Title :
Off-the-grid spectral compressed sensing with prior information
Author :
Mishra, Kumar Vijay ; Myung Cho ; Kruger, A. ; Weiyu Xu
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Iowa, Iowa City, IA, USA
Abstract :
Recent research in off-the-grid compressed sensing (CS) has demonstrated that, under certain conditions, one can successfully recover a spectrally sparse signal from a few time-domain samples even though the dictionary is continuous. In this paper, we extend off-the-grid CS to applications where some prior information about spectrally sparse signal is known. We specifically consider cases where a few contributing frequencies or poles, but not their amplitudes or phases, are known a priori. Our results show that equipping off-the-grid CS with the known-poles algorithm can increase the probability of recovering all the frequency components.
Keywords :
compressed sensing; dictionaries; probability; signal sampling; time-domain analysis; CS; dictionary; known-pole algorithm; off-the-grid spectral compressed sensing; probability; spectrally sparse signal recovery; time-domain sampling; Atomic clocks; Compressed sensing; Dictionaries; Estimation; Indexes; Minimization; Signal resolution; basis mismatch; compressed sensing; known poles; matrix completion; spectral estimation;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location :
Florence
DOI :
10.1109/ICASSP.2014.6853749