{'fraction_non_alphanumeric': 0.01288659793814433, 'fraction_numerical': 0.0, 'mean_word_length': 5.166666666666667, '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}}
Data Fusion Approach Based on High Precision Barometric Altimeter and GPS

In order to ensure the precision flying and the capability of precision approach and landing for small aircraft, a data fusion algorithm of federal Kalman filtering (FKF) based on high precision barometric altimeter and GPS is presented. The model of the data fusion algorithm is analyzed in detail. An improved adaptive filter algorithm is developed to eliminate the oblivious error of GPS data. The preliminary experiment results are given and the results show that the adaptive algorithm is efficient in improving the vertical positioning accuracy. The safety and the reliability of small aircraft in the process of near-enter is improved, which satisfies the landing requirement of civil aviation.