Abstract
Frequency domain image reconstruction algorithms offer significant advantages, especially for applications for which the reconstruction time is crucial. In the frequency domain, image reconstruction can be realized using fast Fourier transformations, reducing the complexity and thus the execution time of the reconstruction algorithm. In this paper, we adopt range migration techniques to reconstruct radar images from numerical and experimental data. The aim is to examine the robustness of the range migration algorithm (RMA) as a function of sampling sparsity under varying noise levels. Considering that sampling at Nyquist rates can be quite challenging for the conventional synthetic aperture radar (SAR) acquisition, we investigate the behavior of the reconstruction algorithm for larger sampling steps.
Original language | English |
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Title of host publication | 2023 34th Irish Signals and Systems Conference, ISSC 2023: proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9798350340570 |
ISBN (Print) | 9798350340587 |
DOIs | |
Publication status | Published - 03 Jul 2023 |
Event | 34th Irish Signals and Systems Conference, ISSC 2023 - Dublin, Ireland Duration: 13 Jun 2023 → 14 Jun 2023 |
Publication series
Name | Irish Signals and Systems Conference (ISSC): Proceedings |
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ISSN (Print) | 2688-1446 |
ISSN (Electronic) | 2688-1454 |
Conference
Conference | 34th Irish Signals and Systems Conference, ISSC 2023 |
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Country/Territory | Ireland |
City | Dublin |
Period | 13/06/2023 → 14/06/2023 |
Keywords
- range migration techniques
- sparse data
- synthetic aperture radar
ASJC Scopus subject areas
- Computer Networks and Communications
- Information Systems
- Signal Processing
- Instrumentation
Fingerprint
Dive into the research topics of 'Fourier-based image reconstruction algorithms for sparse SAR data'. Together they form a unique fingerprint.Student theses
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Real-time signal processing algorithms for computational millimetre-wave radars
Skouroliakou, V. (Author), Yurduseven, O. (Supervisor) & Ngo, H. Q. (Supervisor), Jul 2024Student thesis: Doctoral Thesis › Doctor of Philosophy