Title :
Gaussian Smoothers for Nonlinear Systems With One-Step Randomly Delayed Measurements
Author :
Xiaoxu Wang ; Quan Pan ; Yan Liang ; Feng Yang
Author_Institution :
Inst. of Control & Inf., Northwestern Polytech. Univ., Xi´an, China
Abstract :
This technical note is concerned with the nonlinear state smoothing problem in the case that the measurements are randomly delayed by one sampling time. Under Gaussian domain, two general Gaussian approximation (GA) and Gaussian mixture approximation (GMA) smoothers are proposed in minimum mean square error (MMSE) sense. The smoothing implementation is transformed into computing some special posterior covariances, which triggers the development of the new unscented Kalman smoother (UKS) by applying unscented transformation (UT). Simulation results demonstrate the superior performance of the proposed GA-UKS and GMA-UKS algorithms.
Keywords :
Gaussian processes; Kalman filters; approximation theory; covariance analysis; delays; mean square error methods; nonlinear filters; nonlinear systems; sampling methods; GMA smoothers; GMA-UKS algorithms; Gaussian mixture approximation smoothers; nonlinear state smoothing problem; nonlinear systems; one-step randomly delayed measurements; sampling time; unscented Kalman smoother; unscented transformation; Approximation methods; Delay; Electronics packaging; Filtering; Smoothing methods; Standards; Gaussian approximation; Gaussian mixture approximation; nonlinear state; one-step randomly delayed measurement; smoother; unscented transformation;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2013.2237971
