{'fraction_non_alphanumeric': 0.018633540372670808, 'fraction_numerical': 0.002484472049689441, 'mean_word_length': 5.5, '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}}
Advances in subspace eigenanalysis based algorithms: from 1D toward 3D superresolution techniques

An overview of two superresolution methods, MUSIC and ESPRIT, for the ID case is firstly given. Afterwards, an extension of these algorithms to the three-dimensional case is proposed. New formulations for the signal model, data resampling, spatial smoothing method and estimate expression are provided. Although many applications can be considered in the areas of radar and wireless communications, only one of them is detailed: high-resolution radar target imaging. The concluding remarks drawn in the final part of the paper are supported by simulation results performed on synthetic signals and by comparing the proposed methods to the scattering center extraction technique using the Fourier transform.