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- W2937646723 abstract "We study resilient distributed field estimation under measurement attacks. A network of agents or devices measures a large, spatially distributed physical field parameter. An adversary arbitrarily manipulates the measurements of some of the agents. Each agent's goal is to process its measurements and information received from its neighbors to estimate only a few specific components of the field. We present $mathbf{SAFE}$, the Saturating Adaptive Field Estimator, a consensus+innovations distributed field estimator that is resilient to measurement attacks. Under sufficient conditions on the compromised measurement streams, the physical coupling between the field and the agents' measurements, and the connectivity of the cyber communication network, $mathbf{SAFE}$ guarantees that each agent's estimate converges almost surely to the true value of the components of the parameter in which the agent is interested. Finally, we illustrate the performance of $mathbf{SAFE}$ through numerical examples." @default.
- W2937646723 created "2019-04-25" @default.
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- W2937646723 date "2019-04-18" @default.
- W2937646723 modified "2023-09-24" @default.
- W2937646723 title "Resilient Distributed Field Estimation" @default.
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- W2937646723 doi "https://doi.org/10.48550/arxiv.1904.08787" @default.
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