Decentralized robust set-valued state estimation in networked multiple sensor systems

This paper addresses a decentralized robust set-valued state estimation problem for a class of uncertain systems via a data-rate constrained sensor network. The uncertainties of the systems satisfy an energy-type constraint known as an integral quadratic constraint. The sensor network consists of spatially distributed sensors and a fusion center where set-valued state estimation is carried out. The communications from the sensors to the fusion center are through data-rate constrained communication channels. We propose a state estimation scheme which involves coders that are implemented in the sensors, and a decoder–estimator that is located at the fusion center. Their construction is based on the robust Kalman filtering techniques. The robust set-valued state estimation results of this paper involve the solution of a jump Riccati differential equation and the solution of a set of jump state equations.     

The problem of optimal robust Kalman state estimation via limited capacity digital communication channels

This paper considers a state estimation problem for a continuous-time uncertain system via a digital communication channel with bit-rate constraints. The estimated state must be quantized, coded and transmitted via a limited capacity digital communication channel. Optimal and suboptimal recursive coder–decoder state estimation schemes are proposed and investigated.     

Precision missile guidance using radar/multiple-video sensor fusion via communication channels with bit-rate constraints

We consider a precision missile guidance problem in which the objective is twofold: to come as close as possible to hitting the target, and also to do so from a particular direction. The effectiveness of a guidance law is strongly dependent on the quality of information available to it. In this work we construct a precision guidance law that combines information from an on-board video camera with data transmitted from ground-based radars and video cameras mounted on unmanned aerial vehicles. The communication channels are bit-rate limited, and recent results in control and estimation over finite-data-rate channels are used to construct a nonlinear state estimator. Simulations show the performance improvements which are possible compared to the use of the on-board sensor alone.