Distributed Nonlinear Fusion Estimation for Networked Multi Sensor System with Noisy Control Input and Packet Dropout

This paper investigates the distributed fusion estimation problem for nonlinear networked multi-sensor systems, where the control input contains bounded noise and packet dropout will also occur over the sensor network. Firstly, the prediction measurement-based compensation model is adopted to address the packet dropout problem. Then, based on the compensation measurement, the noisy input is considered in the design of the nonlinear estimator. Furthermore, by modeling the linearization errors as the uncertainty parameters, different convex optimization problems with respect to local estimator gains and the distributed fusion criterion are established. Therefore, a distributed robust fusion estimation method is proposed based on the technique of linear matrix inequality and the idea of bounded recursive optimization. Finally, an example is given to illustrate the effectiveness of the proposed method.