While doing a literature review on sensor planning framework, I found an interesting topic that how to select sensors over given sensors for reducing the cost such as reducing the price budget or limiting the number of sensors for low complexity of the model.

In this blog, I reviewed three representative papers, focusing on what problems they tried to solve, how they defined the problem and what approach they used to solve these problems. I believe it would be helpful to define the novel problem statement: Kalman Filter Sensor Selection for Decentralized joint state and input estimation.

[1] Sensor Selection for Optimal Filtering of Linear Dynamical Systems: Complexity and Approximation (CDC 2015) [2] Sensor Selection for Kalman Filtering of Linear Dynamical Systems: Complexity, Limitations and Greedy Algorithms (Automatica 2017) [3] On the Complexity and Approximability of Optimal Sensor Selection and Attack for Kalman Filtering (IEEE transaction automatic control 2020)

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