A Fault Detection and Exclusion Algorithm using Particle Filters for non-Gaussian GNSS Measurement Noise

• 발행기관: 한국항해항만학회
• 저자명: Youngsun Yun Doyoon Kim Changdon Kee
• 간행물 정보: 『한국항해항만학회 학술대회논문집』2006년도 International Symposium on GPS/GNSS Vol.2, 1~6쪽, 전체 6쪽
• 주제분류: 공학 > 해양공학
• 파일형태: PDF
• 발행일자: 2006.10.25

영문 초록

Safety-critical navigation systems have to provide ‘reliable’ position solutions, i.e., they must detect and exclude measurement or system faults and estimate the uncertainty of the solution. To obtain more accurate and reliable navigation systems, various filtering methods have been employed to reduce measurement noise level, or integrate sensors, such as global navigation satellite system/inertial navigation system (GNSS/INS) integration. Recently, particle filters have attracted attention, because they can deal with nonlinear/non-Gaussian systems. In most GNSS applications, the GNSS measurement noise is assumed to follow a Gaussian distribution, but this is not true. Therefore, we have proposed a fault detection and exclusion method using particle filters assuming non-Gaussian measurement noise. The performance of our method was contrasted with that of conventional Kalman filter methods with an assumed Gaussian noise. Since the Kalman filters presume that measurement noise follows a Gaussian distribution, they used an overbounded standard deviation to represent the measurement noise distribution, and since the overbound standard deviations were too conservative compared to the actual distributions, this degraded the integrity-monitoring performance of the filters. A simulation was performed to show the improvement in performance of our proposed particle filter method by not using the sigma overbounding. The results show that our method could detect smaller measurement biases and reduced the protection level by 30% versus the Kalman filter method based on an overbound sigma, which motivates us to use an actual noise model instead of the overbounding or improve the overbounding methods.

목차

1. Introduction

2. Non-Gaussian GNSS Measurement Noise

3. PARTICLE FILTERS

4. Integrity Monitoring

5. Simulation

6. Conclusion

키워드

FDE Integrity Particle Filter Sigma Overbounding.