Sparse sampling of non-stationary signal for radar signal processing

Qiong Wu, Qilian Liang · 2013

Estimating the spectrogram of non-stationary signal relates to many important applications in radar signal processing. In recent years, coprime sampling and array attract attention for their potential of sparse sensing with derivative to estimate autocorrelation coefficients with all lags, which could in turn calculate the power spectrum density. But this theoretical merit is based on the premise that the input signals are wide-sense stationary. In this paper, we take the first step to design coprime sampling algorithm using with non-stationary signal and discuss how to attain the benefits of coprime sampling meanwhile limiting the disadvantages due to lack of observations for estimations.

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