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Predictive Quantization for Data Volume Reduction in Staggered SAR Systems

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/
Document Type:Article
Title:Predictive Quantization for Data Volume Reduction in Staggered SAR Systems
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Martone, MicheleMichele.Martone (at) dlr.dehttps://orcid.org/0000-0002-4601-6599
Gollin, NicolaNicola.Gollin (at) dlr.dehttps://orcid.org/0000-0003-0477-3273
Villano, MichelangeloMichelangelo.Villano (at) dlr.dehttps://orcid.org/0000-0002-1769-6927
Rizzoli, PaolaPaola.Rizzoli (at) dlr.dehttps://orcid.org/0000-0001-9118-2732
Krieger, GerhardGerhard.Krieger (at) dlr.dehttps://orcid.org/0000-0002-4548-0285
Date: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 - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Tandem-L Vorstudien
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:27 Feb 2020 16:43

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