Propagation and scattering of electromagnetic waves in low THz band in automotive radar applications

This thesis, firstly, due to the lack of knowledge in influence of harsh outdoor environment on the performance of the low-THz automotive sensors, the investigation has been done to demonstrate the performance of low-THz sensors in the presence of different radome contaminants (mud, oil, grit, etc.) and various weather conditions (rain, snow, fog, etc.) to prove the feasibility of using low-THz frequencies (100 GHz -1 THz) in automotive radar in uncontrolled environmental conditions. Secondarily, this thesis reports and discuss the important and yet unsolved task on automotive surface recognition and shows the possibility of using Low THz radar for road surface classification by exploring the radar signal backscattering from surfaces with different roughness, and finally this thesis demonstrate the novel approach to surface classification based on the analysis of radar images obtained using the low THz imaging radar and demonstrate the advantage of low THz radar for surface discrimination for automotive sensing. The proposed experimental technique in combination with a convolutional neural network provides high surface classification accuracy