Modified Adaptive Fusion Scheme for Kalman Filter Based on the Hypothesis Test

Jiang, Chung-Hsiang; Liu, Wenkai; Li, Hui; Xu, Haijun

doi:10.1155/2022/4064339

Cited by 3 publications

(3 citation statements)

References 24 publications

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“…In theory, the factor S k should be inflated if the error of xk−1 is anomalous. A fading filter with an optimal fading factor is proposed and a simplified and applicable fading factor is given [19]:…”

Section: Fading Factormentioning

confidence: 99%

An adaptive robust strategy based on hypothesis testing for satellite clock bias short-term forecasting

Su,

Gao,

et al. 2024

Meas. Sci. Technol.

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The study of short-term forecasting of satellite clock bias is important to promote the development of real-time precise point positioning, and the Kalman filter model has certain advantages over other models in the single forecast model. However, the filtering performance will be degraded by the model bias, and a fading factor is constructed to control the effect brought by the model bias. Considering that the fading factor may cause the covariance matrix to be abnormally inflated or even invalid when the observed information is unreliable, the chi-square test is introduced as a test indicator. At the current epoch moment, the fading factor or robust estimation is conditionally applied based on the result of the hypothesis test. An improved IGGIII weight function is used by the robust estimation, which simplifies the solution of the parametric robust solution. BDS-3 satellite clock bias data with different clock types were selected for the analysis of fitting accuracy and forecasting accuracy, and the experimental results showed that the proposed algorithm can well eliminate the anomalous perturbation phenomenon caused by model deviation and improve the fitting accuracy. The comparison of forecast accuracy between the proposed strategy and GM (1,1), QP, and ARIMA models at 3, 6, and 12-hour intervals reveals that the proposed strategy consistently demonstrates optimal forecast accuracy.

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Section: Fading Factormentioning

confidence: 99%

An adaptive robust strategy based on hypothesis testing for satellite clock bias short-term forecasting

Su,

Gao,

et al. 2024

Meas. Sci. Technol.

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show abstract

“…The calculation of the MD uses covariance to exclude disturbances caused by correlation between variables, which makes it more sensitive to small changes. Thus, the MD can be used to detect outliers in the pseudorange residuals [38,39]. The distribution of the pseudorange residual over a continuous period is usually supposed to be as follows:…”

Section: Robust Algorithm Based On Mahalanobis Distancementioning

confidence: 99%

“…The calculation of the MD uses covariance to exclude disturbances caused by correlation between variables, which makes it more sensitive to small changes. Thus, the MD can be used to detect outliers in the pseudorange residuals [38, 39]. The distribution of the pseudorange residual over a continuous period is usually supposed to be as follows:

{\Delta }{\rho }_{k,k-1}\sim N\left(\mu ,{\sigma }^{2}\right)

where Δ ρ k , k −1 is a vector of pseudorange residual at time [ k , k − 1] that satisfies a Gaussian distribution with mean μ and variance σ 2 .…”

Section: Pseudorange Residual Detection Based On Mahalanobis Distancementioning

confidence: 99%

Robust factor graph optimisation method for shipborne GNSS/INS integrated navigation system

Hu,

Li,

Liu

2023

IET Radar Sonar & Navi

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Robust Global Navigation Satellite System (GNSS) factors are introduced into a factor graph optimisation based integrated navigation system to address the challenge of occluded GNSS signals during ship navigation, which leads to increased errors in positioning results. To enhance the robustness of the GNSS tracking loop, a vector tracking method is applied to receiver tracking loop. Then, the Mahalanobis distance was employed to assess the pseudorange residual and identify and reject signals that exhibit anomalies. Specifically, the pseudorange residual is computed as the difference between the predicted pseudorange of the GNSS receiver and the measured pseudorange. Using the historical information in the window, robust GNSS factors were constructed for use in the factor graph. The robust factor graph optimisation method for a shipborne GNSS/Inertial Navigation System integrated navigation system was implemented by constructing robust GNSS factors and Inertial Measurement Unit factors. The experimental results confirm that the positioning accuracy of the proposed method is superior to those of the factor graph optimization and extended Kalman filter.

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Development and Future Direction of Unmanned System Based on Inertial Integrated Navigation

Zeng

Zhi

et al. 2023

Lecture Notes in Electrical Engineering

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Modified Adaptive Fusion Scheme for Kalman Filter Based on the Hypothesis Test

Cited by 3 publications

References 24 publications

An adaptive robust strategy based on hypothesis testing for satellite clock bias short-term forecasting

An adaptive robust strategy based on hypothesis testing for satellite clock bias short-term forecasting

Robust factor graph optimisation method for shipborne GNSS/INS integrated navigation system

Development and Future Direction of Unmanned System Based on Inertial Integrated Navigation

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