The gridded trihedral: a new polarimetric SAR calibration reflector

The characteristics of the gridded trihedral used to calibrate polarimetric synthetic-aperture radar (SAR) systems are considered. The gridded trihedral is a normal trihedral with one of the conducting faces replaced with a grid of closely spaced (relative to a wavelength) parallel conductors over a layer of microwave absorber. This grid changes the incident wave's polarization and results in a calibration target with a significant cross-polarized reflection. The advantages of the gridded trihedral are that it has a broad backscatter beamwidth (unlike the dihedral), and that it is passive and simple to construct (unlike the active radar calibrator, or ARC). The performance characteristics of the gridded trihedral reflector are reviewed, using basic theoretical models and calibrated P-3 SAR imagery     

On the accuracy of crosstalk calibration of polarimetric SAR usingnatural clutter statistics

A method for the routine correction of fully polarimetric synthetic-aperture radar (SAR) images proposed by J.J. van Zyl (1990) uses assumed statistical properties of natural distributed targets. The method has the potential to improve dramatically the accuracy of polarimetric imagery contaminated by antenna crosstalk and may be of importance for future spaceborne polarimetric SARs as well as current airborne systems. The accuracy of the method is assessed when the statistics of clutter deviate from the assumed form, and limits are placed on likely acceptable deviations. These statistics are studied for a heterogeneous forestry and agricultural scene imaged by the NASA/JPL radar. The only significant deviations were found over certain man-made targets, including villages, and a single agricultural field. The results lend support to the routine use of the van Zyl method in such applications     

Calibration of a polarimetric imaging SAR

Calibration using point targets is discussed. The fourport network calibration technique is used to describe the radar error model. The processor ambiguity function and the radar distortion matrices are combined to form a generalized polarimetric ambiguity function. The polarimetric ambiguity function of the SAR is found using a single point target, namely a trihedral corner reflector. Based on the resultant polarimetric ambiguity function, an estimate for the backscattering coefficient of the terrain is found using a modified version of the single target calibration technique (STCT). A radar image recorded by the JPL aircraft SAR, which includes a variety of point targets, is used for verification of the new calibration method. The calibrated responses of the point targets are compared both with theory and responses based on the POLCAL technique     

Single-baseline polarimetric SAR interferometry

Examines the application of single-baseline polarimetric SAR interferometry to the remote sensing and measurement of structure over forested terrain. For this, a polarimetric coherent scattering model for vegetation cover suitable for the estimation of forest parameters from interferometric observables is introduced, discussed and validated. Based on this model, an inversion algorithm which allows the estimation of forest parameters such as tree height, average extinction, and underlying topography from single-baseline fully polarimetric interferometric data is addressed. The performance of the inversion algorithm is demonstrated using fully polarimetric single baseline experimental data acquired by DLR's E-SAR system at L-band     

Unsupervised terrain classification preserving polarimetric scattering characteristics

In this paper, we proposed an unsupervised terrain and land-use classification algorithm using polarimetric synthetic aperture radar data. Unlike other algorithms that classify pixels statistically and ignore their scattering characteristics, this algorithm not only uses a statistical classifier, but also preserves the purity of dominant polarimetric scattering properties. This algorithm uses a combination of a scattering model-based decomposition developed by Freeman and Durden and the maximum-likelihood classifier based on the complex Wishart distribution. The first step is to apply the Freeman and Durden decomposition to divide pixels into three scattering categories: surface scattering, volume scattering, and double-bounce scattering. To preserve the purity of scattering characteristics, pixels in a scattering category are restricted to be classified with other pixels in the same scattering category. An efficient and effective class initialization scheme is also devised to initially merge clusters from many small clusters in each scattering category by applying a merge criterion developed based on the Wishart distance measure. Then, the iterative Wishart classifier is applied. The stability in convergence is much superior to that of the previous algorithm using the entropy/anisotropy/Wishart classifier. Finally, an automated color rendering scheme is proposed, based on the classes' scattering category to code the pixels to resemble their natural color. This algorithm is also flexible and computationally efficient. The effectiveness of this algorithm is demonstrated using the Jet Propulsion Laboratory's AIRSAR and the German Aerospace Center's (DLR) E-SAR L-band polarimetric synthetic aperture radar images.     

Knowledge-based classification of polarimetric SAR images

In preparation for the flight of the Shuttle Imaging Radar-C (SIR-C) on board the Space Shuttle in the spring of 1994, a level-1 automatic classifier was developed on the basis of polarimetric SAR images acquired by the JPL AirSAR system. The classifier uses L- and C-Band polarimetric SAR measurements of the imaged scene to classify individual pixels into one of four categories: tall vegetation (trees), short vegetation, urban, or bare surface, with the last category encompassing water surfaces, bare soil surfaces, and concrete or asphalt-covered surfaces. The classifier design uses knowledge of the nature of radar backscattering from surfaces and volumes to construct appropriate discriminators in a sequential format. The classifier, which was developed using training areas in a test site in Northern Michigan, was tested against independent test areas in the same test site and in another site imaged three months earlier. Among all cases and all categories, the classification accuracy ranged between 91% and 100%     

A general polarimetric radar calibration technique

A polarimetric radar calibration procedure is introduced and verified with experimental results. The procedure requires measurements of three known targets in order to determine the distortion matrices that characterize the effect of the measurement system on the transmitted and received waves. The scattering matrices for the known targets can be of any form, provided that a limited set of constraints is satisfied. A special case, wherein the transmit and receive distortion matrices are the transpose of each other, is considered. This case is useful for some single antenna systems and has the advantage that only two known targets are required     

Phase calibration of polarimetric radar images

The problem of phase calibration between polarization channels of an imaging radar is studied. The causes of various types of phase errors due to the radar system architecture and system imperfections are examined. A simple model is introduced to explain the spatial variation in phase error as being due to a displacement between the phase centers of the vertical and horizontal antennas. It is also shown that channel leakage can cause a spatial variation in phase error. Phase calibration using both point and distributed ground targets is discussed and a method for calibrating phase using only distributed target is verified, subject to certain constraints. Experimental measurements using the NADC/ERIM P-3 synthetic-aperture radar (SAR) system and NASA/JPL DC-8 SAR, which operates at C-, L-, and P-bands, are presented. Both of these systems are multifrequency, polarimetric, airborne, SAR systems.<>     

CFAR edge detector for polarimetric SAR images

Finding the edges between different regions in an image is one of the fundamental steps of image analysis, and several edge detectors suitable for the special statistics of synthetic aperture radar (SAR) intensity images have previously been developed. In this paper, a new edge detector for polarimetric SAR images is presented using a newly developed test statistic in the complex Wishart distribution to test for equality of covariance matrices. The new edge detector can be applied to a wide range of SAR data from single-channel intensity data to multifrequency and/or multitemporal polarimetric SAR data. By simply changing the parameters characterizing the test statistic according to the applied SAR data, constant false-alarm rate detection is always obtained. An adaptive filtering scheme is presented, and the distributions of the detector are verified using simulated polarimetric SAR images. Using SAR data from the Danish airborne polarimetric SAR, EMISAR, it is demonstrated that superior edge detection results are obtained using polarimetric and/or multifrequency data compared to using only intensity data.     

Measurement of topography using polarimetric SAR images

A processing technique for polarimetric synthetic aperture radar (SAR) data has been developed which produces profiles of terrain slopes and elevations in the azimuthal (or along-track) direction. This technique estimates the average shift in orientation angle of copolarization backscatter caused by azimuthal tilts of the scattering plane. Using P-band data, tests of this technique have been made for an area in the Black Forest near Villingen/Schwenningen in Baden-Wurttemberg, Germany. The radar measured slope and derived elevation profiles have low rms errors and high correlation values when compared with a stereo-photograph digital-elevation map (DEM) for the area. This algorithm is capable of adaptively making transitions from the forested areas to nearby regions with open-terrain. Subsequent tests of the algorithm have been conducted using polarimetric SAR L-band data for a mountainous, nonforested, region in the Mojave Desert (Ft. Irwin, CA) where an accurate DEM also was available. Complete elevation and slope mapping of the terrain in two dimensions using this technique is possible when azimuthal elevation profiles are produced throughout the range extent of the SAR image     

极化SAR图像分割方法研究

极化SAR图像分割是面向对象的极化SAR图像分析处理的重要组成部分,也是极化SAR图像处理的关键和难题。然而,目前还没有一种极化SAR分割方法被广泛接受。文章通过对现有的极化SAR图像分割方法进行综述,以使各位研究者对其有一个较全面的认识。文章首先介绍了国内外在极化SAR图像分割方面的主要研究机构;然后对现有的极化SAR图像分割算法进行了分类,并归纳了不同方法的基本思想,分析了各自的性能特点;最后对极化SAR图像分割方法的研究现状及发展趋势进行了总结和展望。     

极化SAR遥感中森林特征的提取

提出了极化散射矩阵总功率、极化熵、相似性参数的组合表达式。通过特征值分析可得该组合表达式的最优系数。该表达式对森林地区的特征敏感,所以可用来检测森林地区。使用中国天山地区的极化SAR数据,验证了所提方法是有效的。     

A calibration technique for polarimetric coherent-on-receive radarsystems

A new technique for calibrating a coherent-on-receive polarimetric radar system is proposed. A coherent-on-receive polarimetric radar is capable of measuring the Mueller matrix of point or distributed targets directly by transmitting at least four independent polarizations and measuring the vertical and horizontal components of the backscatter signal simultaneously. The technique requires the use of two calibration targets, a target with known scattering matrix (such as a metallic sphere or a trihedral corner reflector) and any depolarizing target (for which knowledge of its scattering matrix is not required) to determine the system distortion parameters. The system distortion parameters, which include the channel imbalances, the cross-talk factors of both the transmit and the receive antennas, and the phase shifts and amplitude variations of the transmitter polarizers, are determined by measuring the calibration targets for four different transmit polarizations. The validity of the new calibration technique is examined by measuring the scattering matrices of spheres and cylinders as test targets using a coherent-on-receive radar operating at 34.5 GHz. Excellent agreement between the theoretical and the measured scattering matrices for the test targets are obtained     

Volume decorrelation effects in polarimetric SAR interferometry

Volume decorrelation is an aspect of synthetic aperture radar interferometry that is currently at stake. It stems from the distribution in height of the backscattering cross section in a imaged scene, and it widely affects interferometric coherence images, e.g., in the presence of forests or buildings. The interest in its reduction lies on the fact that "resolving" volume decorrelation and fixing the exact position of the scattering centers in a resolution cell may lead to an estimation of the height of the observed distributed scatterers. Indeed, the determination of the volume scattering contribution is determinant in digital elevation model generation as well as in biomass estimation. However, volume decorrelation itself may be a source of information on the mechanisms that originate it. In this paper, a distinction is made between the behavior of volume decorrelation due to random volumes and stationary distributed targets. The two cases are then studied by means of polarimetry: the response of such targets to different polarizations is considered by applying a series of decompositions of the scattering matrix, and a systematic analysis of the interferometric coherence characteristics is reported.     

Restoration of polarimetric SAR images using simulated annealing

Filtering synthetic aperture radar (SAR) images ideally results in better estimates of the parameters characterizing the distributed targets in the images while preserving the structures of the nondistributed targets. However, these objectives are normally conflicting, often leading to a filtering approach favoring one of the objectives. An algorithm for estimating the radar cross-section (RCS) for intensity SAR images has previously been proposed in the literature based on Markov random fields and the stochastic optimization method simulated annealing. A new version of the algorithm is presented applicable to multilook polarimetric SAR images, resulting in an estimate of the mean covariance matrix rather than the RCS. Small windows are applied in the filtering, and due to the iterative nature of the approach, reasonable estimates of the polarimetric quantities characterizing the distributed targets are obtained while at the same time preserving most of the structures in the image. The algorithm is evaluated using multilook polarimetric L-band data from the Danish airborne EMISAR system, and the impact of the algorithm on the unsupervised H-α classification is demonstrated     

A three-component scattering model for polarimetric SAR data

An approach has been developed that involves the fit of a combination of three simple scattering mechanisms to polarimetric SAR observations. The mechanisms are canopy scatter from a cloud of randomly oriented dipoles, evenor double-bounce scatter from a pair of orthogonal surfaces with different dielectric constants and Bragg scatter from a moderately rough surface. This composite scattering model is used to describe the polarimetric backscatter from naturally occurring scatterers. The model is shown to describe the behavior of polarimetric backscatter from tropical rain forests quite well by applying it to data from NASA/Jet Propulsion Laboratory's (JPLs) airborne polarimetric synthetic aperture radar (AIRSAR) system. The model fit allows clear discrimination between flooded and nonflooded forest and between forested and deforested areas, for example. The model is also shown to be usable as a predictive tool to estimate the effects of forest inundation and disturbance on the fully polarimetric radar signature. An advantage of this model fit approach is that the scattering contributions from the three basic scattering mechanisms can be estimated for clusters of pixels in polarimetric SAR images. Furthermore, it is shown that the contributions of the three scattering mechanisms to the HH, HV, and VV backscatter can be calculated from the model fit. Finally, this model fit approach is justified as a simplification of more complicated scattering models, which require many inputs to solve the forward scattering problem     

Four-component scattering model for polarimetric SAR image decomposition

A four-component scattering model is proposed to decompose polarimetric synthetic aperture radar (SAR) images. The covariance matrix approach is used to deal with the nonreflection symmetric scattering case. This scheme includes and extends the three-component decomposition method introduced by Freeman and Durden dealing with the reflection symmetry condition that the co-pol and the cross-pol correlations are close to zero. Helix scattering power is added as the fourth component to the three-component scattering model which describes surface, double bounce, and volume scattering. This helix scattering term is added to take account of the co-pol and the cross-pol correlations which generally appear in complex urban area scattering and disappear for a natural distributed scatterer. This term is relevant for describing man-made targets in urban area scattering. In addition, asymmetric volume scattering covariance matrices are introduced in dependence of the relative backscattering magnitude between HH and VV. A modification of probability density function for a cloud of dipole scatterers yields asymmetric covariance matrices. An appropriate choice among the symmetric or asymmetric volume scattering covariance matrices allows us to make a best fit to the measured data. A four-component decomposition algorithm is developed to deal with a general scattering case. The result of this decomposition is demonstrated with L-band Pi-SAR images taken over the city of Niigata, Japan.     

A calibration method for fully polarimetric microwave radiometers

A technique for absolute end-to-end calibration of a fully polarimetric microwave radiometer is presented. The technique is based on the tripolarimetric calibration technique of Gasiewski and Kunkee, but is extended to provide a means of calibrating all four Stokes parameters. The extension is facilitated using a biaxial phase-retarding microwave plate to provide a precisely known fourth Stokes signal from the Gasiewski-Kunkee (GK) linearly polarized standard. The relations needed to determine the Stokes vector produced by the augmented standard are presented, and the effects of nonidealities in the various components are discussed. The application of the extended standard to determining the complete set of radiometer constants (the calibration matrix elements) for the National Oceanic and Atmospheric Administration Polarimetric Scanning Radiometer in a laboratory environment is illustrated. A calibration matrix inversion technique and error analysis are described, as well. The uncertainties associated with practical implementation of the fully polarimetric standard for spaceborne wind vector measurements are discussed relative to error thresholds anticipated for wind vector retrieval from the U.S. National Polar-Orbiting Environmental Satellite System.     

HUT fully polarimetric calibration standard for microwave radiometry

This paper describes the Helsinki University of Technology's Fully Polarimetric Calibration Standard (FPCS). The developed standard generates a complete Stokes reference vector and it is applied for the end-to-end absolute calibration of a fully polarimetric microwave radiometer at 36.5 GHz. The FPCS is based on the function principle of a Gasiewski-Kunkee linearly polarized (tripolarimetric) standard, with an additional phase retardation plate to generate the fourth Stokes parameter. Design considerations and operational aspects of the standard are discussed in this paper. An advanced calibration procedure, which takes advantage of both the tripolarimetric and fully polarimetric calibration scenes to suppress calibration uncertainties, is introduced. The feasibility of the standard has been verified and the generated brightness temperatures in a sample calibration are presented. An extensive set of tests has been performed to evaluate the characteristics and performance of the calibration standard. Furthermore, the use of the advanced calibration procedure to measure the characteristics of the phase retardation plate has been successfully demonstrated. The achievable calibration accuracy is analyzed and discussed relative to requirements for maritime wind vector measurements; the results indicate that the pixel-to-pixel retrieval of the wind speed is possible with high accuracy and the retrieval of the wind direction with at least moderate accuracy. In addition to calibration of a fully polarimetric radiometer, other potential applications, e.g., linearity measurements, are discussed.