A Quaternion Scaled Unscented Kalman  Estimator for Inertial Navigation States Determination Using INS/GPS/Magnetometer Fusion

Khoder, Wassim; Jida, Bassem

doi:10.4236/jst.2014.42010

Cited by 6 publications

(2 citation statements)

References 11 publications

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“…In recent years, integrated alignment method has been applied gradually, which includes GPS, magnetometer, odometer, IMU and other sensors (Georgy et al, 2011;Ali and Elsheimy, 2013;Chang et al 2017). With the development of multi-sensor information fusion techniques, MIMU/ GPS/magnetometer integrated navigation system has been widely used in navigation and positioning, which could improve the initial alignment accuracy effectively (Khoder and Jida, 2014). However, magnetometer often causes observation outliers for it is highly susceptible to abnormal interference of unknown magnetic field (Zhou et al 2016), the influence of GPS receiver signal occlusion (Teng et al 2011), and the multi-path effect (Azarbad and Mosavi, 2014), which may produce observation outliers and result in large errors in initial alignment.…”

Section: Introductionmentioning

confidence: 99%

A MIMU/GPS/magnetometer integrated alignment method based on sequential robust estimation

Shida

Jian

et al. 2018

J. Glob. Position. Syst.

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For a micro-electro-mechanical system inertial measurement unit (MEMS-IMU), Global Positioning System (GPS) and magnetometer integrated navigation system, the procedure of initial alignment is a necessity. However, both magnetometer and GPS receiver are susceptible to external complex environment. Outliers in the observations of the two devices are inevitable. In order to reduce the influence of the outliers and improve the initial alignment accuracy, a sequential robust Kalman filter (SRKF) algorithm based on the square dimension of the innovation vector is proposed. The proposed SRKF algorithm can reasonably decrease the contribution of outlier affected elements of the observation vector in an element-wise way. Robust factor, used to suppress the influence of outliers, is constructed according to the Mahalanobis distance and the Chi-square distribution significance level. The results of different simulations and field tests all indicate the feasibility and the effectiveness of the proposed method.

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Section: Introductionmentioning

confidence: 99%

A MIMU/GPS/magnetometer integrated alignment method based on sequential robust estimation

Shida

Jian

et al. 2018

J. Glob. Position. Syst.

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show abstract

“…The low cost inertial navigation systems provide accurate and reliable navigation solutions when they are integrated with aided sensors (GPS, magnetometer) in the filter Q-SUKF [1]. The INS/GPS/MAG integration can be briefly classified as loosely-coupled, tightly-coupled and deeplycoupled.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Fuzzy Logic Quaternion Scaled Unscented Kalman Filtering for Inertial Navigation System, GPS and Magnetometer Sensors Integration

Khoder¹

2014

CSSP

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In this paper, we present a technique based on fuzzy logic to improve the performance of the inertial navigation system integrated with GPS, and magnetometer. The proposed fuzzy technique is primarily used to predict position and velocity measurements during GPS outage signals. As long as the GPS measurements are available, the Q-SUKF of INS/GPS/MAG (MAG: magnetometer) integrated system operates efficiently and provides precise navigation states estimation. Nevertheless, during GPS outage signals, the proposed fuzzy technique is adapted to the Q-SUKF to obtain the (A) (FL) QSUKF (Adaptive Fuzzy Logic Quaternion Scaled Unscented Kalman Filter) in order to correct the degradation of the performance of the algorithm. The adaptive fuzzy logic attributes values to the measurements covariance matrix in order to determine the gain of the filter. It will decrease the measurement noise variance of the Kalman filter and then improves eventually the accuracy of the integrated navigation system states estimation. Finally, an experimental part on the use of the proposed fuzzy technical with the Q-SUKF has been validated. Several GPS outages with duration of 30s have been simulated to study the behavior of the proposed filter. In addition, an initial attitude error of 60 degrees is given in each axis to test the robustness of the filter proposed under large attitude errors. The results of the experimental validation have shown the effectiveness and the significant impact of the (A) (FL) Q-SUKF in the reduction of the drift errors estimation of the position and velocity in case of GPS outages in the tested scenarios.

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Global finite-time stability of delayed quaternion-valued neural networks based on a class of extended Lyapunov–Razumikhin methods

Alsaedi

Kashkynbayev

2022

Cogn Neurodyn

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A Quaternion Scaled Unscented Kalman Estimator for Inertial Navigation States Determination Using INS/GPS/Magnetometer Fusion

Cited by 6 publications

References 11 publications

A MIMU/GPS/magnetometer integrated alignment method based on sequential robust estimation

A MIMU/GPS/magnetometer integrated alignment method based on sequential robust estimation

An Adaptive Fuzzy Logic Quaternion Scaled Unscented Kalman Filtering for Inertial Navigation System, GPS and Magnetometer Sensors Integration

Global finite-time stability of delayed quaternion-valued neural networks based on a class of extended Lyapunov–Razumikhin methods

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