{'fraction_non_alphanumeric': 0.012557077625570776, 'fraction_numerical': 0.0, 'mean_word_length': 5.401459854014599, '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}}
Compressed sensing in array signal processing based on modulated wideband converter

Nyquist theory is a serious obstacle to the wideband signal processing, which has been broken by compressed sensing theory. Modulated wideband converter can sample wideband signals with subNyquist frequency. In array signal processing, to bring down the sampling rate for the wideband signal is especially an essential issue. This paper proposes a new architecture based on modulated wideband converter, which can be used in array wideband signal processing. It makes full use of the parallelism of the modulated wideband converter and the sparsity of the special wideband signal, and the existing algorithms for L-shaped array can be used in the proposed architecture directly. The theoretical analysis and simulations prove its capableness of compressed sensing in array signal processing.