{'fraction_non_alphanumeric': 0.022170361726954493, 'fraction_numerical': 0.005834305717619603, 'mean_word_length': 5.128571428571429, '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}}
A novel ionospheric clutter mitigation method through time-frequency image processing based on ridgelet analysis

For Ionospheric clutter is non-stationary and very strong, targets submerged in it is too difficult to extract. The detection performance of High Frequency Surface Wave Radar (HFSWR) is influenced. Ridgelet analysis is a tool for analyzing non-stationary signals and can separate lines with different directions and scales in a 2D image. Therefore, this paper presents a new method which applies ridgelet analysis to time-frequency image of radar signal to mitigate the clutter. The results show that this method can mitigate the clutter effectively, and the target submerged in clutter can be extracted well. When the target submerged in clutter and have low signal-to-clutter ratio, about 15∼20dB improvement can be get after the processing.