Modeling and Analysis of Ground RCS for UAV Radar

Unmanned Aerial Vehicle (UAV)-borne radar offers a cost-effective and efficient solution for surveying complex, inaccessible terrains. This study evaluates the Radar Cross Section (RCS) characteristics critical for terrain detection using radar echoes across four distinct landform types: plains, forests, hills, and mountains. A computational model for the ground backscattering coefficient ($\sigma^{\boldsymbol{0}}$) is established based on the modified Morchin model, incorporating terrain-specific parameters. Geometrical modeling defines the elliptical radar coverage area on the ground, leading to an analytical expression for RCS as a function of grazing angle ($\alpha$), UAV altitude ($\mathbf{h}$), and radar operating frequency ($\mathbf{f}_{0}$), and beamwidth ($\boldsymbol{\theta}$). Simulation experiments, conducted with initial parameter, reveal the complex relationship between RCS and grazing angle. Analysis shows RCS variation with altitude is slow-growing, while its dependence on frequency shows rapid growth below 20 GHz, slowing thereafter. Furthermore, RCS exhibits a significant dependence on beamwidth ($\theta$), decreasing rapidly as $\theta$ narrows below approximately 2°, with the rate of decrease slowing as $\theta$ increases. The radar equation highlights the critical trade-off involving echo power ($\mathrm{P}_{\mathrm{r}}$), which depends strongly on range and wavelength. Results demonstrate that grazing angle, UAV altitude, radar frequency and beamwidth significantly impact RCS and detectable echo power. These findings provide essential guidance for optimizing UAV radar system parameters to enhance terrain surveying performance in diverse environments.