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A Gaussian Sum Filter Approach for DGNSS Integrity Monitoring

Published online by Cambridge University Press:  02 October 2008

Youngsun Yun ,
Ho Yun ,
Doyoon Kim  and
Changdon Kee
Youngsun Yun*
Affiliation:
(Seoul National University, Republic of Korea)
Ho Yun
Affiliation:
(Seoul National University, Republic of Korea)
Doyoon Kim
Affiliation:
(Seoul National University, Republic of Korea)
Changdon Kee
Affiliation:
(Seoul National University, Republic of Korea)
*
(E-mail: zoro@snu.ac.kr)
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Abstract

With conventional snapshot RAIM algorithms, it is difficult to detect small errors and simultaneous multiple faults. Assuming that we know the system dynamics, filtering algorithms, such as the Kalman filter, can provide better integrity-monitoring performance than the snapshot algorithms because the filter reduces the noise level of measurements. However, because the Kalman filter presumes that measurement noise and disturbance follow the Gaussian distribution, its performance might degrade if the assumption is wrong. To address this problem, we propose a fault detection and exclusion algorithm using Gaussian sum filters. Because GNSS measurement noise does not follow the Gaussian distribution perfectly, the Gaussian sum filter can estimate the posterior distribution more accurately; therefore it has better integrity-monitoring performance. This paper describes the detailed algorithms and shows simulation results to evaluate the integrity-monitoring performance of the algorithms. The proposed algorithms detect about 30% smaller faults and generate 35% lower protection levels than the conventional methods. The results show that the proposed algorithms can provide better accuracy and availability performance.

Keywords

Integrity monitoringRAIMGaussian sum filterNon-Gaussian error distribution
Type
Research Article
Information
The Journal of Navigation , Volume 61 , Issue 4 , October 2008 , pp. 687 - 703
Copyright
Copyright © The Royal Institute of Navigation 2008

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References

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