Real-Time Attitude-Independent Three-Axis Magnetometer Calibration for Spinning Projectiles: A Sliding Window Approach

Grandvallet, Bertrand; Zemouche, Ali; Boutayeb, Mohamed; Changey, Sébastien

doi:10.1109/tcst.2012.2237402

Cited by 34 publications

(21 citation statements)

References 17 publications

(20 reference statements)

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“…It must be noted that all the above-mentioned methods are batch-processing methods. Many studies in the literature propose a real-time calibration algorithm for magnetometers, specifically the filtering algorithm, to address the problems in the above-mentioned methods [16,17]. Although the real-time calibration algorithm can estimate the parameters in real time and reduce computational loads, the filtering algorithm is still a biased estimation.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Calibration of Magnetometers Using the RLS/ML Algorithm

Cao

2020

Sensors

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This study presents a new real-time calibration algorithm for three-axis magnetometers by combining the recursive least square (RLS) estimation and maximum likelihood (ML) estimation methods. Magnetometers are widely employed to determine the heading information by sensing the magnetic field of earth; however, they are vulnerable to ambient magnetic disturbances. This makes the calibration of a magnetometer inevitable before it is employed. In this paper, first, a complete measurement error model of the magnetometer is studied, and a simplified model is developed. Then, the real-time RLS algorithm is introduced and discussed in detail, and the unbiased optimal ML is utilized to improve the accuracy of the parameter estimation. The proposed algorithm is advantageous in correcting the parameters in real time and simultaneously obtaining unbiased parameter estimation. Finally, the simulation and experimental results demonstrate that both the accuracy and computational speed of the proposed algorithm is better than those of the widely used bath-processing method. Moreover, the proposed calibration method can be adopted for calibrating other three-axis sensors.

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Section: Introductionmentioning

confidence: 99%

Real-Time Calibration of Magnetometers Using the RLS/ML Algorithm

Cao

2020

Sensors

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“…and the other sensors. Corresponding methods have been widely used in autonomous unmanned aerial vehicle (UAV) system [9], autonomous underwater vehicles (AUV) [10], gun launched munitions [11], etc.…”

Section: Introductionmentioning

confidence: 99%

Compounded Calibration Based on FNN and Attitude Estimation Method Using Intelligent Filtering for Low Cost MEMS Sensor Application

Lei

Guan

2019

Mathematical Problems in Engineering

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Micro electro mechanical system (MEMS) inertial sensors have advantages, including small size and low power consumption. The performances of Micro Inertial measurement unit (IMU), which is composed of MEMS inertial sensors, degrade, and error, will become larger in high dynamic environment. In order to solve the problem, a novel combined calibration method for compensating the deterministic error of MEMS sensors is proposed. Considering the rotation of different sensitive axes in high dynamic and low dynamic environment, the compounded calibration based on fuzzy neural network (FNN) is adopted to identify the coupling coefficients to eliminate the adverse coupling effects between different rotation axes. Furthermore, the self-developed Micro IMU and magnetometer are applied in attitude estimation system. Considering the large attitude error occurred in most cases, the approach utilizing the estimation of error quaternion vector could avoid the calculation error due to inaccurate modeling in the skew symmetric matrix that comprises attitude error vector components. The intelligent Kalman filter (IKF) based on complexity state equation of error quaternion is designed to improve the performance by adjusting the parameters of filter on line. The experimental results show that the proposed approach could have a higher level of stability and accuracy in comparison to other attitude estimation algorithms.

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“…Similar methods based on Two-Step improves the performance using the total least squares method [3], adaptive least squares [4] and maximum likelihood estimation [5]. The abovementioned methods are all batch, which is difficult to implement in some real-time critical applications [6,7]. This paper proposed a real-time calibration algorithm for tri-axial magnetometer.…”

Section: Introductionmentioning

confidence: 99%

“…Ab b Ab b BAn n An B( 6 ) At this time,   , A b is the parameter to be estimated. A can be parameterized as a symmetric matrix with diagonal elements A , B , C and off-diagonal elements D , E , F .…”

mentioning

confidence: 99%

Real-time Calibration Algorithm for Three-axis Magnetometer

Zhao¹,

Lin²,

Zhai³

2016

Proceedings of the 2016 4th International Conference on Electrical &Amp; Electronics Engineering and Computer Science (ICEEECS

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This paper presents a real-time calibration algorithm for tri-axial magnetometer. A non-linear state space model for calibration related parameters is derived by the invariance norm of local geomagnetic field, and cubature Kalman filter (CKF) is used to estimate calibrating parameters in sequential manner, which is more suitable for real-time critical applications. The effectiveness of the algorithm are verified by numerical simulations. The results are compared with the traditional TWO-STEP algorithm, and the corresponding conclusions are obtained.

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Real-Time Attitude-Independent Three-Axis Magnetometer Calibration for Spinning Projectiles: A Sliding Window Approach

Cited by 34 publications

References 17 publications

Real-Time Calibration of Magnetometers Using the RLS/ML Algorithm

Real-Time Calibration of Magnetometers Using the RLS/ML Algorithm

Compounded Calibration Based on FNN and Attitude Estimation Method Using Intelligent Filtering for Low Cost MEMS Sensor Application

Real-time Calibration Algorithm for Three-axis Magnetometer

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