Paper
20 August 2010 New filtering method for GPS/INS integrated navigation
Xiao-chun Zhong, Tao Song
Author Affiliations +
Proceedings Volume 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering; 782038 (2010) https://doi.org/10.1117/12.867204
Event: International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 2010, Xi'an, China
Abstract
The error caused by linearization in the filtering process is an important factor that decrease the filtering accuracy, and if the error exceeds the allowable range it may result in filter divergence for some highly nonlinear systems. In the GPS/INS system integrated with position and velocity, though the linearization process is eliminated because of its linear model, the navigation accuracy is degraded by the correlation between the system's measurements. So the integration of range was adopted for observation model, which makes use of the original measurements of GPS, so it can improve the navigation accuracy. As this observation model is nonlinear, for the high accuracy requirement of GPS/INS integrated navigation system, the UPF (Unscented Particle Filter) algorithm was introduced to estimate the system states. The UPF is a nonlinear filer which is more suitable for nonlinear systems. The simulation was carried out under the condition of less than four GPS satellites data available, the results of which show that the estimated values with UPF are quite close to real values, and the UPF algorithm has a very good performance when it applied in the GPS/INS integrated navigation.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiao-chun Zhong and Tao Song "New filtering method for GPS/INS integrated navigation", Proc. SPIE 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 782038 (20 August 2010); https://doi.org/10.1117/12.867204
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KEYWORDS
Navigation systems

Nonlinear filtering

Error analysis

Global Positioning System

Complex systems

Linear filtering

Silicon

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