Performance Improvement of GPS/INS Integrated System Using Allan Variance Analysis

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Kim, Hyunseok; Lee, Jang Gyu; Park, Chan Gook
Issue Date
The 2004 International Symposium on GPS/GNSS, Sydney, Australia 6-8 December 2004
Low cost IMUAllan varianceintegrated GPS/INS system
Because of the sensor noises, the accuracy of a low cost INS deteriorates
very rapidly with time. In the INS, deterministic noises of inertial sensors are
easing compensated, but random noises must be compensated using a
Kalman filter. In this paper, an accurate random noise model of a MEMS
inertial sensor is derived to improve the performance of a low cost INS
integrated system. The Allan variance analysis method is adopted to model
the inertial sensor random noise and then random noise sources are identified
and modelled to design the improved model of low cost INS integrated
system. If the noise model is accurate, then the navigation performance of
newly designed GPS/INS system shows better performance during a GPS
blockage. In order to verify the navigation performance of the newly
designed GPS/INS system, a car navigation test has been carried out in this
research. The test results show a better performance of the improved
GPS/INS system model than that of the old GPS/INS system without the
Allan variance analysis.
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College of Engineering/Engineering Practice School (공과대학/대학원)Dept. of Mechanical Aerospace Engineering (기계항공공학부)Others_기계항공공학부
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