Martone, Michele and Gollin, Nicola and Villano, Michelangelo and Rizzoli, Paola and Krieger, Gerhard (2020) Predictive Quantization for Data Volume Reduction in Staggered SAR Systems. IEEE Transactions on Geoscience and Remote Sensing, pp. 1-13. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/TGRS.2020.2967450. ISSN 0196-2892.
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Official URL: https://ieeexplore.ieee.org/document/9007611
Abstract
Staggered synthetic aperture radar (SAR) is an innovative SAR acquisition concept which exploits digital beamforming (DBF) in elevation to form multiple receive beams and continuous variation of the pulse repetition interval to achieve high-resolution imaging of a wide continuous swath. Staggered SAR requires an azimuth oversampling higher than an SAR with constant pulse repetition interval (PRI), which results in an increased volume of data. In this article, we investigate the use of linear predictive coding, which exploits the correlation properties exhibited by the nonuniform azimuth raw data stream. According to this, the prediction of each sample is calculated onboard as a linear combination of a set of previous samples. The resulting prediction error is then quantized and downlinked (instead of the original value), which allows for a reduction of the signal entropy and, in turn, of the onboard data rate achievable for a given target performance. In addition, the a priori knowledge of the gap positions can be exploited to dynamically adapt the bit rate allocation and the prediction order to further improve the performance. Simulations of the proposed dynamic predictive block-adaptive quantization (DP-BAQ) are carried out considering a Tandem-L-like staggered SAR system for different orders of prediction and target scenarios, demonstrating that a significant data reduction can be achieved with a modest increase of the system complexity.
Item URL in elib: | https://elib.dlr.de/134246/ | ||||||||||||||||||||||||
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Document Type: | Article | ||||||||||||||||||||||||
Title: | Predictive Quantization for Data Volume Reduction in Staggered SAR Systems | ||||||||||||||||||||||||
Authors: |
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Date: | 24 February 2020 | ||||||||||||||||||||||||
Journal or Publication Title: | IEEE Transactions on Geoscience and Remote Sensing | ||||||||||||||||||||||||
Refereed publication: | Yes | ||||||||||||||||||||||||
Open Access: | Yes | ||||||||||||||||||||||||
Gold Open Access: | No | ||||||||||||||||||||||||
In SCOPUS: | Yes | ||||||||||||||||||||||||
In ISI Web of Science: | Yes | ||||||||||||||||||||||||
DOI: | 10.1109/TGRS.2020.2967450 | ||||||||||||||||||||||||
Page Range: | pp. 1-13 | ||||||||||||||||||||||||
Publisher: | IEEE - Institute of Electrical and Electronics Engineers | ||||||||||||||||||||||||
ISSN: | 0196-2892 | ||||||||||||||||||||||||
Status: | Published | ||||||||||||||||||||||||
Keywords: | Staggered synthetic aperture radar (SAR), block adaptive quantization (BAQ), data volume reduction, linear predictive coding. | ||||||||||||||||||||||||
HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||||||||||||||
HGF - Program: | Space | ||||||||||||||||||||||||
HGF - Program Themes: | Earth Observation | ||||||||||||||||||||||||
DLR - Research area: | Raumfahrt | ||||||||||||||||||||||||
DLR - Program: | R EO - Earth Observation | ||||||||||||||||||||||||
DLR - Research theme (Project): | R - Vorhaben Tandem-L Vorstudien (old) | ||||||||||||||||||||||||
Location: | Oberpfaffenhofen | ||||||||||||||||||||||||
Institutes and Institutions: | Microwaves and Radar Institute > Spaceborne SAR Systems Microwaves and Radar Institute > Radar Concepts | ||||||||||||||||||||||||
Deposited By: | Martone, Michele | ||||||||||||||||||||||||
Deposited On: | 27 Feb 2020 16:43 | ||||||||||||||||||||||||
Last Modified: | 18 Feb 2022 17:38 |
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