Compressed Sensing for UWB medical radar applications

UWB has been a very attractive choice for medical radar and localization applications. The use of UWB signals can provide distance measurements with very high accuracy but a big challenge is caused by high attenuation resulting in low signal-to-noise ratios. It is well-known that analog-to-digital conversion is practically not feasible for UWB. Compressed Sensing is an emerging concept which potentially could solve this problem. The weakness of this concept is to handle noisy signals. We propose an implementation strategy to overcome this problem. The hardware implementation and complexity are also taken into account. Simulation results show significant improvements compared to conventional algorithms for both ideal and measured signals.