Improved Target Detection and Tracking Techniques for Moving Objects with IR-UWB Radar

Abstract

Object detection, localization, and tracking are important for the purposes of rescue, surveillance, and security applications. Generally, these techniques are based on Global Positioning System (GPS), and/or Radar systems. However, in indoor environment, GPS and Radar system cannot apply because they have high error. In recent years, Ultra Wide-band (UWB) has become a possible solution for object detection, localization, and tracking in indoor environment, due to its high range resolution, compact size, and low cost. This thesis work presents the improved target detection and tracking techniques of moving objects with Impulse Radio UWB (IR-UWB) Radar in a short range indoor area. This purpose is archived through several signal processing steps such as: clutter reduction, target detection, and target tracking. In the clutter reduction step, a method using Kalman Filter (KF) is proposed. In the target detection, the modification of conventional CLEAN algorithm is applied. After that, the output is fed up the target localization and tracking step in which the target distance and location will be determined and tracked in 1 dimension and 2 dimensions, respectively. In each step, the proposed and/or modified methods are evaluated in comparison with the conventional methods to show their performances. To evaluate the performances of various methods, the experiments are made with real IR-UWB radar in different scenarios. Then, the raw data are processed with these signal processing steps. The results verify that the proposed methods can improve the probability of target detection and tracking efficiently.