Suboptimal Filter for Multisensor Linear Continuous-Time Systems with Uncertainties

Abstract

The problem of estimation for uncertain multisensor linear continuous-time systems is considered. A new suboptimal filtering algorithm is proposed herein. The proposed algorithm is based on the fusion formula for an arbitrary number of local Kalman filters. Each local Kalman filter is fused by weighted sum with scalar weights in the proposed suboptimal filter. The real time implementation of the proposed filter is possible because the scalar weights do not depend on current observations unlike optimal adaptive filter. The given examples, demonstrate the effectiveness and high precision of proposed filter