2021 IEEE Radar Conference (RadarConf21) 2021
DOI: 10.1109/radarconf2147009.2021.9455209
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First experimental results on multi-angle DVB-S based passive ISAR exploiting multipolar data

Abstract: This work investigates the potentialities of a passive multidimensional ISAR imaging based on DVB-S transmitters of opportunity. Image fusion methods exploiting diversities in both the spatial and polarimetric domains are introduced, aiming at achieving an image with better quality than the images acquired by the individual observation angles and/or polarimetric channels. An analysis using experimental datasets comprising a passive receiver able to collect signals in both the horizontal and vertical polarizati… Show more

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Cited by 6 publications
(5 citation statements)
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“…Previous investigations using BPA for passive ISAR assumed an exact knowledge of the target motion, [9], [19], [20]. Although the obtained results showed its potentials for passive ISAR imaging, the assumption of perfect knowledge of the target motion was clearly unrealistic.…”
Section: Introductionmentioning
confidence: 81%
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“…Previous investigations using BPA for passive ISAR assumed an exact knowledge of the target motion, [9], [19], [20]. Although the obtained results showed its potentials for passive ISAR imaging, the assumption of perfect knowledge of the target motion was clearly unrealistic.…”
Section: Introductionmentioning
confidence: 81%
“…Indeed, DVB-S spectrum is densely populated by multiple channels with little gaps, which can be combined to enhance the range resolution [8]. Moreover, signals with both horizontal and vertical polarizations states are available, thus providing further degrees-of-freedom to enrich the image's information space [9], [19].…”
Section: B Dvb-s Based Passive Isarmentioning
confidence: 99%
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“…In addition to the multiangle illumination with spatial diversity, these novel illuminators of opportunity also allow the application of polarimetric methods. Both the multiangle illumination and polarisation information may improve the target classification performance of the system [30].…”
Section: Capabilities and Challengesmentioning
confidence: 99%