Multisensor Fusion Estimation Theory and Application

Multisensor Fusion Estimation Theory and Application

Jiang, Lu; Xia, Yuanqing; Yan, Liping

Springer Verlag, Singapore

11/2021

227

Mole

Inglês

9789811594281

15 a 20 dias

385

Descrição não disponível.
Introduction to Optimal Fusion Estimation and Kalman Filtering: Preliminaries.- Kalman Filtering of Discrete Dynamic Systems.- Optimal Kalman filtering Fusion for Linear Dynamic Systems with Cross-Correlated Sensor Noises.- Distributed Data Fusion for Multirate Sensor Networks.- Optimal Estimation for Multirate Systems with Unreliable Measurements and Correlated Noise.- Fusion Estimation for Asynchronous Multirate Multisensor Systems with Unreliable Measurements and Coupled Noises.- Multi-sensor Distributed Fusion Estimation for Systems with Network Delays, Uncertainties and Correlated Noises.- Event-triggered Centralized Fusion Estimation for Dynamic Systems with Correlated Noises.- Event-triggered Distributed Fusion Estimation for WSN Systems.- Event-triggered Sequential Fusion Estimation for Dynamic Systems with Correlated Noises.- Distributed Fusion Estimation for Multisensor Systems with Heavy-tailed Noises.- Sequential FusionEstimation for Multisensor Systems with Heavy-tailed Noises.
Multisensor data fusion;State estimation;Kalman filter;Heavy-tailed noise;Event-triggered mechanism