Hongfeng Pang

Integrated Compensation of Magnetometer Array Magnetic Distortion Field and Improvement of Magnetic Object Localization

A fluxgate magnetometer array for magnetic object localization is designed, where hard-iron and soft-iron magnetic distortion fields are the major factors influencing measurement accuracy. A vector compensation method is proposed to suppress error, in which magnetometer error, misalignment error, and magnetic distortion fields are considered. The experimental system mainly consists of a plane cross magnetometer array, a magnet (to be hard-iron), a steel block (to be soft-iron), and a deployment platform (to change the attitude of the magnetometer array). Experimental results show that integrated compensation parameters can be obtained accurately, and array difference errors are reduced about two orders, thus proving the effectiveness of the vector compensation method. The compensated array is used for static and dynamic localization in 3-D. In static situation, localization errors are reduced from 0.17 m, 0.28 m, and 0.27 m to 0.03 m, 0.05 m, and 0.14 m, respectively. On the object deployment trace, error intensity is reduced from 0.17 to 0.04 m. In particular, the dynamic localization results are unreliable without compensation, and the error intensity is reduced from 2.47 to 0.05 m using the proposed method, thus improving the localization accuracy.

Nonlinear temperature compensation of fluxgate magnetometers with a least-squares support vector machine

Fluxgate magnetometers are widely used for magnetic field measurement. However, their accuracy is influenced by temperature. In this paper, a new method was proposed to compensate the temperature drift of fluxgate magnetometers, in which a least-squares support vector machine (LSSVM) is utilized. The compensation performance was analyzed by simulation, which shows that the LSSVM has better performance and less training time than backpropagation and radical basis function neural networks. The temperature characteristics of a DM fluxgate magnetometer were measured with a temperature experiment box. Forty-five measured data under different magnetic fields and temperatures were obtained and divided into 36 training data and nine test data. The training data were used to obtain the parameters of the LSSVM model, and the compensation performance of the LSSVM model was verified by the test data. Experimental results show that the temperature drift of magnetometer is reduced from 109.3 to 3.3 nT after compensation, which suggests that this compensation method is effective for the accuracy improvement of fluxgate magnetometers.

A New Calibration Method of Three Axis Magnetometer With Nonlinearity Suppression

Nonlinearity is a prominent limitation to the calibration performance of vector magnetometers. A new calibration model is proposed to suppress the nonlinearity of magnetometers and improve calibration performance, in which the nonlinearity coefficients of scale factors are considered. The experimental system mainly consists of a three-axis fluxgate magnetometer (MAG3300), a 2D nonmagnetic rotation equipment, and a proton magnetometer (CZM-3), in which the nonmagnetic rotation equipment is used to change the position of three-axis fluxgate magnetometer, and the scalar value of magnetic field is obtained with the proton magnetometer and considered to be the true value. The principle of this new calibration method is analyzed, and the calibration procedures are introduced. Experimental results show that after nonlinearity suppression, the root-mean-square error of calibration can be reduced by three times. It suggests an effective way to improve the calibration performance of three-axis magnetometers.

Calibration and Compensation of Geomagnetic Vector Measurement System and Improvement of Magnetic Anomaly Detection

The magnetometer error and distortion magnetic field of an inertial navigation system are the major two factors influencing the measurement accuracy of geomagnetic vector information measurement systems. The calibration and compensation methods are proposed in this letter. As a first step, a calibration model for a three-axis magnetometer is established, and a nonlinear least square algorithm is used to estimate thoroughly the error parameters. Then, a distortion compensation model based on relative attitude information is proposed, in which only four groups of attitude information are needed to estimate precisely the distortion parameters. Finally, the whole system is used for magnetic anomaly detection. Experimental results suggest that the magnetometer error can be accurately calibrated, and the magnetic field distortion can be suppressed significantly. After calibration and compensation, the intensity and magnetic anomaly vectors such as west vector, south vector, and vertical vector can be accurately measured by the geomagnetic vector measurement system. It demonstrates that the proposed method can effectively improve the accuracy of the geomagnetic vector measurement system.

Calibration of magnetic gradient tensor measurement array in magnetic anomaly detection

Magnetic anomaly detection based on magnetic gradient tensor has become more and more important in civil and military applications. Compared with methods based on magnetic total field or components measurement, magnetic gradient tensor has some unique advantages. Usually, a magnetic gradient tensor measurement array is constituted by four three-axis magnetometers. The prominent problem of magnetic gradient tensor measurement array is the misalignment of sensors. In order to measure the magnetic gradient tensor accurately, it is quite essential to calibrate the measurement array. The calibration method, which is proposed in this paper, is divided into two steps. In the first step, each sensor of the measurement array should be calibrated, whose error is mainly caused by constant biases, scale factor deviations and nonorthogonality of sensor axes. The error of measurement array is mainly caused by the misalignment of sensors, so that triplets’ deviation in sensors array coordinates is calibrated in the second step. In order to verify the effectiveness of the proposed method, simulation was taken and the result shows that the proposed method improves the measurement accuracy of magnetic gradient tensor greatly.

Calibration of three-axis magnetometer diversionary error based on equipment and LMS adaptive algorithm

Bias of magnetometers and target total value is obtained precisely via calibration equipment. Then, real time calibration weight matrix is obtained using LMS adaptive algorithm. It is proved through experiment that bias is obtained with good stability and accuracy compared with parameter estimation; after calibration, diversionary error is reduced from 33nT to 4nT. Furthermore, diversionary error is calibrated well using a proton magnetometer without rotating the magnetometer over one circle. Experiment results show that it not only reduces diversionary error fluctuation but also eliminates system error compared with other methods.

Subsection various step-size adaptive algorithm and its performance in noise cancelling and magnetometer calibration

Step-size is the most important parameter in LMS adaptive algorithm, which directly influences the performance of adaptive filter. In this paper, filter parameter is theoretically calculated and subsection various step-size (SVSS) is introduced to improve stability of adaptive filter. Simulation results indicate that the new method of SVSS can solve well the contradiction between convergence rate and stability in noise cancelling. Furthermore, SVSS is introduced in calibration of three-axis magnetometer based on simulation and experiment. Obviously, experiment result shows the advantage of SVSS compared with fixed step-size and various step-size (VSS) method.

Magnetic flux modulation with a piezoelectric silicon bridge for 1/f noise reduction in magnetoresistive sensors

Magnetoresistive sensors have plenty of applications in magnetic sensing areas, but magnetic and nonmagnetic 1/f noise severely degrades their low-frequency performances, especially detection sensitivity with hundreds of loss. In this paper, vertical motion flux modulation scheme with a piezoelectric silicon bridge is recommended for 1/f noise reduction, due to its effectiveness, simplicity and stability as well as moderate modulation efficiency. In our prototype sensor, the detection sensitivity was greatly improved to ~80 pT /√Hz at 1 Hz, which was near 300 times upgraded, when the detected magnetic field was transferred up to the resonance frequency of the piezoelectric silicon bridge.

Calibration improvement of three-axis magnetometer in disturbing magnetic circumstance based on FIR digital filter

Ideally, the output total value of three-axis magnetometer is stable at a certain place no matter what direction the three-axis magnetometer is placed. Actually, diversionary error of the three-axis magnetometer can not be avoided. In stable magnetic circumstance, tradional LMS adaptive algorithm is with good performance to calibrate the three-axis magnetometer. Experiment result indicates that diversionary error is decreased from 28 nT to 3.5 nT; but the performance is bad in disturbing magnetic field circumstance. Hence, the new method of combining adaptive filter with FIR digital filter is introduced. Then, advantages of the new method is proved by comparing with traditional LMS adaptive filter. Original diversionary error of three-axis magnetometer is 34.4722 nT in disturbing magnetic field circumstance, which is calibrated to 25.7352 nT using traditional LMS adaptive filter and 2.3502 nT by the new method of combining adaptive filter with FIR digital filter, respectively. Obviously, the method proposed in this paper has better calibration performance in disturbing magnetic circumstance.