CAREER: OpenGPRxAI: Open-Source, AI-Powered Ground Penetrating Radar Technologies for Real-Time Subsurface Vision

NSF Award Search · 01002627DB NSF RESEARCH & RELATED ACTIVIT · $560,865 · view on nsf.gov ↗

Abstract

This project aims to significantly advance subsurface imaging by developing advanced, open-source, AI-powered ground-penetrating radar (GPR) technologies. GPR is a non-invasive sensing tool that uses electromagnetic waves to detect and visualize objects beneath the surface, making it invaluable for applications such as precision agriculture, defense, archaeology, civil engineering, and planetary exploration. Despite its broad utility, current GPR technologies face significant limitations, including the lack of standardized datasets and the inability of existing AI models to generalize across diverse systems and environments. This project addresses these challenges by creating innovative solutions that will enable real-time, high-resolution subsurface imaging. The outcome of this project is expected to transform how humans and autonomous systems perceive and interact with the subsurface world. The societal benefits of this work are profound: it will support sustainable water management, improve precision agriculture for global food security, enhance humanitarian demining efforts to save lives, and enable safer infrastructure monitoring. Additionally, the project includes a robust education and outreach component, engaging K-12, undergraduate, and graduate students in electromagnetics and AI through hands-on learning experiences. By fostering interdisciplinary collaboration and launching an open-source online platform, the project will create a global hub for sharing GPR datasets, algorithms, and educational resources, driving innovation and expanding access to cutting-edge subsurface sensing technologies. The research of this project will advance GPR technology through four integrated objectives. First, it will develop far-field and near-field GPR domain transfer frameworks to standardize data collected across different systems, addressing the critical bottleneck of data scarcity and incompatibility. Second, it will create a modular, physics-informed deep

Key facts

NSF award ID
2543048
Awardee
University of Wisconsin-Madison (WI)
SAM.gov UEI
LCLSJAGTNZQ7
PI
Haihan Sun
Primary program
01002627DB NSF RESEARCH & RELATED ACTIVIT
All programs
Artificial Intelligence (AI), Antennas and Electromagnetics, CAREER-Faculty Erly Career Dev, RF/Microwave & mm-wave tech
Estimated total
$560,865
Funds obligated
$560,865
Transaction type
Standard Grant
Period
09/01/2026 → 08/31/2031