Compressive Sensing and Waveform Design for the Identification of Linear Time-varying Systems Using Noisy Measurements

The application of compressive sensing and waveform design on the estimation of linear time-varying system characteristics using noisy measurements is investigated in this paper. Due to the sparsity of the system’s spreading function representation and the inherent noise in any real-world sensor or measurement device, we propose a new method based on our previous work for identifying narrowband, wideband and dispersive systems using a small set of measurements in the presence of noise. Through numerical simulations, we demonstrate the feasibility and the performance of compressive sensing to estimate the system spreading function.