DocumentCode
1754084
Title
A Novel Approach to Measurement Drift Phenomenon in Terrain Aided Navigation
Author
Li, Shidan ; Sun, Liguo ; Li, Xin ; Wang, Desheng
Author_Institution
Dept. Electron. Eng., Tsinghua Univ., Beijing, China
Volume
1
fYear
2011
fDate
28-29 March 2011
Firstpage
559
Lastpage
563
Abstract
Terrain Aided Navigation (TAN) system has been widely used in aerial and underwater vehicles for its autonomy, anti-electromagnetic interference (anti-EMI) and all-weather advantages. TAN system is also a multi-sensor system usually consists of radar altimeter, barometric altimeter, laser scanner, echo sounder, inertial navigation system (INS) and so on. It fuses the information from different sensors to highly improve the positioning accuracy that can not be acquired by a single positioning system, such as INS. However, the positioning accuracy of TAN can be easily affected by the altimeter measurement errors which may caused by atmosphere turbulence or water current. This paper focuses on the effort to overcome the influences of these aspects. We propose a high dimensional measurement drift system model that incorporates measurement bias and drift aspects, which can model the influences above. The recursive Bayesian filter is used for analytic solutions, while a modified SIR particle filter is in charge of numerically calculating the results. The paper also examines the traditional model without measurement drift for comparison. From the simulation results, the positioning accuracy of the measurement drift model has improved by approximate one order of magnitude than the traditional model.
Keywords
interference (signal); radionavigation; aerial vehicles; all-weather advantages; anti-electromagnetic interference; drift aspects; drift phenomenon measurement; high dimensional measurement; measurement bias; terrain aided navigation; underwater vehicles; Atmospheric measurements; Atmospheric modeling; Computational modeling; Mathematical model; Particle filters; Particle measurements; Sea measurements; Measurement Drift Model; Particle Filter; Recursive Bayesian Filter; Terrain Aided Navigation;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Computation Technology and Automation (ICICTA), 2011 International Conference on
Conference_Location
Shenzhen, Guangdong
Print_ISBN
978-1-61284-289-9
Type
conf
DOI
10.1109/ICICTA.2011.151
Filename
5750679
Link To Document