UAV Formation Optimization for Communication-assisted InSAR Sensing
Interferometric synthetic aperture radar (InSAR) is an increasingly important remote sensing technique that enables three-dimensional (3D) sensing applications such as the generation of accurate digital elevation models (DEMs). In this paper, we investigate the joint formation and communication reso...
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Format | Journal Article |
Language | English |
Published |
12.11.2023
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Abstract | Interferometric synthetic aperture radar (InSAR) is an increasingly important
remote sensing technique that enables three-dimensional (3D) sensing
applications such as the generation of accurate digital elevation models
(DEMs). In this paper, we investigate the joint formation and communication
resource allocation optimization for a system comprising two unmanned aerial
vehicles (UAVs) to perform InSAR sensing and to transfer the acquired data to
the ground. To this end, we adopt as sensing performance metrics the
interferometric coherence, i.e., the local correlation between the two
co-registered UAV radar images, and the height of ambiguity (HoA), which
together are a measure for the accuracy with which the InSAR system can
estimate the height of ground objects. In addition, an analytical expression
for the coverage of the considered InSAR sensing system is derived. Our
objective is to maximize the InSAR coverage while satisfying all relevant
InSAR-specific sensing and communication performance metrics. To tackle the
non-convexity of the formulated optimization problem, we employ alternating
optimization (AO) techniques combined with successive convex approximation
(SCA). Our simulation results reveal that the resulting resource allocation
algorithm outperforms two benchmark schemes in terms of InSAR coverage while
satisfying all sensing and real-time communication requirements. Furthermore,
we highlight the importance of efficient communication resource allocation in
facilitating real-time sensing and unveil the trade-off between InSAR height
estimation accuracy and coverage. |
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AbstractList | Interferometric synthetic aperture radar (InSAR) is an increasingly important
remote sensing technique that enables three-dimensional (3D) sensing
applications such as the generation of accurate digital elevation models
(DEMs). In this paper, we investigate the joint formation and communication
resource allocation optimization for a system comprising two unmanned aerial
vehicles (UAVs) to perform InSAR sensing and to transfer the acquired data to
the ground. To this end, we adopt as sensing performance metrics the
interferometric coherence, i.e., the local correlation between the two
co-registered UAV radar images, and the height of ambiguity (HoA), which
together are a measure for the accuracy with which the InSAR system can
estimate the height of ground objects. In addition, an analytical expression
for the coverage of the considered InSAR sensing system is derived. Our
objective is to maximize the InSAR coverage while satisfying all relevant
InSAR-specific sensing and communication performance metrics. To tackle the
non-convexity of the formulated optimization problem, we employ alternating
optimization (AO) techniques combined with successive convex approximation
(SCA). Our simulation results reveal that the resulting resource allocation
algorithm outperforms two benchmark schemes in terms of InSAR coverage while
satisfying all sensing and real-time communication requirements. Furthermore,
we highlight the importance of efficient communication resource allocation in
facilitating real-time sensing and unveil the trade-off between InSAR height
estimation accuracy and coverage. |
Author | Lahmeri, Mohamed-Amine Vossiek, Martin Schober, Robert Mustieles-Pérez, Victor Krieger, Gerhard |
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BackLink | https://doi.org/10.48550/arXiv.2311.06959$$DView paper in arXiv |
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Snippet | Interferometric synthetic aperture radar (InSAR) is an increasingly important
remote sensing technique that enables three-dimensional (3D) sensing
applications... |
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Title | UAV Formation Optimization for Communication-assisted InSAR Sensing |
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