caa a22 4500 606206493 CHVBK 20210128101011.0 cr unu---uuuuu 210128e20150201xx s 000 0 eng 10.1007/s00034-014-9859-5 doi (NATIONALLICENCE)springer-10.1007/s00034-014-9859-5 Sub-Nyquist Sampling and Reconstruction Model of LFM Signals Based on Blind Compressed Sensing in FRFT Domain [Elektronische Daten] [Biao Fang, Gaoming Huang, Jun Gao] A novel framework of sub-Nyquist sampling and reconstruction for linear frequency modulation (LFM) radar signals based on the theory of blind compressed sensing (BCS) is proposed. This structure takes LFM signals as a sparse linear combination under an unknown transform order $$p$$ p in fractional Fourier transform (FRFT) domain. First, making good use of energy concentration of LFM signal in the proper FRFT domain, we determine the optimal order $$p$$ p which meets the convergence conditions under subsampling condition. Second, discrete fractional Fourier transform (DFRFT) sparse basis is constructed according to the specific sparse FRFT domain dominated by $$p$$ p . Third, based on the DFRFT basis dictionary, using the random demodulator and block reconstruction algorithm, a LFM signal subsampling and reconstruction system is designed in the framework of BCS theory. With this system, the unknown LFM signal in radar system can be sampled at about 1/8 of Nyquist rate without the knowledge of priori sparse basis, but still can be reconstructed with overwhelming probability. Finally, simulations are taken on verifying the feasibility and efficiency of the proposed method, the novel framework can bring a new way to subsample and reconstruct LFM signals under the environment of non-collaboration. Springer Science+Business Media New York, 2014 Blind compressed sensing (BCS) nationallicence Linear frequency modulated (LFM) nationallicence Fractional Fourier transform (FRFT) nationallicence Sub-Nyquist sampling nationallicence Random demodulator nationallicence Fang Biao College of Electronic Engineering, Naval University of Engineering, Wuhan, People's Republic of China aut Huang Gaoming College of Electronic Engineering, Naval University of Engineering, Wuhan, People's Republic of China aut Gao Jun College of Electronic Engineering, Naval University of Engineering, Wuhan, People's Republic of China aut Circuits, Systems, and Signal Processing Springer US; http://www.springer-ny.com 34/2(2015-02-01), 419-439 0278-081X 34:2<419 2015 34 34 https://doi.org/10.1007/s00034-014-9859-5 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00034-014-9859-5 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Fang Biao College of Electronic Engineering, Naval University of Engineering, Wuhan, People's Republic of China aut NATIONALLICENCE 700 1- Huang Gaoming College of Electronic Engineering, Naval University of Engineering, Wuhan, People's Republic of China aut NATIONALLICENCE 700 1- Gao Jun College of Electronic Engineering, Naval University of Engineering, Wuhan, People's Republic of China aut NATIONALLICENCE 773 0- Circuits, Systems, and Signal Processing Springer US; http://www.springer-ny.com 34/2(2015-02-01), 419-439 0278-081X 34:2<419 2015 34 34