Efficient Interpolation of SAR Images for Coregistration in SAR Interferometry

Selva, J.; López-Sánchez, Juan M.

doi:10.1109/lgrs.2007.895961

Cited by 10 publications

(9 citation statements)

References 14 publications

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“…The relationship between the numerical accuracy and the computational burden has already been analyzed in [6]. For the numerical example in this paper (P = 10, B = 0.82/T ), figure 3 shows the number flops per interpolated point for the proposed and the conventional methods.…”

Section: Computational Burden Versus Accuracymentioning

confidence: 96%

“…The Farrow interpolator in [4] has been recently applied to this interpolation problem in [5], [6]. When compared with the conventional interpolation method in (1), this technique eliminates the need to compute or store any set of functional weights g p (u), and exhibits a smaller computational burden.…”

Section: Interpolation Of One-dimensional Signals By Means Of Thementioning

confidence: 99%

“…This justifies the fact that the proposed method is less complex than the conventional one, even if the functional weights have been pre-computed in the latter. For implementation details see [6]. …”

Section: B Bound For Chebyshev Approximation Assuming a Specific Pulsementioning

confidence: 99%

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Image coregistration in SAR interferometry only by means of arithmetic operations

Selva

López-Sánchez

2007

2007 IEEE International Geoscience and Remote Sensing Symposium

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An alternative interpolation technique for SAR image coregistration in interferometric processing is formulated and described. The proposed algorithm is based on the 1-D Farrow interpolator and, when combined with an adequate implementation, it involves a smaller computational burden than the conventional method and yields high accuracy. Basically, this technique enables to carry out the coregistration without resorting to a set of functional weights, and it only requires arithmetic operations and 2-D FFTs. This paper includes several results and comparisons that confirm its validity: the proposed technique is combined with two different polynomial interpolation procedures (Taylor and Chebyshev); bounds on its interpolation error in the 1-D and 2-D cases are derived; and, additionally, it is tested numerically with a synthetic image.

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Section: Computational Burden Versus Accuracymentioning

confidence: 96%

Section: Interpolation Of One-dimensional Signals By Means Of Thementioning

confidence: 99%

See 1 more Smart Citation

Image coregistration in SAR interferometry only by means of arithmetic operations

Selva

López-Sánchez

2007

2007 IEEE International Geoscience and Remote Sensing Symposium

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“…The approach can be finally useful for interferometric coregistration applications [18,19,55] and also to quickly forming 3D SAR images [56].…”

Section: Conclusion and Future Developmentsmentioning

confidence: 99%

Fast Gpu-Based Interpolation for Sar Backprojection

Capozzoli¹,

Curcio²,

Liseno³

2013

PIER

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Abstract-We introduce and discuss a parallel SAR backprojection algorithm using a Non-Uniform FFT (NUFFT) routine implemented on a GPU in CUDA language.The details of a convenient GPU implementation of the NUFFT-based SAR backprojection algorithm, amenable to further generalizations to a multi-GPU architecture, are also given.The performance of the approach is analyzed in terms of accuracy and computational speed by comparisons to a "standard", parallel version of the backprojection algorithm exploiting FFT + interpolation instead of the NUFFT. Different interpolators have been considered for the latter processing scheme. The NUFFT-based backprojection has proven significantly more accurate than all the compared approach, with a computing time of the same order. An analysis of the computational burden of all the different steps involved in both the considered approaches (i.e., standard and NUFFT backprojections) has been also reported.Experimental results against the Air Force Research Laboratory (AFRL) airborne data delivered under the "challenge problem for SAR-based Ground Moving Target Identification (GMTI) in urban environments" and collected over circular flight paths are also shown.

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“…If a 2D space-domain interpolator is used, a conservative estimate for the interpolation proportionality factor is ¹ int = M r ¢ M ® =10, where M r and M ® are the number of neighbour samples used for the range and angle interpolation, respectively. The advantage of this kind of approache is that the ¹ int does not increase with increasing image sizes, like is the case if interpolators requiring FFTs are used (e.g., Farrow 2D [62], data upsampling + low-order interpolator). Fig.…”

Section: F Computational Burden and Memory Consumptionmentioning

confidence: 99%

Efficient Time-Domain Image Formation with Precise Topography Accommodation for General Bistatic SAR Configurations

Rodríguez-Cassolà

Prats

Krieger

et al. 2011

IEEE Trans. Aerosp. Electron. Syst.

126

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Due to the lack of an appropriate symmetry in the acquisition geometry, general bistatic synthetic aperture radar (SAR) cannot benefit from the two main properties of low-to-moderate resolution monostatic SAR: azimuth-invariance and topography-insensitivity. The precise accommodation of azimuth-variance and topography is a real challenge for efficent image formation algorithms working in the Fourier domain, but can be quite naturally handled by time-domain approaches. We present an efficient and practical implementation of a generalised bistatic SAR image formation algorithm with an accurate accommodation of these two effects. The algorithm has a common structure with the monostatic fast-factorised backprojection (FFBP), and is therefore based on subaperture processing. The images computed over the different subapertures are displayed in an advantageous elliptical coordinate system capable of incorporating the topographic information of the imaged scene in an analogous manner as topography-dependent monostatic SAR algorithms do. Analytical expressions for the Nyquist requirements using this coordinate system are derived. The overall discussion includes practical implementation hints and a realistic computational burden estimation. The algorithm is tested with both simulated and actual bistatic SAR data. The actual data correspond to the spaceborne-airborne experiment between TerraSAR-X and F-SAR performed in 2007 and to the DLR-ONERA airborne experiment carried out in 2003. The presented approach proves its suitability for the precise SAR focussing of the data acquired in general bistatic configurations.

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Efficient Interpolation of SAR Images for Coregistration in SAR Interferometry

Cited by 10 publications

References 14 publications

Image coregistration in SAR interferometry only by means of arithmetic operations

Image coregistration in SAR interferometry only by means of arithmetic operations

Fast Gpu-Based Interpolation for Sar Backprojection

Efficient Time-Domain Image Formation with Precise Topography Accommodation for General Bistatic SAR Configurations

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