Adaptive Event-Driven Robust Set-Membership Estimation for Received-Signal-Strength-Based Moving Targets Localization

Abstract

This article presents an environmentally adaptive event-driven robust set-membership fusion estimator for received-signal-strength-based moving targets localization or tracking in resource-constrained mobile wireless sensor networks under the influence of unknown but bounded modeling and measurement uncertainties. First, a new adaptive event-triggered mechanism is designed to schedule close to the desired number of anchors no matter how the anchors are distributed near the moving target, which can improve energy efficiency, ease communication burden, and reduce computational complexity. Second, to obtain the recursive fusion estimation formulas generating an ellipsoidal set containing the actual state of the moving target or mobile node by fusing the received signal strength measurements from the nearby triggered anchors, this estimator is divided into two steps: 1) the prediction update step and 2) the fusion estimation step. Each step is converted to a semidefinite or convex programming problem of dimension variation, and its computational complexity is reduced substantially by the decoupled method and the adaptive event-triggered mechanism. Finally, numerical simulations show that the proposed method has superiority in reducing energy consumption, communication, and computational complexity with guaranteed localization accuracy.