Linear correction method of aeromagnetic gradient detection system error based on global surface attitude swing

Abstract

The aeromagnetic gradient detection system composed of two vector magnetic detectors carried by the Unmanned Aerial Vehicle (UAV) will be affected by error parameters such as non-orthogonality, non-alignment, sensitivity gain, and zero drift. The coupling relationship between these parameters complicates the process of solving the error parameters. Aiming at this problem, a linear calibration model of error parameters is constructed. The model establishes a system of linear equations using the projection relationship between the two vector magnetic sensors. This system of equations simplifies the process of solving the error parameters. To verify the correction effect of the model, a training process of arbitrary shaking of the global surface attitude is proposed to simulate the flight attitude of the UAV. The method has little dependence on the test equipment and has strong environmental adaptability. It can quickly solve the non-alignment error and relative zero drift error parameters on the ground. The actual measurement results show that the calibration effect between the corresponding axes can reach more than 89% under random shaking of an angle of ±20°.