On the limited communication analysis and design for decentralized estimation
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1801.05849.pdf
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Author(s)
Alexandru, Andreea B.
Pequito, Sergio
Jadbabaie-Moghadam, Ali
Pappas, George
Date Issued
January 2018
Journal
2017 IEEE 56th Annual Conference on Decision and Control (CDC)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Alexandru, Andreea B., Sergio Pequito, Ali Jadbabaie, and George J. Pappas. “On the Limited Communication Analysis and Design for Decentralized Estimation.” 2017 IEEE 56th Annual Conference on Decision and Control (CDC) (December 2017).
Version
Author's final manuscript
Abstract
This paper pertains to the analysis and design of decentralized estimation schemes that make use of limited communication. Briefly, these schemes equip the sensors with scalar states that iteratively merge the measurements and the state of other sensors to be used for state estimation. Contr arily to commonly used distributed estimation schemes, the only information being exchanged are scalars, there is only one common time-scale for communication and estimation, and th e retrieval of the state of the system and sensors is achieved in finite-time. We extend previous work to a more general setup and provide necessary and sufficient conditions required for the communication between the sensors that enable the use of limited communication decentralized estimation schemes. Additionally, we discuss the cases where the sensors are memoryless, and where the sensors might not have the capacity to discern the contributions of other sensors. Based on these conditions a nd the fact that communication channels incur a cost, we cast th e problem of finding the minimum cost communication graph that enables limited communication decentralized estimation schemes as an integer programming problem.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1109/CDC.2017.8263897
