Design of Short-Range S-band Radar Sensing System for Autonomous Object Classification

Remote environmental and industrial sensing based on multi-spectral or radar imaging today plays an important role in ensuring sustainability and protection of natural resources, in saving time and energy in industry and agriculture, and in many other applications. Numerous examples of such systems exist which provide information like product quality to manufacturers, crops growth parameters to farmers or structural integrity details to civil engineers. With recent developments in electromagnetic millimetre-wave (mm-wave) technology and artificial intelligence implementation, short range mm-wave remote sensing is experiencing strong growth with the market dictating new applications with increasingly higher levels of system autonomy. The objective of this paper is to demonstrate methodology and hardware used in short-range radar sensing and use it to build-up a database of scattering images which will allow us the extraction of key signal parameters for particular objects and subsequently allow autonomous object classification using machine learning principles.