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We consider the problem of state estimation of a discrete time process over an unreliable communication network. Most previous work in literature focus on either quantization effect or packet drops or delays, with a few work considering those uncertainties simultaneously. In this paper, we first present two quantized filter design methods based on a logarithmic quantizer. The first method characterizes...
In this paper we consider the state estimation carried over a sensor network. At each time step, only a subset of all sensors are selected to send their observations to the fusion center, where a Kalman filter is implemented to perform the state estimation. The sensors are selected to maximize the lifetime of the network while maintaining a desired quality of state estimation accuracy. We propose...
In this paper we consider state estimation carried over a sensor network. A fusion center forms a local multi-hop tree of sensors and gateways and fuses the data into a state estimate. It is shown that the optimal estimator over a sensor tree is given by a Kalman filter of certain structure. The number of hops that the sensors use to communicate data with the fusion center is optimized such that either...
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