Parameter Estimation of LFM Signal Based on RD Compressed Sampling and DFRFT Dictionary

Abstract

Abstract In order to estimate the parameters of linear frequency modulation (LFM) signals directly from compressed sampled data, a method combining random demodulator (RD) and discrete fractional Fourier transform (DFRFT) dictionary is proposed in this manuscript. Firstly, according to the characteristics of LFM signal, the RD system parameters are adjusted to obtain effective compressed sampling data; Then, based on the fractional Fourier transform theory, a DFRFT dictionary is constructed, and sparse representation coefficients are obtained by reconstructing the compressed sampling data through the recovery algorithm and DFRFT dictionary. The signal has the characteristics of impact under the optimal fractional transform order, so the problem of signal parameter estimation can be converted into searching the location of the maximum value of sparse representation coefficients, and the location is determined by parameter optimization algorithm, then the initial frequency and frequency modulation (FM) slope of LFM signal can be estimated. Finally, simulation and real data experiments are carried out to verify that the proposed method not only has a good sparse representation ability for LFM signals, but also can directly be used to estimate the parameter of LFM signals with compressed sampling data.