{'fraction_non_alphanumeric': 0.024922118380062305, 'fraction_numerical': 0.0, 'mean_word_length': 5.366336633663367, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
An error calibration method based on BPANN algorithm for three-axis magnetometers

Due to the effects of nonorthogonality, scale factor and zero-shifts, Three-axis Fluxgate Magnetometers (TFMs) with the attitude changes have certain errors. Therefore, it's quite necessary to establish a calibration method to get high precision magnetic information. Back Propagation Artificial Neural Network (BPANN) algorithm is used to correct the system errors of measured data in this paper. The results show that the BPANN method can well calibrate the data error of TFMs. The measuring error of geomagnetic field decreases obviously after calibration.