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Handheld Ground-Penetrating Radar Antenna Position Estimation Using Factor Graphs.
Paweł Słowak1, Tomasz Kraszewski1, Piotr Kaniewski1
1Faculty of Electronics, Military University of Technology, ul. gen. S. Kaliskiego 2, 00-908 Warsaw, Poland.
Sensors (Basel, Switzerland)
|September 19, 2025
Summary
A new factor-graph algorithm significantly improves handheld ground-penetrating radar (HH-GPR) localization accuracy by 30-50% over previous methods. This enhances subsurface imaging and buried object detection.
Area of Science:
- Geophysics
- Geospatial technology
- Robotics and Automation
Background:
- Accurate localization of handheld ground-penetrating radar (HH-GPR) is crucial for effective subsurface imaging and mapping.
- Previous work established a UWB positioning system with an Extended Kalman Filter (EKF) and a proprietary pendulum (PND) dynamics model for high accuracy.
Purpose of the Study:
- To develop and evaluate a factor-graph-based estimation algorithm for enhanced HH-GPR antenna trajectory estimation.
- To improve upon the localization accuracy achieved by the EKF PND method.
Main Methods:
- Modeling the HH-GPR localization system under realistic conditions.
- Implementing and comparing both EKF PND and various factor-graph algorithms.
- Utilizing the sparse matrix representation of factor graphs for efficient iterative solutions.
Main Results:
- The factor-graph approach demonstrated a significant improvement in localization accuracy, ranging from over 30% to almost 50% compared to the EKF PND.
- The sparse matrix representation facilitated an efficient iterative solution for the linearized system.
Conclusions:
- The factor-graph-based algorithm offers superior accuracy for HH-GPR localization compared to the EKF PND method.
- Enhanced positioning accuracy is expected to lead to clearer subsurface images and more reliable identification of buried objects and infrastructure.
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