Multi-Sensor Linear State Estimation Under High Rate Quantization

Variance-Constrained State Estimation for Networked Multi-rate Systems with Measurement Quantization and Probabilistic Sensor Failures

This paper is concerned with the variance-constrained state estimation problem for a class of networked multi-rate systems (NMSs) with network-induced probabilistic sensor failures and measurement quantization. The stochastic characteristics of the sensor failures are governed by mutually independent random variables over the interval [0, 1]. By applying the lifting technique, an augmented syst...

Multi-sensor Transmission Management for Remote State Estimation under Coordination

This paper considers the remote state estimation in a cyber-physical system (CPS) using multiple sensors. The measurements of each sensor are transmitted to a remote estimator over a shared channel, where simultaneous transmissions from other sensors are regarded as interference signals. In such a competitive environment, each sensor needs to choose its transmission power for sending data packe...

Multi-rate optimal state estimation

Estimation of Intrinsic Dimensionality Using High-Rate Vector Quantization

We introduce a technique for dimensionality estimation based on the notion of quantization dimension, which connects the asymptotic optimal quantization error for a probability distribution on a manifold to its intrinsic dimension. The definition of quantization dimension yields a family of estimation algorithms, whose limiting case is equivalent to a recent method based on packing numbers. Usi...

Sensor Scheduling for Multi-parameter Estimation under an Energy Constraint

We consider a sensor scheduling problem for estimating multiple independent Gaussian random variables under an energy constraint. The sensor measurements are described by a linear observation model; the observation noise is assumed to be Gaussian. We formulate this problem as a stochastic sequential allocation problem. Due to the Gaussian assumption and the linear observation model, this proble...