Sensing Accuracy Optimization for Communication-assisted Dual-baseline UAV-InSAR

Fuente: arXiv
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Main Authors: Lahmeri, Mohamed-Amine, Mustieles-Pérez, Víctor, Vossiek, Martin, Krieger, Gerhard, Schober, Robert
Format: Preprint
Published: 2024
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author Lahmeri, Mohamed-Amine
Mustieles-Pérez, Víctor
Vossiek, Martin
Krieger, Gerhard
Schober, Robert
author_facet Lahmeri, Mohamed-Amine
Mustieles-Pérez, Víctor
Vossiek, Martin
Krieger, Gerhard
Schober, Robert
contents In this paper, we study the optimization of the sensing accuracy of unmanned aerial vehicle (UAV)-based dual-baseline interferometric synthetic aperture radar (InSAR) systems. A swarm of three UAV-synthetic aperture radar (SAR) systems is deployed to image an area of interest from different angles, enabling the creation of two independent digital elevation models (DEMs). To reduce the InSAR sensing error, i.e., the height estimation error, the two DEMs are fused based on weighted averaging techniques into one final DEM. The heavy computations required for this process are performed on the ground. To this end, the radar data is offloaded in real time via a frequency division multiple access (FDMA) air-to-ground backhaul link. In this work, we focus on improving the sensing accuracy by minimizing the worst-case height estimation error of the final DEM. To this end, the UAV formation and the power allocated for offloading are jointly optimized based on alternating optimization (AO), while meeting practical InSAR sensing and communication constraints. Our simulation results demonstrate that the proposed solution can significantly improve the sensing accuracy compared to classical single-baseline UAV-InSAR systems and other benchmark schemes.
format Preprint
id arxiv_https___arxiv_org_abs_2410_18848
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Sensing Accuracy Optimization for Communication-assisted Dual-baseline UAV-InSAR
Lahmeri, Mohamed-Amine
Mustieles-Pérez, Víctor
Vossiek, Martin
Krieger, Gerhard
Schober, Robert
Signal Processing
In this paper, we study the optimization of the sensing accuracy of unmanned aerial vehicle (UAV)-based dual-baseline interferometric synthetic aperture radar (InSAR) systems. A swarm of three UAV-synthetic aperture radar (SAR) systems is deployed to image an area of interest from different angles, enabling the creation of two independent digital elevation models (DEMs). To reduce the InSAR sensing error, i.e., the height estimation error, the two DEMs are fused based on weighted averaging techniques into one final DEM. The heavy computations required for this process are performed on the ground. To this end, the radar data is offloaded in real time via a frequency division multiple access (FDMA) air-to-ground backhaul link. In this work, we focus on improving the sensing accuracy by minimizing the worst-case height estimation error of the final DEM. To this end, the UAV formation and the power allocated for offloading are jointly optimized based on alternating optimization (AO), while meeting practical InSAR sensing and communication constraints. Our simulation results demonstrate that the proposed solution can significantly improve the sensing accuracy compared to classical single-baseline UAV-InSAR systems and other benchmark schemes.
title Sensing Accuracy Optimization for Communication-assisted Dual-baseline UAV-InSAR
topic Signal Processing
url https://arxiv.org/abs/2410.18848