Gravity Matching Aided Inertial Navigation Technique Based on Marginal Robust Unscented Kalman Filter
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-02-23
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
This paper is concerned with the topic of gravity matching aided inertial navigation technology using Kalman filter.
The dynamic state space model for Kalman filter is constructed as follows: the error equation of the inertial navigation system is employed as the process equation while the local gravity model based on 9-point surface interpolation is employed as the observation equation.
The unscented Kalman filter is employed to address the nonlinearity of the observation equation.
The filter is refined in two ways as follows.
The marginalization technique is employed to explore the conditionally linear substructure to reduce the computational load; specifically, the number of the needed sigma points is reduced from 15 to 5 after this technique is used.
A robust technique based on Chi-square test is employed to make the filter insensitive to the uncertainties in the above constructed observation model.
Numerical simulation is carried out, and the efficacy of the proposed method is validated by the simulation results.
American Psychological Association (APA)
Liu, Ming& Chang, Guobin. 2015. Gravity Matching Aided Inertial Navigation Technique Based on Marginal Robust Unscented Kalman Filter. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1074227
Modern Language Association (MLA)
Liu, Ming& Chang, Guobin. Gravity Matching Aided Inertial Navigation Technique Based on Marginal Robust Unscented Kalman Filter. Mathematical Problems in Engineering No. 2015 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1074227
American Medical Association (AMA)
Liu, Ming& Chang, Guobin. Gravity Matching Aided Inertial Navigation Technique Based on Marginal Robust Unscented Kalman Filter. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1074227
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074227