TerraSAR-X SAR products and processing algorithms

Eineder, Michael; Schättler, Birgit; Breit, Helko; Fritz, Thomas; Roth, Achim

doi:10.1109/igarss.2005.1526765

Cited by 15 publications

(12 citation statements)

References 9 publications

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“…[6,18] However, for spotlight SAR, the non-stationary squint angle during the imaging brings varied Doppler centroids along the azimuth which is shown in Figure 2. [12,15,16] Hence, ignoring the variations of azimuth Doppler centroids in interpolation operation will lead to serious residual azimuth interferometric fringes and obvious misregistration decorrelation.…”

Section: Co-registration Related To 2-d Doppler Centroid Estimationmentioning

confidence: 98%

“…u ao x; y ð Þ ¼ u a ðx; yÞ þ Du mod ðx; yÞ (15) where u ao x; y ð Þis the optimized unwrapped phase of the accessory method.…”

Section: Step1: Joint Phase Unwrappingmentioning

confidence: 99%

“…Hereby, the phase differences between two phase unwrapping methods Du mod can be obtained by virtue of polynomial fitting. Finally, optimization will be achieved by adding Du mod to the unwrapped phase of the accessory method u a , which is expressed in (15).…”

Section: Step1: Joint Phase Unwrappingmentioning

confidence: 99%

“…[6,18] However, in spotlight SAR images, obvious linear azimuth Doppler centroids' variation exists. [12,15,16] If ignoring the variation in interpolations, the azimuth spectrum of the SAR data and the spectrum of interpolator will shift incorrectly, which will give rise to residual azimuth phase and misregistration in the registration of slave image. Hereby, the interferogram will have additional azimuth interferometric fringes and misregistration decorrelation.…”

Section: Introductionmentioning

confidence: 96%

“…[13,14] After the launch of TerraSAR-X in 2007, German Aerospace Center (DLR) did lots of work on spotlight SAR imaging and InSAR, which suggested that azimuth Doppler centroids of the spotlight image were varied and spotlight data had good phase coherence. [15][16][17] Despite the excellent characteristics of spotlight SAR, it induces serious problems in conventional interferometry processing. Firstly, additional azimuth interferometric fringes and misregistration decorrelation will be produced by conventional co-registration methods.…”

Section: Introductionmentioning

confidence: 99%

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A novel SAR interferometry processing method in high resolution spotlight SAR

2015

Journal of Electromagnetic Waves and Applications

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Synthetic Aperture Radar Interferometry (InSAR) can produce accurate Digital Elevation Model (DEM), and a novel spotlight SAR can get higher azimuth resolution than conventional strip-map SAR. Hence, the combination of InSAR and spotlight SAR techniques implies the potential to obtain higher resolution DEMs which will show more tiny terrain variations. However, in spotlight InSAR processing, additional azimuth interferometric fringes and misregistration decorrelation will be induced by conventional co-registration methods which ignore azimuth varied Doppler centroids in interpolations. Meanwhile, because interferometric fringes in regions with high resolution terrain variations can easily be damaged by random phase noise, there will generate more unreliable unwrapped phase areas with conventional phase unwrapping methods. To eliminate residual azimuth fringes, misregistration decorrelation and unreliable unwrapped phase areas, this paper firstly proposes a novel spotlight SAR interferometry processing method based on co-registration related to two-dimensional Doppler centroid estimation and joint phase unwrapping, and it is validated by using TerraSAR-X spotlight data. The final generated 4 m × 4 m grid space DEM not only preserves high resolution, but also has low root mean square error and absolute mean error which are less than 3 m with respect to the Google earth DEM.

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Section: Co-registration Related To 2-d Doppler Centroid Estimationmentioning

confidence: 98%

“…u ao x; y ð Þ ¼ u a ðx; yÞ þ Du mod ðx; yÞ (15) where u ao x; y ð Þis the optimized unwrapped phase of the accessory method.…”

Section: Step1: Joint Phase Unwrappingmentioning

confidence: 99%

Section: Step1: Joint Phase Unwrappingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

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A novel SAR interferometry processing method in high resolution spotlight SAR

2015

Journal of Electromagnetic Waves and Applications

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Image acquisition geometry analysis for the fusion of optical and radar remote sensing data

Palubinskas

Reinartz

Bamler

2010

International Journal of Image and Data Fusion

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Modifications in the SIFT operator for effective SAR image matching

Suri

Schwind

Uhl

et al. 2010

International Journal of Image and Data Fusion

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With the increasing availability and rapidly improving the spatial resolution of synthetic aperture radar (SAR) images from the latest and future satellites like TerraSAR-X and TanDEM-X, their applicability in remote sensing applications is set to be paramount. Considering challenges in the field of point feature-based multisensor/multimodal SAR image matching/registration and advancements in the field of computer vision, we extend the applicability of the scale invariant feature transform (SIFT) operator for SAR images. In this article, we have analysed the feature detection, identification and matching steps of the original SIFT processing chain. We implement steps to counter the speckle influence, which deteriorates the SIFT operator performance for SAR images. In feature identification, we evaluate different local gradient estimating techniques and highlight the fact that giving up the SIFT's rotation invariance characteristic increases the potential number of matches when the multiple SAR images from different sensors have been acquired with the same geometrical acquisition parameters. In the feature matching stage, we propose to assist the standard SIFT matching scheme to utilise the SIFT operator capability for effective results in challenging SAR image matching scenarios. The results obtained for SAR images acquired by different sensors using different incidence angles and orbiting directions over both rural and semi urban land cover, highlight the SIFT operator's capability for point feature matching in SAR imagery.

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TerraSAR-X SAR products and processing algorithms

Cited by 15 publications

References 9 publications

A novel SAR interferometry processing method in high resolution spotlight SAR

A novel SAR interferometry processing method in high resolution spotlight SAR

Image acquisition geometry analysis for the fusion of optical and radar remote sensing data

Modifications in the SIFT operator for effective SAR image matching

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