An average-phase calibration method for the sensing matrix of a Modulated Wideband Converter

Abstract

As a sub-Nyquist sampling structure based on compressed sensing (CS), a modulated wideband converter (MWC) is used for spectral blind sampling and reconstruction of multiband sparse signals. Sinusoidal signals with known phases have been theoretically used to study the calibration of the sensing matrix of MWC, but in practice, the initial phase of sinusoidal signals is unfortunately difficult to know in advance. Consequently, phase error will exist in the calibrated sensing matrix, which reduces the reconstruction signal-to-noise ratio (RSNR) of the reconstructed signal.In this paper, we first analyze the phase error uncertainty caused by the DC component of the periodic pseudo-random sequence. In addition, an average-phase calibration method based on a 0/1 mixing sequence is proposed to calibrate the sensing matrix. Each column of the sensing matrix is calibrated according to its average phase, which avoids introducing phase error when using sinusoidal signals with arbitrary unknown phases. Comparative experiments are conducted to evaluate the performance of the proposed method in terms of the RSNR and the reconstruction mean squared error (RMSE). The results show that the RSNR obtained by the proposed method is 40 dB, which is close to the signal-to-noise (SNR) of the input RF signal.