On infinite-horizon sensor scheduling
- Creators
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Mo, Y.
- Garone, E.
- Sinopoli, B.
Abstract
In this paper we consider the problem of infinite-horizon sensor scheduling for estimation in linear Gaussian systems. Due to possible channel capacity, energy budget or topological constraints, it is assumed that at each time step only a subset of the available sensors can be selected to send their observations to the fusion center, where the state of the system is estimated by means of a Kalman filter. Several important properties of the infinite-horizon schedules will be presented in this paper. In particular, we prove that the infinite-horizon average estimation error and the boundedness of a schedule are independent of the initial covariance matrix. We further provide a constructive proof that any feasible schedule with finite average estimation error can be arbitrarily approximated by a bounded periodic schedule. We later generalized our result to lossy networks. These theoretical results provide valuable insights and guidelines for the design of computationally efficient sensor scheduling policies.
Additional Information
© 2014 Elsevier B.V. Received 10 February 2013; Received in revised form 15 January 2014; Accepted 4 February 2014; Available online 17 March 2014. The first and third authors' research was supported in part by the CyLab at Carnegie Mellon under grant DAAD19-02-1-0389 from the Army Research Office Foundation. The views and conclusions contained here are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either express or implied, of ARO, CMU, or the U.S. Government or any of its agencies.Additional details
- Eprint ID
- 45987
- DOI
- 10.1016/j.sysconle.2014.02.002
- Resolver ID
- CaltechAUTHORS:20140529-154555050
- Carnegie Mellon CyLab
- DAAD19-02-1-0389
- Army Research Office (ARO)
- Created
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2014-05-30Created from EPrint's datestamp field
- Updated
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2021-11-10Created from EPrint's last_modified field