Sensor placement for optimal Kalman filtering: Fundamental limits, submodularity, and algorithms

@article{Tzoumas2016SensorPF,
  title={Sensor placement for optimal Kalman filtering: Fundamental limits, submodularity, and algorithms},
  author={Vasileios Tzoumas and Ali Jadbabaie and George J. Pappas},
  journal={2016 American Control Conference (ACC)},
  year={2016},
  pages={191-196}
}
In this paper, we focus on sensor placement in linear dynamic estimation, where the objective is to place a small number of sensors in a system of interdependent states so to design an estimator with a desired estimation performance. In particular, we consider a linear time-variant system that is corrupted with process and measurement noise, and study how the selection of its sensors affects the estimation error of the corresponding Kalman filter over a finite observation interval. Our… 

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