A complete greedy algorithm for infinite-horizon sensor scheduling. (July 2017)

• Record Type: Journal Article
• Authors: Asghar, Ahmad Bilal; Jawaid, Syed Talha; Smith, Stephen L.
• Is Part Of: Automatica. Volume 81(2017)
• Page Start: 335
• Page End: 341
• Publication Date: 2017-07
• Subjects: Sensor networks -- Kalman filters -- Sensor scheduling -- Multi-sensor estimation; Automatic control -- Periodicals; Automation -- Periodicals; 629.805
• DOI: 10.1016/j.automatica.2017.04.018
• Languages: English
• ISSNs: 0005-1098

Abstract

Abstract: In this paper we study the problem of scheduling sensors to estimate the state of a linear dynamical system. The estimator is a Kalman filter and our objective is to optimize the a posteriori error covariance over an infinite time horizon. We focus on the case where a fixed number of sensors are selected at each time step, and we characterize the exact conditions for the existence of a schedule with uniformly bounded estimation error covariance. Using this result, we construct a scheduling algorithm that guarantees that the error covariance will be bounded if the existence conditions are satisfied. We call such an algorithm complete. Finally, we provide simulations to compare the performance of the algorithm against other known techniques.