{'fraction_non_alphanumeric': 0.01981132075471698, 'fraction_numerical': 0.0, 'mean_word_length': 5.3532934131736525, '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}}
Multi-Function Radar Work Mode Recognition Based on Encoder-Decoder Model

The multi-function radar (MFR) is capable of transmitting complex signals and achieving beam agility according to different tasks, thus leading to many challenges in the work mode recognition field. This paper, therefore, develops an Encoder-Decoder model based on the gated recurrent units (GRU) network to achieve work mode recognition. It involves the use of the Encoder structure to extract the temporal features and the work mode transition regulations of the intercepted pulse group sequence while leveraging the Decoder structure to decode the features and transition regulations as a part of the input for the next decoding process. Additionally, the label substitution (LS) method is utilized for improving the ability of the Decoder structure to recognize work mode under non-ideal situations. Simulation results show that the proposed method is less sensitive in the presence of non-ideal situations and shares better performance than existing work mode recognition methods.