DroneSAR
UAV Synthetic Aperture Radar
Design and development of an S-band UAV SAR system for high-resolution agricultural remote sensing and field-scale mapping.
Radar · Remote Sensing · Navigation
Weihang (Leo) Li
Ph.D. Candidate in Aeronautics and Astronautics · Purdue University
I develop sensing and estimation methods for Earth observation and positioning, with a focus on UAV-based synthetic aperture radar (SAR), microwave remote sensing, GNSS/signals of opportunity, and multi-sensor navigation.
About
I am a Ph.D. candidate in Purdue University's School of Aeronautics and Astronautics and a member of the Radio Navigation Laboratory. My work connects instrumentation, signal processing, geospatial products, and estimation methods for both Earth remote sensing and positioning applications.
I lead the DroneSAR effort, an S-band UAV-based synthetic aperture radar platform for high-resolution agricultural remote sensing. My research spans radar calibration, SAR image formation, georeferencing, field experiments, and soil-moisture retrieval. I have also contributed to SNOOPI, CYGNSS, and related signals-of-opportunity remote sensing efforts.
My industry experience spans location technology and sensor fusion at Qualcomm, GNSS system development at Samsung Semiconductor, and semiconductor dry-etch process development at Micron Technology. These roles have given me experience carrying modeling, simulation, sensing, and data-analysis methods into product-oriented engineering environments.
Featured Projects
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Retrieval
Soil Moisture Products
Turning calibrated radar observations into geophysical products through retrieval models, uncertainty-aware estimation, and field validation.
SoOp / GNSS-R
Signals of Opportunity
Remote sensing using existing communication and navigation transmissions, including CubeSat-scale sensing concepts such as SNOOPI.
Industry Experience
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2026 · Santa Clara, CA
Position Engineer, Location Tech
Sensor fusion using VIO, IMU, and GNSS for mobile and extended-reality positioning, together with sensor noise and error characterization.
2023 · San Jose, CA
SoC Location System Engineer
Modeled TCXO phase noise and evaluated its impact on GNSS acquisition, signal quality, and tracking-loop stability.
2022 · Boise, ID
Dry Etch Process Development Engineer
Worked on DRAM/HRAM dry-etch process development, including word-line metal process studies, data analysis, and machine-learning-based etch-rate estimation.
Project Spotlight
Featured media
DroneSAR Demo
A short demonstration video of the DroneSAR platform and field operation context. This project integrates the radar, UAV platform, calibration workflow, SAR processing chain, and downstream science products.
Research Focus
UAV Synthetic Aperture Radar
Low-altitude S-band SAR systems, calibration, motion compensation, image formation, and georeferenced radar products.
Microwave Remote Sensing
Retrieval of soil moisture and vegetation properties from high-resolution radar observations for precision agriculture.
GNSS & Signals of Opportunity
GNSS reflectometry and passive/bistatic sensing concepts including SNOOPI and related Earth-observation applications.
Navigation & Sensor Fusion
Probabilistic estimation and fusion of complementary navigation sensors, including GNSS and visual-inertial information.
Recent News
View publications →Aug 2026
Second Place, IEEE IGARSS Student Prize Paper Award. Recognized for “Soil Moisture Retrieval from a UAV-based S-Band Synthetic Aperture Radar in Bare Agricultural Fields.”
Aug 2026
Presented UAV-SAR and soil-moisture retrieval research at IEEE IGARSS 2026, including an oral Student Prize Paper presentation and a Bayesian retrieval poster.
Summer 2026
Joined Qualcomm as a Location Technology Intern, working in the broader area of positioning, location technology, and sensor fusion.
2025
Presented DroneSAR work on UAV-based synthetic aperture radar for soil-moisture remote sensing at IEEE IGARSS and Purdue's Symposium on Digital Agriculture.
2024
Co-authored the SNOOPI mission paper in Advances in Space Research, describing P-band signals-of-opportunity remote sensing from a CubeSat.
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