{'fraction_non_alphanumeric': 0.020656136087484813, 'fraction_numerical': 0.001215066828675577, 'mean_word_length': 5.014598540145985, '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}}
ISAR imaging with sparse pulses based on compressed sensing

For the conventional Inverse synthetic aperture radar (ISAR) imaging, the observation durations must be long enough to achieve high cross-range resolution. However, it is often impossible to achieve enough echo samples in cross-range, making the imaging result with poor resolution. Compressed sensing (CS) is a new approach of sparse signals recovered. In this paper, a high resolution ISAR imaging method for sparse pulses based on CS method is presented. It shows that the image of sparse targets can be reconstructed by solving a convex optimization problem based on l1 norm minimization with only a small number of ISAR echo samples. The simulation results show that the CS imaging approach outperforms the range-Doppler one in resolution with limited data.