Recursive State Estimation for Complex Networks With Degraded Measurements and Amplify-and-Forward Relays Under Energy Harvesting Constraints

Abstract

This paper addresses the recursive remote state estimation problem for a class of discrete-time nonlinear time-varying complex networks with measurement degradation, uncertain inner couplings, energy harvesting (EH) constraints, and amplify-and-forward (AF) relays. The inner-coupling matrix is assumed to be unknown but bounded within a prescribed interval. To mitigate the limited communication capability of sensor nodes, amplify-and-forward (AF) relays are introduced to assist measurement transmission over extended links and to enhance the quality of the received data. To address these stochastic effects, a recursive state estimator is designed under the considered time-varying network framework. An upper bound on the estimation error covariance is then derived via a set of Riccati-like difference equations, and the estimator gain is recursively obtained by minimizing the trace of this bound. Furthermore, the boundedness of the proposed estimator is established. Simulation results confirm the effectiveness and applicability of the proposed estimation scheme.