Visible to the public "Model calibration for compressive sampling system with non-ideal lowpass filter"Conflict Detection Enabled

Title"Model calibration for compressive sampling system with non-ideal lowpass filter"
Publication TypeConference Paper
Year of Publication2015
AuthorsZhao Yijiu, Long Ling, Zhuang Xiaoyan, Dai Zhijian
Conference Name2015 12th IEEE International Conference on Electronic Measurement Instruments (ICEMI)
Date PublishedJuly
ISBN Number978-1-4799-7071-1
Accession Number16091663
Keywordscalibration, compensation, compensation filter, compressed sensing, compressive sampling, compressive sampling system, digital compensation filter, finite impulse response estimation, FIR estimation, FIR filters, Frequency conversion, Frequency measurement, Frequency modulation, low-pass filters, LPF, Matrix converters, model calibration, model calibration algorithm, modulated wideband converter, multiband sparse, MWC, nonideal analog lowpass filter, probability, pubcrawl170104, signal reconstruction, test signal technique, Wideband

This paper presents a model calibration algorithm for the modulated wideband converter (MWC) with non-ideal analog lowpass filter (LPF). The presented technique uses a test signal to estimate the finite impulse response (FIR) of the practical non-ideal LPF, and then a digital compensation filter is designed to calibrate the approximated FIR filter in the digital domain. At the cost of a moderate oversampling rate, the calibrated filter performs as an ideal LPF. The calibrated model uses the MWC system with non-ideal LPF to capture the samples of underlying signal, and then the samples are filtered by the digital compensation filter. Experimental results indicate that, without making any changes to the architecture of MWC, the proposed algorithm can obtain the samples as that of standard MWC with ideal LPF, and the signal can be reconstructed with overwhelming probability.

Citation Key7494335