Towards Radar Cross-Section-Based Insect Classification Using THz CSAR and Synthetic Training Data

Accurate insect classification is crucial for environmental monitoring and pest control. This study explores the use of terahertz (THz) radar technology for non-invasive and non-contact insect identification. A THz circular synthetic aperture radar (CSAR) system is employed to acquire radar cross-section (RCS) data of insects, enabling the capture of finer details and distinctions of small insects. Digital twins simulation is used as a tool for generating synthetic radar datasets, which will be used in the future to train machine learning models. The experimental results demonstrate the ability of THz radar to resolve fine structural features of insects, offering improved identification capabilities compared to microwave radars.