Human Detection and Tracking with UWB radar

University dissertation from Västerås : Mälardalen University

Abstract: As robots and automated machineries are increasingly replacing the manual operations, protecting humans who are working in collaboration with these machines is becoming an increasingly important task. Technologies such as cameras, infra-red and seismic sensors as well as radar systems are used for presence detection and localization of human beings. Among different radar sensors, Ultra Wide Band (UWB) radar has shown some advantages such as providing the distance to the object with good precision and high performance even under adverse weather and lightning conditions. In contrary to traditional radar systems which use a specific frequency and high output power, UWB Radar uses a wide frequency band (>500 MHz) and low output power to measure the distance to the object.The purpose of this thesis is to investigate UWB radar system for protecting humans around dangerous machinery in environments like mines where conditions like dirt, fog, and lack of light cause other technologies such as cameras to have a limited functionality. Experimental measurements are done to validate the hardware and to investigate its constraints.Comparison between two dominant UWB radar technologies is performed: Impulse and M-sequence UWB radar for static human being detection. The results show that M-sequence UWB radar is better suited for detecting the static human target at larger distances. The better performance comes at the cost of higher power usage. Measurements of human walking in different environments is done to measure and compare the background noise and radar reflection of the human body. A human phantom is developed and choice of material and shape for it is discussed. The reflection of the phantom is analyzed and compared with the reflection of a human trunk. Furthermore, the choice of frequency in discerning human beings is discussed.Signal processing algorithms and filters are developed for tracking of the human presence, position and movements. These algorithms contain pre-processing of the signal such as removing the background, detection and positioning techniques.