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This article addresses a novel methodology for the utilization of Field Programmable Gate Array (FPGA) accelerators in on-board Synthetic Aperture Radar (SAR) processing routines. The methodology consists of using High-Level Synthesis (HLS) to create Intellectual property (IP) blocks and using the Reusable Integration Framework for FPGA Accelerators (RIFFA) to develop a Peripheral Component Interconnect express (PCIe) interface between the Central Processing Unit (CPU) and the FPGA, attaining transfer rates up to 15.7 GB/s. HLS and RIFFA reduce development time (between fivefold and tenfold) by using high-level programming languages (e.g., C/C++); moreover, HLS provides optimizations like pipeline, cyclic partition, and unroll. The proposed schematic also has the advantage of being highly flexible and scalable since the IPs can be exchanged to perform different processing routines, and since RIFFA allows employing up to five FPGAs, multiple IPs can be implemented in each FPGA. Since Fast Fourier Transform (FFT) is one of the main functions in SAR processing, we present a FPGA accelerator in charge of the reordering stage of VEC-FFT (an optimized version of FFT) as a proof of concept. Results are retrieved in reversed bit order, and the conventional reordering function may consume more than half of the total clock cycles. Next, to demonstrate flexibility, an IP for matrix transposition is implemented, another computationally expensive process in SAR due to memory access. [ABSTRACT FROM AUTHOR]

The performance of a tracking algorithm considering remotely sensed data strongly depends on a correct statistical description of the data, i.e., its noise model. The objective of this paper is to introduce a new intensity tracking algorithm for synthetic aperture radar (SAR) data, considering its multiplicative speckle/ noise model. The proposed tracking algorithm is discussed regarding the measurement of glacier velocities. Glacier monitoring exhibits complex spatial and temporal dynamics including snowfall, melting, and ice flows at a variety of spatial and temporal scales. Due to these complex characteristics, most traditional methods based on SAR suffer from speckle decorrelation that results in a low signal-to-noise ratio. The proposed tracking technique improves the accuracy of the classical intensity tracking technique by making use of the temporal speckle structure. Even though a new intensity-based matching algorithm is proposed, particularly for incoherent data sets, the analysis of the proposed technique was also performed for correlated data sets. As it is demonstrated, the velocity monitoring can be continuously performed by using the maximum likelihood (ML) texture tracking without any assumption concerning the correlation of the data set. The ML texture tracking approach was tested on ENVISAT-ASAR data acquired during summer 2004 over the Inyltshik glacier in Kyrgyzstan, representing one of the largest alpine glacier systems of the world. It will be demonstrated that the proposed technique is capable of robustly and precisely detecting the surface velocity field and velocity changes in time. Index Terms--Estimation theory, glacier-motion estimation, maximum likelihood (ML) estimation, offset tracking, speckle, synthetic aperture radar (SAR).

This paper presents a methodology to process airborne interferometric synthetic aperture radar (SAR) data to measure surface velocity fields (SVFs) of temperate glaciers, and applies it to data acquired over the Aletsch glacier. The first part of this paper deals with the main limitation in airborne interferometric SAR to retrieve reliable interferometric products, namely, the existence of the so-called residual motion errors--inaccuracies on the order of a few centimeters in the navigation system. An extended multisquint approach is proposed for their estimation in the case of nonstationary scenes. The second part of this paper expounds an efficient methodology to derive SVFs with airborne systems, where the line-of-sight displacement is estimated using differential interferometry and the along-track component by estimating the azimuth coregistration offsets. The necessary steps to finally obtain the 3-D SVF are also presented, as well as the possibility of combining different acquisition geometries. Airborne interferometric SAR data acquired by the Experimental SAR system of the German Aerospace Center over the Aletsch glacier, located in the Swiss Alps, are used to evaluate the performance of the proposed approach. The motion of the corner reflectors deployed in the scene is retrieved with an accuracy between 1 and 5 cm/day using L-band data. Index Terms--Cryosphere, differential synthetic aperture radar (SAR) interferometry (DInSAR), SAR interferometry.

In synthetic aperture radar (SAR) polarimetry, the measured polarimetric signatures are used to analyze physical scattering properties of the imaged media. It is generally assumed that the sensor has a fixed orientation with respect to the objects. However, SAR sensors operating at lower frequencies, like L- and P-band, have a wide azimuth beamwidth, i.e., during the formation of the synthetic aperture, multiple squint angles are integrated to build the full-resolution SAR image. Variations in the polarimetric properties with the azimuthal look angle remain unconsidered. In this paper, a fully polarimetric subaperture analysis method is introduced. Using deconvolution, synthesized SAR images are decomposed into subaperture datasets, which correspond to the scene responses under different azimuthal look angles. A statistical analysis of the polarimetric parameters permits to clearly discriminate media showing a nonstationary behavior during the SAR integration. Finally, a method is proposed, which eliminates the influence of azimuthal backscattering variations in conventional polarimetric SAR data analysis. The effectiveness of the new methods is demonstrated on fully polarimetric SAR data, acquired by the German Aerospace Center (DLR) airborne experimental SAR sensor (E-SAR) at L-band. Index Terms--SAR polarimetry, subaperture processing, Bragg-resonance.

In recent years, differential interferometry using spaceborne synthetic aperture radar (SAR) sensors has become an established technique for detecting and monitoring centimeter-scale detbrmations of the earth's surface, as well as glacier flows and land slides. Although often very efficient, the use of spaceborne SAR data has several drawbacks, namely phase artifacts caused by atmospheric effects and very low coherence due to long data acquisition intervals and the short radar wavelength of the sensor. Most important, current spaceborne sensors are not able to ensure flexible monitoring of critical regions. Airborne sensors may overcome most of the problems mentioned above, but up to now, the operational use of airborne differential SAR interferometry has been prevented by insufficiently accurate motion compensation of the platform. In this letter, first results of airborne differential interferometry using the German Aerospace Center (DLR) experimental SAR system (E-SAR) in the interferometric repeat-pass mode are addressed. This includes an analysis of long-term decorrelation behavior in L-band and, particularly, the correction of residual motion errors in heavily decorrelated interferograms. A first differential interferogram of agricultural and forested areas is presented and analyzed. Index Terms--Airborne, differential interferometry, motion errors, synthetic aperture radar (SAR).

This paper addresses the noise filtering problem for synthetic aperture radar (SAR) interferometric phase images. The phase noise is characterized by an additive noise model. The model is verified with an L-band shuttle imaging radar (SIR)-C interferogram. An adaptive filtering algorithm based on this noise model is developed. It emphasizes filtering noise adaptively according to the local noise level and filtering along fringes using directionally dependent windows. This algorithm is effective, especially for the tightly packed fringes of X-band interferometry. Using simulated and SIR-C/X-SAR repeat-pass generated interferograms, the effectiveness of this filter is demonstrated by its capabilities in residue reduction, adaptive noise filtering, and its ability to filter areas with high fringe rates. In addition, a scheme of incorporating this filtering algorithm in iterative phase unwrapping using a least-squares method is proposed. Index Terms - Interferometric synthetic aperture radar (IF-SAR), phase noise filtering, phase noise modeling, phase unwrapping.