Brief paper: Data-driven communication for state estimation with sensor networks

Authors:
Giorgio Battistelli;Alessio Benavoli;Luigi Chisci
Affiliations:
Dipartimento di Sistemi e Informatica, DSI-Universití di Firenze, Via Santa Marta 3, 50139 Firenze, Italy;Istituto 'Dalle Molle' di Studi sull'Intelligenza Artificiale, 6928 Manno-Lugano, Switzerland;Dipartimento di Sistemi e Informatica, DSI-Universití di Firenze, Via Santa Marta 3, 50139 Firenze, Italy
Venue:
Automatica (Journal of IFAC)
Year:
2012

Citing 7
Cited 0

State estimation with communication constraints

Systems & Control Letters
Brief paper: Modified Kalman filter for networked monitoring systems employing a send-on-delta method

Automatica (Journal of IFAC)
Stability of Kalman filtering with Markovian packet losses

Automatica (Journal of IFAC)
Energy efficient state estimation with wireless sensors through the use of predictive power control and coding

IEEE Transactions on Signal Processing
On a stochastic sensor selection algorithm with applications in sensor scheduling and sensor coverage

Automatica (Journal of IFAC)
Rate-distortion performance in coding bandlimited sources by sampling and dithered quantization

IEEE Transactions on Information Theory
Distributed Kalman filtering based on consensus strategies

IEEE Journal on Selected Areas in Communications

Quantified Score

Hi-index	22.14

Visualization

Abstract

This paper deals with the problem of estimating the state of a discrete-time linear stochastic dynamical system on the basis of data collected from multiple sensors subject to a limitation on the communication rate from the sensors. More specifically, the attention is devoted to a centralized sensor network consisting of: (1) multiple remote nodes which collect measurements of the given system, compute state estimates at the full measurement rate and transmit data (either raw measurements or estimates) at a reduced communication rate; (2) a fusion node that, based on received data, provides an estimate of the system state at the full rate. Local data-driven transmission strategies are considered and issues related to the stability and performance of such strategies are investigated. Simulation results confirm the effectiveness of the proposed strategies.