Abstract

To ensure navigation integrity for safety-critical applications, this paper proposes an efficient Fault Detection and Exclusion (FDE) scheme for tightly coupled navigation system of Global Navigation Satellite Systems (GNSS) and Inertial Navigation System (INS). Special emphasis is placed on the potential faults in the Kalman Filter state prediction step (defined as “filter fault”), which could be caused by the undetected faults occurring previously or the Inertial Measurement Unit (IMU) failures. The integration model is derived first to capture the features and impacts of GNSS faults and filter fault. To accommodate various fault conditions, two independent detectors, which are respectively designated for GNSS fault and filter fault, are rigorously established based on hypothesis-test methods. Following a detection event, the newly-designed exclusion function enables (a) identifying and removing the faulty measurements and (b) eliminating the effect of filter fault through filter recovery. Moreover, we also attempt to avoid wrong exclusion events by analyzing the underlying causes and optimizing the decision strategy for GNSS fault exclusion accordingly. The FDE scheme is validated through multiple simulations, where high efficiency and effectiveness have been achieved in various fault scenarios.

Highlights

  • Coupled navigation system of Global Navigation Satellite Systems (GNSS)/InertialNavigation System (INS) is widely acknowledged as a suitable navigation solution for civil and military aircraft, aerial photogrammetry, Unmanned Aerial Vehicle (UAV), and Mobile MappingSystems (MMS) [1]

  • Theoretical analyses quantitatively reveal the different effects of GNSS faults and filter fault on the filter, which motivates the design of an effective Fault Detection and Exclusion (FDE) scheme to handle these faults independently

  • This paper presents a comprehensive Fault Detection and Exclusion (FDE) scheme for tightly coupled navigation system of Global Navigation Satellite Systems (GNSS)/Inertial Navigation System coupled navigation system of Global Navigation Satellite Systems (GNSS)/Inertial Navigation (INS), with special emphasis on the fault in state prediction

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Summary

Introduction

All the recursive effects of the undetected faults occurring previously are represented by FF. Where bG denotes the GNSS fault vector and b y is the vector of the bias in INS-derived navigation solution (i.e., FF). Both bG and b y represents the effects of various faults on current-time innovations and state estimates. Equation (17) illustrates the effects of noises and faults on the innovations and lays the foundation of the design of FDE schemes. Their effects on the navigation solution are given in Appendix A

Then two-step exclusiona algorithm presented in Section
Error Analysis of Tight Integration Model
Fault Analysis of Tight Integration Model
Fault Detection Based on AIME
Enhanced AIME Scheme Based on Fault Grouping
Alternative Hypotheses and Statistics for GNSS Fault Exclusion
Complete
Decision Strategy for GNSS Fault Exclusion
Results
Filter Recovery After GNSS Fault Exclusion
Simulation Description
Fault Detection Based on AIME and FG-AIME
Simulated
Fault detection for faults in both SV-1
Notes for Figures
10. Statistics
12. Reciprocal
13. Chi-squared
14. Estimation
Conclusions
Conclusions and Prospects
Methods
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