An improved detection method of GNSS faults with fractional information divergence

Gao, Zhen; Zhan, Xingqun; Yang, Rong

doi:10.1016/j.asr.2023.08.046

Cited by 6 publications

(2 citation statements)

References 28 publications

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“…Typically, integrity is assessed through the application of an integrity monitoring method, which comprises mainly two components: fault detection and * Author to whom any correspondence should be addressed. exclusion (FDE) and protection levels (PLs) [2][3][4]. The FDE aims to promptly raise alarms when various failure modes occur.…”

Section: Introductionmentioning

confidence: 99%

Integrity monitoring for decentralized redundant IMUs/GNSS integrated navigation system with correlated measurements

Yang,

Zhang,

et al. 2024

Meas. Sci. Technol.

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In the civil aviation system, the Inertial Measurement Unit (IMU)/ Global Navigation Satellite System (GNSS) integrated navigation remains the most effective navigation scheme. Based upon this, the utilization of redundant IMUs and a multi-constellation system can significantly enhance navigation and integrity performance. However, a redundant IMUs/GNSS integrated navigation system is susceptible to more complex failure modes, including GNSS faults (satellite and constellation faults) and IMU fault. Additionally, dealing with correlated measurements between redundant construction presents a challenging issue. Therefore, we propose an integrity monitoring method for decentralized redundant IMUs/GNSS integrated navigation system. This method considers GNSS faults and IMU fault in the integrity monitoring process, specifically designed for decentralized filter construction with redundancy. Furthermore, due to the correlated measurements between redundant filters, optimal fusion coefficients are determined by considering the unbiased estimate and minimizing the trace of covariance of primary filter. An optimal allocation scheme of continuity risk is also established to improve navigation and integrity performance. Simulation results demonstrate the feasibility and effectiveness of the proposed integrity monitoring method. Moreover, in the context of correlated measurements, the integrated navigation system also exhibits superiority.

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Section: Introductionmentioning

confidence: 99%

Integrity monitoring for decentralized redundant IMUs/GNSS integrated navigation system with correlated measurements

Yang,

Zhang,

et al. 2024

Meas. Sci. Technol.

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“…These faults affect the performance of the filter and reduce the navigation and positioning accuracy and robustness of the system [7,8]. Therefore, how to effectively enhance the fault-tolerant of the system becomes the key to improving the navigation and positioning performance of the GNSS/SINS integrated navigation system [9,10].…”

Section: Introductionmentioning

confidence: 99%

A GNSS/SINS fault detection and robust adaptive algorithm based on sliding average smooth bounded layer width

Zhao,

Wang,

Gao

et al. 2024

Meas. Sci. Technol.

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The Global Navigation Satellite System/Strapdown Inertial Navigation System (GNSS/SINS) integrated navigation system is an important technology for UAV measurement and vehicle movement measurement. But in the operational process of the GNSS/SINS integrated navigation system, the Global Navigation Satellite System (GNSS) signal is vulnerable to external interference, resulting in abnormal system measurement data, and system faults. These faults will reduce the navigation and positioning performance of the system and reduce the measurement accuracy of the system. Aiming at this problem, a GNSS/SINS fault detection and robust adaptive algorithm based on sliding average smooth bounded layer width is proposed. The algorithm evaluates the system measurement data based on the innovation residual and incorporates the sliding average filter to design the fault detection function based on the smooth bounded width layer. Accurate detection of system faults using fault detection function. The fault detection function value is used to construct the robust cofactor matrix to correct the measurement error in real-time, to improve the accuracy and robustness of the state estimation. The experimental results show that: The proposed algorithm in the paper compares with two traditional robust adaptive algorithms based on smooth bounded layer fault detection and residual chi-square fault detection. The fault detection rates for small step faults show an increase of more than 44.26% and 9.54%, respectively. Similarly, for slowly varying faults, the fault detection rates exhibit an increase of more than 29.32% and 13.56%, respectively. Throughout the fault, the filtering accuracy demonstrates an increase of more than 16.52% and 15.47%, respectively. The algorithm effectively improves the measurement accuracy of the GNSS/SINS integrated navigation system.

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RTK ramp faults detection and exclusion by the hybrid control chart

Gao,

Zhan,

Yang

2024

Advances in Space Research

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An improved detection method of GNSS faults with fractional information divergence

Cited by 6 publications

References 28 publications

Integrity monitoring for decentralized redundant IMUs/GNSS integrated navigation system with correlated measurements

Integrity monitoring for decentralized redundant IMUs/GNSS integrated navigation system with correlated measurements

A GNSS/SINS fault detection and robust adaptive algorithm based on sliding average smooth bounded layer width

RTK ramp faults detection and exclusion by the hybrid control chart

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