Deterministic Sensor Selection for Centralized State Estimation Under Limited Communication Resource

This paper studies a sensor selection problem. A group of sensors measure the state of a process and send their measurements to a remote estimator. Due to communication constraints, only limited sensors are allowed to communicate with the estimator. The paper intends to answer which sensors should be chosen such that the estimation performance of the estimator is optimized. Both reliable and packet-dropping channels are considered. It is required to minimize the steady-state estimation error covariance for reliable channels and to minimize the upper bound of the expected estimation error covariance for packet-dropping channels. For both scenarios, the original optimization problems are transformed to problems which can be solved by convex optimization techniques.