Sensing Accuracy Optimization for Multi-UAV SAR Interferometry with Data Offloading
Mohamed-Amine Lahmeri, Pouya Fakharizadeh, V\'ictor Mustieles-P\'erez, Martin Vossiek, Gerhard Krieger, and Robert Schober

TL;DR
This paper presents an optimization framework for UAV swarms performing multi-baseline InSAR to enhance DEM accuracy, integrating data offloading and joint optimization of formation, velocity, and power for real-time high-precision Earth surface monitoring.
Contribution
It introduces a novel joint optimization approach for UAV formation, velocity, and communication power to improve InSAR sensing accuracy and real-time data transmission.
Findings
Outperforms baseline optimization methods like GAs, SA, and DRL.
Achieves sub-decimeter vertical accuracy in DEM reconstruction.
Demonstrates the effectiveness of coordinated UAV swarms for high-precision Earth observation.
Abstract
The integration of unmanned aerial vehicles (UAVs) with radar imaging sensors has revolutionized the monitoring of dynamic and local Earth surface processes by enabling high-resolution and cost-effective remote sensing. This paper investigates the optimization of the sensing accuracy of a UAV swarm deployed to perform multi-baseline interferometric synthetic aperture radar (InSAR) sensing. In conventional single-baseline InSAR systems, only one synthetic aperture radar (SAR) antenna pair acquires two SAR images from two distinct angles to generate a digital elevation model (DEM) of the target area. However, multi-baseline InSAR extends this concept by aggregating multiple acquisitions from different angles, thus, significantly enhancing the vertical accuracy of the DEM. The heavy computations required for this process are performed on the ground and, therefore, the radar data is…
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Taxonomy
TopicsSynthetic Aperture Radar (SAR) Applications and Techniques · Advanced SAR Imaging Techniques · Arctic and Antarctic ice dynamics
