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• W3120900716 abstract "This paper describes a framework to design guidance for a team of mobile sensors to estimate a distributed parameter system modeled by a diffusion process. The diffusion process has an abstract linear system representation with a linear observation equation, so an infinite-dimensional version of the Kalman filter is applied for estimation. We propose an optimization problem that minimizes the weighted sum of the trace of the covariance operator of the Kalman filter and the guidance effort of the mobile sensors, whose motion is modeled by linear dynamics. This formulation is well-suited for limited endurance mobile sensor platforms. We provide a solution method to solve for the optimal guidance. A finite-dimensional approximation is applied to a simulation in which we analyze how the performance of a single mobile sensor depends on mobility penalty and sensor noise. We also illustrate the application of the framework to a team of heterogeneous sensors." @default.
• W3120900716 created "2021-01-18" @default.
• W3120900716 creator A5079627021 @default.
• W3120900716 creator A5090964638 @default.
• W3120900716 date "2020-12-14" @default.
• W3120900716 modified "2023-10-18" @default.
• W3120900716 title "Optimal guidance and estimation of a 1D diffusion process by a team of mobile sensors" @default.
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• W3120900716 doi "https://doi.org/10.1109/cdc42340.2020.9303985" @default.
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