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At least 37 records · Page 2

Phi-s correlation and dynamic time warping - Two methods for tracking ice floes in SAR images

The authors present two algorithms for performing shape matching on ice floe boundaries in SAR (synthetic aperture radar) images. These algorithms quickly produce a set of ice motion and rotation vectors that can be used to guide a pixel value correlator. The algorithms match a shape descriptor known as the Phi-s curve. The first algorithm uses normalized correlation to match the Phi-s curves, while the second uses dynamic programming to compute an elastic match that better accommodates ice floe deformation. Some empirical data on the performance of the algorithms on Seasat SAR images are presented.

Mcconnell, Ross↗

Digital SAR processing using a fast polynomial transform

A new digital processing algorithm based on the fast polynomial transform is developed for producing images from Synthetic Aperture Radar data. This algorithm enables the computation of the two dimensional cyclic correlation of the raw echo data with the impulse response of a point target, thereby reducing distortions inherent in one dimensional transforms. This SAR processing technique was evaluated on a general-purpose computer and an actual Seasat SAR image was produced. However, regular production runs will require a dedicated facility. It is expected that such a new SAR processing algorithm could provide the basis for a real-time SAR correlator implementation in the Deep Space Network.

Butman, S.↗

Digital SAR processing using a fast polynomial transform

A new digital processing algorithm based on the fast polynomial transform is developed for producing images from Synthetic Aperture Radar data. This algorithm enables the computation of the two dimensional cyclic correlation of the raw echo data with the impulse response of a point target, thereby reducing distortions inherent in one dimensional transforms. This SAR processing technique was evaluated on a general-purpose computer and an actual Seasat SAR image was produced. However, regular production runs will require a dedicated facility. It is expected that such a new SAR processing algorithm could provide the basis for a real-time SAR correlator implementation in the Deep Space Network. Previously announced in STAR as N82-11295

Truong, T. K.↗

Estimation of Bare Surface Soil Moisture and Surface Roughness Parameter Using L-Band SAR Image Data

An algorithm based on a fit of the single-scattering Integral Equation Method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quasi-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well-managed watershed in southwest Oklahoma. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively.

Shi, Jian-Cheng↗

Estimation of Bare Surface Soil Moisture and Surface Roughness Parameter Using L-Band SAR Image Data

An algorithm based on a fit of the single-scattering Integral Equation Method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quad-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by the Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well- managed watershed in southwest Oklahoma. Prior to its application for soil moisture inversion, a good agreement was found between the single-scattering IEM simulations and the L band measurements of SIR-C and AIRSAR over a wide range of soil moisture and surface roughness conditions. The sensitivity of soil moisture variation to the co-polarized signals were then examined under the consideration of the calibration accuracy of various components of SAR measurements. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively.

Shi, Jian-Cheng↗

Robustness of Spann-Wilson segmentation on SAR imagery

The performances of the Spann-Wilson algorithm on simulated synthetic aperture radar (SAR) images with varying degrees of speckle (one to four looks and varying amounts of white noise) is described. One hundred forty-eight test images are considered, of which the algorithm segmented most without any adjustment to the algorithm's parameters. The effect of speckle on fractal boundaries is studied. The effect of varying multiplicative and additive noise distributions for a fixed set of segmentation parameters is examined. The modified Spann-Wilson algorithm on four-look imagery is evaluated.

Daida, Jason M.↗

Synthetic aperture radar target detection, feature extraction, and image formation techniques

This report presents new algorithms for target detection, feature extraction, and image formation with the synthetic aperture radar (SAR) technology. For target detection, we consider target detection with SAR and coherent subtraction. We also study how the image false alarm rates are related to the target template false alarm rates when target templates are used for target detection. For feature extraction from SAR images, we present a computationally efficient eigenstructure-based 2D-MODE algorithm for two-dimensional frequency estimation. For SAR image formation, we present a robust parametric data model for estimating high resolution range signatures of radar targets and for forming high resolution SAR images.

Li, Jian↗

A comparative study of real-time spaceborne synthetic aperture radar processing techniques

A review of various spaceborne synthetic aperture radar (SAR) processing algorithms and their associated real-time SAR processor architectures is given in this paper. The processing complexity for each real-time SAR processor is presented next. A complexity comparison is then given based on the Seasat SAR parameters. It is shown that the frequency/time domain hybrid fast correlation and the two-stage fast Fourier transform (FET) approaches are the two most cost-effective choices for real-time spaceborne SAR processing. Finally, a discussion on future development trends in real-time spaceborne SAR processing is given.

Liu, K. Y.↗

SAR processing based on the exact two-dimensional transfer function

The two-dimensional transfer functions of several synthetic aperture radar (SAR) focusing algorithms are derived considering the spaceborne SAR environments. The formulation includes the factors of the earth rotation and the antenna squint angles. The resultant transfer functions are explicitly expressed in terms of Doppler centroid frequency and Doppler frequency rate, which can be accurately estimated from the SAR data. Point target simulation results show that the algorithm based on the two-dimensional Fourier transformation outperforms the one-dimensional one for processing data acquired from high squint angles. The two-dimensional Fourier transformation approach appears to be a viable and simple solution for the processor design of future spaceborne SAR systems.

Chang, C. Y.↗

Optimal Estimation Of Range And Doppler Centroid In ScanSAR

Algorithm processes synthetic-aperture-radar (SAR) returns into optimal estimates of ranges, pointing angles, and Doppler centroids. Derives radar-beam-pointing angles partly from SAR data. Exploits information available in overlapping regions between adjacent image bursts or, equivalently, between adjacent radar beams corresponding to adjacent image bursts. Range or Doppler centroid obtained from estimate of range or Doppler value at which intensity in one image burst equals that in adjacent burst.

Jin, Michael Y.↗

Automated preprocessing of spaceborne SAR data

An efficient algorithm has been developed for estimation of the echo phase delay in spaceborne synthetic aperture radar (SAR) data. This algorithm utilizes the spacecraft ephemeris data and the radar echo data to produce estimates of two parameters: (1) the centroid of the Doppler frequency spectrum f(d) and (2) the Doppler frequency rate. Results are presented from tests conducted with Seasat SAR data. The test data indicates that estimation accuracies of 3 Hz for f(d) and 0.3 Hz/sec for the Doppler frequency rate are attainable. The clutterlock and autofocus techniques used for estimation of f(d) and the Doppler frequency rate, respectively are discussed and the algorithm developed for optimal implementation of these techniques is presented.

Curlander, J. C.↗

SAR Processing Based On Two-Dimensional Transfer Function

Exact transfer function, ETF, is two-dimensional transfer function that constitutes basis of improved frequency-domain-convolution algorithm for processing synthetic-aperture-radar, SAR data. ETF incorporates terms that account for Doppler effect of motion of radar relative to scanned ground area and for antenna squint angle. Algorithm based on ETF outperforms others.

Chang, Chi-Yung↗

Classification Of Terrain In Polarimetric SAR Images

Two algorithms processing polarimetric synthetic-aperture-radar data found effective in assigning various parts of SAR images to classes representing different types of terrain. Partially automate interpretation of SAR imagery, reducing amount of photointerpretation needed and putting whole interpretation process on more quantitative and systematic basis. First algorithm implements Bayesian classification scheme "supervised" by use of training data. Second algorithm implements classification procedure unsupervised.

Van Zyl, Jakob J.↗

Topographic slope from the SAR interferometric phase gradient

A new algorithm for the direct calculation of topographic slope maps from synthetic aperture radar (SAR) interferograms is presented. The algorithm derives slope maps without first requiring the creation of a digital elevational model (DEM) from the interferogram, thus obviating the need for high SNR in the interferogram and altitude calibration points for the scene. SAR data useful for interferometry has been collected by the Active Microwave Imager on board the ERS-1 satellite, when it was in a short period repeat orbit. Two passes of the radar sensor form a cross-track interferometric baseline. For a point target at some position (x,y,h), the interferometric phase difference phi is proportional to the difference in path lengths for the two sensor positions to the scatterer. Given the phase difference as measured in the complex interferogram and an accurate baseline geometry, the position of the scatterer, most significantly the height h, can be determined through triangulation. The interferometric phase measurement however is known only modulo 2-pi, and hence it is necessary to determine the correct multiple of 2-pi to add to the phase at each point to obtain an estimate of the actual phase with respect to an absolute datum. This phase unwrapping process is required for creating DEM's, and is difficult or impossible for regions of low SNR or SAR image layover. The new algorithm described here derives slope maps without requiring phase unwrapping.

Werner, Charles L.↗

Amazonia Disasters: Assessing Methods for Gold Mining-related Deforestation Detection in Amazonia Using NASA Earth Observations

Artisanal and small-scale gold mining (ASGM) is responsible for a large fraction of deforestation and disturbance in Amazonia. These activities cause severe impacts on the rainforest ecosystem and socioeconomic state of the region. NASA DEVELOP partnered with the Asociación para la Conservación de la Cuenca Amazónica (ACCA), NASA SERVIR Science Coordination Office, and the Spatial Informatics Group to enhance ASGM-related deforestation detection methods. ACCA currently uses the Omnibus Q-test Change Point Detection Algorithm to identify changes in Synthetic Aperture Radar (SAR) monthly-aggregated temporal data from the Sentinel-1 satellite. The team determined the algorithm's accuracy by comparing a stratified random sample of change points against data from January 2019 to June 2020 identified using PlanetScope and Landsat 8 Operational Land Imager (OLI) Earth observations through Collect Earth Online. Our results indicated a users' accuracy of 55% for temporal change detection and producer's and user's accuracies of 99% and 97%, respectively, for detecting when change did not occur. Of the labeled change points, only 19% were due to mining activity. This research can help our partners have a more accurate understanding of where illegal gold mining may be taking place and inform decisions to remediate this activity.

DEVELOP Project Summary↗

Amazonia Disasters: Assessing Methods for Gold Mining-Related Deforestation Detection in Amazonia Using NASA Earth Observations

Artisanal and small-scale gold mining (ASGM) is responsible for a large fraction of deforestation and disturbance in Amazonia. These activities cause severe impacts on the rainforest ecosystem and socioeconomic state of the region. NASA DEVELOP partnered with the Asociación para la Conservación de la Cuenca Amazónica (ACCA), NASA SERVIR Science Coordination Office, and the Spatial Informatics Group to enhance ASGM-related deforestation detection methods. ACCA currently uses the Omnibus Q-test Change Point Detection Algorithm to identify changes in Synthetic Aperture Radar (SAR) monthly-aggregated temporal data from the Sentinel-1 satellite. The team determined the algorithm's accuracy by comparing a stratified random sample of change points against data from January 2019 to June 2020 identified using PlanetScope and Landsat 8 Operational Land Imager (OLI) Earth observations through Collect Earth Online. Our results indicated a users' accuracy of 55% for temporal change detection and producer's and user's accuracies of 99% and 97%, respectively, for detecting when change did not occur. Of the labeled change points, only 19% were due to mining activity. This research can help our partners have a more accurate understanding of where illegal gold mining may be taking place and inform decisions to remediate this activity.

DEVELOP Tech Paper↗

Modified Polar-Format Software for Processing SAR Data

HMPF is a computer program that implements a modified polar-format algorithm for processing data from spaceborne synthetic-aperture radar (SAR) systems. Unlike prior polar-format processing algorithms, this algorithm is based on the assumption that the radar signal wavefronts are spherical rather than planar. The algorithm provides for resampling of SAR pulse data from slant range to radial distance from the center of a reference sphere that is nominally the local Earth surface. Then, invoking the projection-slice theorem, the resampled pulse data are Fourier-transformed over radial distance, arranged in the wavenumber domain according to the acquisition geometry, resampled to a Cartesian grid, and inverse-Fourier-transformed. The result of this process is the focused SAR image. HMPF, and perhaps other programs that implement variants of the algorithm, may give better accuracy than do prior algorithms for processing strip-map SAR data from high altitudes and may give better phase preservation relative to prior polar-format algorithms for processing spotlight-mode SAR data.

Chen, Curtis↗

More-Precise Calibration Of Polarimetric SAR

Algorithm for calibration of polarimetric synthetic-aperture-radar (SAR) data in Stokes-matrix representation more nearly exact. Present algorithm resembles prior algorithm closely, except requires extraction of one additional parameter from high-resolution raw SAR data in scattering-matrix format before compression and transformation to Stokes-matrix format and slight change in subalgorithm compressing those data.

Freeman, Anthony↗