Paper Info
Title
An Improved Gaussian Filter for Dynamic Positioning Ships With Colored Noises and Random Measurements Loss.
Abstract
An improved Gaussian Filter (GF) is designed for nonlinear Dynamic Positioning (DP) ships with cross-correlated colored noises and random measurements loss. For the actual nonlinear Dynamic Position System (DPS), the state noises and measurement noises do not satisfy the assumption of Gaussian white noises and the loss of measurements may occur randomly. Therefore, the following circumstances are considered: the state noises and measurement noises are cross-correlated colored noises at the same and adjacent sampling moments; the measurement loss occurs randomly for the data transmission between the sensor units and the estimator units. In order to get the estimator for nonlinear DP ships with cross-correlated colored noises and random measurements loss, a GF framework based on Bayesian theory is proposed, and then the Cubature Mix Kalman Filter based on spherical-radial method is obtained. In the end, the simulation results show that the proposed algorithm has better estimation performance than Unscented Kalman Filter with Measurements Loss and standard Cubature Kalman Filter.
Year
DOI
Venue
2018
10.1109/ACCESS.2018.2789336
IEEE ACCESS
Keywords
Field
DocType
Colored noise,filtering algorithms,nonlinear systems,noise measurement,loss measurement
Gaussian filter,Dynamic positioning,Colors of noise,Nonlinear system,Noise measurement,Computer science,Algorithm,Kalman filter,Gaussian,Distributed computing,Estimator
Journal
Volume
ISSN
Citations 
6
2169-3536
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Xiaogong Lin141.78
Yuzhao Jiao220.71
Dawei Zhao319320.38