The MWC efficiently samples and reconstructs sparse wideband, or multiband, signals below the Nyquist rate,without a priori knowledge of their support. However, in some applications, the transmissions composing the wideband signal are known to belong to certain function families, such as CW, pulses with known shapes,chirps… The unknown parameters are the carrier frequencies, delays, amplitudes, scaling factors, symbol rates…
In this project, our goal is to incorporate this a priori knowledge and derive a sampling scheme that allows recovering the unknown parameters while reducing the sampling rate and sensing time.