Design and Development of an RF-SoC-Based Ultra-Wideband Radar for Remote Sensing of Snow

Snow is a crucial element of Earth's climate system, making its monitoring essential for the effective management of global water resources. High-resolution snow measurements are fundamental to climate modeling, hydrology, and water resource management. Currently, global snow monitoring relies on satellite-based remote sensing technologies developed by NASA and ESA. However, these systems face significant limitations in spatial resolution and penetration depth. While ground-based measurements offer high accuracy, their coverage is limited. This dissertation explores the potential of ultra-wideband (UWB) radar integrated with small Unmanned Aircraft Systems (sUAS) to bridge these gaps. The goal is to develop a UWB radar system capable of generating a snow water equivalent (SWE) product from sUAS. The radar operates in both monostatic and bistatic modes, enabling high-resolution data collection over large, kilometer-scale areas. A key contribution of this work is the successful generation of both snow depth and SWE maps over a 1 km² area in Grand Mesa, CO, demonstrating the feasibility of UWB radar-equipped swarm sUAS for large-scale snow remote sensing. Additional contributions of this dissertation include the development of a high-performance linear chirp synthesizer and a data acquisition system to perform monostatic and bistatic radar measurements. The chirp synthesizer enables precise generation of linear frequency modulated chirps with a bandwidth of up to 4.4 GHz. The data acquisition system directly digitizes signals up to 2.2 GHz without the need for downconversion to baseband, preserving signal fidelity while reducing hardware complexity. Additionally, we developed models and data inversion algorithms to extract key geophysical parameters, including snow permittivity, from bistatic radar data. We tested and validated these developments through extensive field deployments in Colorado, including sites near Gothic and Grand Junction. We collected data on snow and processed them to generate high-resolution snow depth maps. By integrating these measurements with density observations derived from our bistatic radar, we produced a SWE map over a large area without the need for extensive in-situ measurements of snow density. The results of this dissertation highlight the potential of UWB radar-equipped sUAS as a scalable and effective solution for high-resolution snow remote sensing.

Grantor dc:publisher

University of Alabama Libraries

Year dc:date.issued

2025

Author dc:creator

• Reyhanigalangashi, Omid

Advisors dc:contributor.advisor

• Taylor, Drew
• Gogineni, Siva-Prasad

Contributors dc:contributor

• Freeborn, Todd
• Jeong, Nathan
• Mulani, Sameer

• Bistatic
• FPGA
• Radar
• Remote Sensing
• Snow
• Snow Water Equivalent

Statement dc:rights

• All rights reserved by the author unless otherwise indicated.

Language dc:language.iso

en_US, English

Dc Identifier Other

1133529

OAI identifier oai:identifier

oai:ir.ua.edu:123456789/16619