Study of Low Terahertz Radar Signal Backscattering for Surface Identification.

Area of Science:

• Electromagnetics and Wave Propagation
• Automotive Sensing Technologies
• Materials Science

Background:

• Surface roughness significantly impacts radar signal scattering.
• Millimeter wave (mmWave) and low terahertz (THz) frequencies offer potential for detailed surface analysis.
• Automotive sensing requires advanced methods for accurate surface and object identification.

Purpose of the Study:

• To investigate the scattering of mmWave and low THz signals from surfaces of varying roughness.
• To demonstrate the advantages of low THz radar for automotive surface discrimination.
• To validate the applicability of existing radar scattering models in the low THz range.

Main Methods:

• Experimental measurement of radar responses from four test surfaces at 79 GHz, 150 GHz, 300 GHz, and 670 GHz.
• Estimation of normalized radar cross sections as a function of grazing angle and polarization.
• Utilizing the Fraunhofer criterion to classify backscattering as specular or diffuse.
• Measuring surface permittivity using time-domain spectroscopy for model comparison.

Main Results:

• Accurate measurement of backscattering coefficients demonstrated dependence on signal frequency, polarization, and grazing angle.
• Empirical models for diffuse radar signal scattering, developed for lower frequencies, were found to be accurate for the low THz range.
• The study confirmed the feasibility of extending established scattering models to higher frequencies.

Conclusions:

• Low terahertz radar systems show significant advantages for automotive surface classification and object detection.
• The findings provide crucial reference data for developing remote surface identification systems for autonomous vehicles.
• Accurate surface discrimination using low THz radar can enhance path determination and overall autonomous operation.