Prof. Xiaohui Liu Profile

Prof. Xiaohui Liu

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Proceedings Article | 30 December 2024 Paper

A fault detection method based on orthogonality for integrated navigation system

Jing Yu, Pengpeng Li, Zheng Wei, Xiaohui Liu, Weihua Mou

Proceedings Volume 13394, 133940S (2024) https://doi.org/10.1117/12.3052377

KEYWORDS: Detection and tracking algorithms, Navigation systems, Windows, Covariance matrices, Simulations, Signal filtering, Tunable filters, Satellite navigation systems, Covariance, Evolutionary algorithms

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Improving the reliability of integrated navigation systems requires effective fault detection and isolation strategies. In response to false alarms in jump soft fault detection grounded on the orthogonality principle, this study proposes refinements to the approach for data selection within a sliding window. The refined method introduces an improved orthogonality fault detection algorithm, which enhances detection accuracy and reduces the likelihood of false alarms. By harnessing data within the sliding window optimally, the algorithm computes the orthogonal average as the test statistic without necessitating an increase in the sliding window length. Furthermore, by combining the traditional residual chi-square test and extrapolation chi-square test, more precise judgments can be made regarding fault type and occurrence time. Ultimately, through the integration of traditional residual chi-square and residual extrapolation chi-square detection, this methodology enhances fault classification capabilities, reduces false alarm rates, and enables the effective identification of pulse, abrupt, and gradual faults even in scenarios with limited fault signal strength.

Proceedings Article | 19 January 2024 Paper

Enhancing ephemeris accuracy in low earth orbit: a Chebyshev polynomial fitting approach during earth's shadow period

Hao Chen, Zongnan Li, Xiaohui Liu

Proceedings Volume 12980, 129802P (2024) https://doi.org/10.1117/12.3020889

Read Abstract +

Low Earth orbit (LEO) satellites are a key focus in the research and development of next-generation navigation systems. When combined with existing Global Navigation Satellite Systems (GNSS), they can significantly enhance the accuracy, integrity, availability, and anti-jamming capabilities of satellite navigation and positioning services. Broadcast ephemeris, which is essential for providing navigation services, directly impacts user experience. Currently, main stream broadcast ephemeris fitting primarily employs orbital element-based ephemeris models. However, these models are intermittently affected by solar radiation pressure perturbations during satellite entry and exit from the Earth's shadow, which is more frequent due to the shorter orbital periods in LEO. Therefore, this paper investigates the feasibility of using Chebyshev polynomials to fit broadcast ephemeris in LEO. It also addresses issues related to setting Chebyshev polynomial fitting parameters. Experimental analyses are conducted on fitting order, fitting arc length, and selection of fitting point intervals. The results show that the Chebyshev polynomial fitting is more stable than the 22 parameter ephemeris model with orbital elements in the fitting arc segment containing the incoming and outgoing shadows. When the fitting order is25, the fitting time does not exceed 90 minutes, and the fitting accuracy can reach the level of 0.1 millimeters.

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