UWB radar echo signal detection based on compressive sensing

Abstract

Ultra-wideband (UWB) technology has been widely utilized in radar system because of the advantage of the ability of high spatial resolution and object-distinction capability. A major challenge in UWB signal processing is the requirement for very high sampling rate under Shannon-Nyquist sampling theorem which exceeds the current ADC capacity. Recently, new approaches based on the Finite Rate of Innovation (FRI) allow significant reduction in the sampling rate. A system for sampling UWB radar echo signal at an ultra-low sampling rate and the estimation of time-delays is presented in the paper. An ultra-low rate sampling scheme based on FRI is applied, which often results in sparse parameter extraction for UWB radar signal detection. The parameters such as time-delays are estimated using the framework of compressed sensing based on total-variation norm minimization. With this system, the UWB radar signal can be accurately reconstructed and detected with overwhelming probability at the rate much lower than Nyquist rate. The simulation results show that the proposed method is effective for sampling and detecting UWB radar signal at an ultra-low sampling rate.