In this thesis we present a novel method for remote breathing detection using ultra-wideband(UWB) radar. This is a method that does not require any wearable sensors, makingit more comfortable and convenient for users. Furthermore, because of the penetratingcharacteristic of the transmitted signal through materials like walls, our system is usefulin emergency situations such as earthquakes, which require monitoring people who maybe trapped under rubble. In this thesis we present two new convolution-based methodsto extract breathing rate information from the received radar signal. We use two differenttemplate signals to detect a part of the received signal which contains breathing information.Using this information we are able to estimate the frequency of chest displacement.This method was tested on several people who were monitored while lying down on a bed.The subject’s position was determined and breathing rate was estimated. Experimental resultsincluding 20 different subjects are provided, showing that this is a viable method formonitoring breathing rate using a low-power UWB radar.i