{'fraction_non_alphanumeric': 0.020682523267838676, 'fraction_numerical': 0.0, 'mean_word_length': 5.285714285714286, '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}}
The Research on Sparse Decomposition of AIS Realtime Signal

To utilize the existing Automatic Identification System (AIS) as an additional backup land-based positioning system is a cutting-edge research topic. One of the technical problems that need to be solved is the carrier measurement. Since the non-periodicity of AIS signal, the sparse representation is used to reconstruct the AIS real-time signal to obtain the carrier information. In this paper, based on the characteristics of AIS signal and the requirements of AIS real-time signal processing, for the adaptive redundant dictionary based on the K-SVD algorithm, two sparse decomposition algorithms were compared in terms of signal processing time, sparse representation accuracy, error rate and noise impact. The experiment results indicate that both of the two methods can effectively and accurately reconstruct the AIS signal, thereby laying the foundation for realizing the measurement of AIS carrier.