the bounds of noises are also unknown. By modeling a new distributed estimation error system including the bias among local estimation errors, a bounded recursive optimization scheme is constructed to determine the matrix gains of distributed estimator. Notice that the constructed optimization problem for each local estimator, which can be easily solved by the existing software applications, is only dependent on the itself information and its neighboring information, and thus the design of distributed estimator and the determination of estimator gains are all fully distributed. Finally, a range-only target tracking system is employed to show the effectiveness and advantages of the proposed methods.