Abstract
In order to calibrate the magnetic measurement system used in guided munition on site, a two-stage calibration (TSC) scheme without reference is proposed in this paper. Analyzing the interfering magnetic field in the projectile and misalignment angles between the projectile coordinate system and measurement coordinate system establishes a proper mathematical equivalent model and derives a calibration method. The first stage is ellipsoid fitting to obtain the equivalent zero-offset, equivalent sensitivity and equivalent non-orthogonal angles of the sensor; the second stage is to calibrate the misalignment angles between the projectile coordinate system and the measurement coordinate system with the three-position calibration (TPC) method. Complete calibration is convenient to operate and does not need an additional reference, which has wide applicability. The simulation results show that the deviation in the measured value after compensation is within 100 nT. The experiment proves that the error of compensated magnetic value is about 150 nT, which meets the accuracy of requirements in guided munitions.
Highlights
In the field of navigation technology, the triaxial magnetic measurement system, with the AMR magnetometer as the core sensor which measures the earth’s magnetic field to obtain precise directional information [1], has been widely applied to vehicle detection [2], resource exploration [3], magnetic anomaly detection and navigation [4,5,6], due to the advantages of using a magnetometer such as small space occupation, fast response speed, good anti-overload performance, low cost, etc. [4,7]; as well, it is used in guided munitions
Hard magnetism and soft magnetism were considered when they established the error model; some necessary components are ignored in the analysis, which cannot be estimated and extra deviations still exist, and the particle swarm optimization algorithm has its disadvantages: the more complex the surrounding environment is, the more samples are needed to describe the posterior probability distribution, and the higher the complexity of the algorithm, the less it is suitable for calibrating magnetic measurement systems on guided munitions on site
According to the analysis above, the calibration process can be decomposed into two stages: calibration of sensor and calibration of measurement system: (1) The first stage is to finish the unitization and orthogonalization of the coordinate system of the sensor; (2) The second stage is to calibrate misalignment angles between the measurement system and projectile coordinate system by the three-position calibration (TPC) method based on the first stage
Summary
In the field of navigation technology, the triaxial magnetic measurement system, with the AMR magnetometer as the core sensor which measures the earth’s magnetic field to obtain precise directional information [1], has been widely applied to vehicle detection [2], resource exploration [3], magnetic anomaly detection and navigation [4,5,6], due to the advantages of using a magnetometer such as small space occupation, fast response speed, good anti-overload performance, low cost, etc. [4,7]; as well, it is used in guided munitions. Yanke Wang proposed a calibration method of magnetometer based on a BP neural network [25]; to improve the training speed and convergence of neural networks, the Levenberg Marquardt backpropagation training algorithm is designed to calibrate the magnetometer This method can effectively reduce the error caused by the change in magnetometer parameters; the measurement error of a magnetometer can be less than 10 nT, the influence of misalignment errors is not considered in their model. Aiming at the various errors of measurement systems and inconvenient conditions, this paper proposes a complete calibration scheme without additional reference and uses ellipsoid fitting based on the Least Square method and TPC method to obtain equivalent parameters and misalignment angles to finish fast calibration for measurement systems on site
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