Assessment of a UAV Radar System for Reconstructing Vertical Structure of Forests by Single Pass

Forests are the most extensive terrestrial ecosystems in the world. Their vertical structure information not only reflects the spatial structure characteristics of forest but also the physiological and ecological processes. The existing studies on forest vertical structure through remote sensing often encounter challenges such as high costs, difficulties in acquiring effective data, or complexities in data processing. In this study, a new technology for detecting vertical structure of vegetation is proposed and validated, which can obtain vertical structure of vegetation by single flight. In order to perform the new technology, a radar system is developed, incorporating a modular design scheme that emphasizes high integration and lightweight characteristics, which was deployed on an Unmanned Aerial Vehicle (UAV) flight platform. It consists of a main control unit, a signal processing unit, and a data recording unit, which weighs only 0.92 kg in total. Meanwhile, a novel algorithm is proposed to reconstruct the vertical structure of targets, effectively addressing critical challenges in UAV radar signal processing, such as strong system coupled signal, significant noise in radar signals, and high sidelobes in images. In order to validating the capability of the new technology, UAV flight experiments as well as in-situ observation were carried out in typical vegetation areas. The proposed algorithm was used to process the acquired radar echoes, yielding a root mean square error (RMSE) of 1.33 m for the vegetation height compared to the ground synchronous measurement.