3D Point Cloud Object Detection for Millimeter Wave Radar : a Synthesis Study

FMCW mmWave radar has suitable characteristics to monitor patients at home in an unobtrusive way. However, difficulties are encountered for 3D point cloud generation due to limited detection performance for crowded realistic indoor environments such as living rooms. Therefore the detection process needs to become more robust. This thesis provides a complete overview of the CFAR object detection method, including the steps and theory behind them. The interdependent relation of computation of the scaling factor with other steps is also clarified. Additionally, an implementation has been developed from radar signal to point cloud, including signal processing, object detection, and a proposed informatively improved post-processing step. Furthermore, to demonstrate the performance of the different interference estimators of the CFAR method for various realistic situations, an experiment has been designed and conducted.