Calibration of linearly polarized polarimetric SAR data subject to Faraday rotation

A model for linearly polarized fully polarimetric backscatter measurements is used, incorporating the effects of system noise, channel amplitude, phase imbalance, crosstalk, and Faraday rotation. A step-by-step procedure is outlined for correction (or calibration) of fully polarimetric data subject to Faraday rotation, to recover the true scattering matrix. The procedure identifies steps for crosstalk removal and correction of channel imbalances that are robust in the presence of Faraday rotation. The final steps in the procedure involve a novel strategy for estimation and correction of Faraday rotation. Three approaches to estimate the (one-way) Faraday rotation angle /spl Omega/ directly from linear (quad-) polarized synthetic aperture radar (SAR) backscatter data obtained by a spaceborne SAR system are described. Each approach can initially be applied to the signature of any scatterer within the scene. Sensitivity analyses are presented that show that at least one of the measures can be used to estimate /spl Omega/ to within /spl plusmn/3/spl deg/ to 5/spl deg/, with reasonable levels of residual crosstalk, noise floor, channel amplitude, and phase imbalance. Ambiguities may be present in the estimates of /spl Omega/ of /spl plusmn/n/spl pi//2 - the impact of this is discussed, and several approaches are suggested to deal with this possibility. The approach described in this paper is relevant for future L-band spaceborne SARs and removes one key obstacle to the deployment of even longer wavelength SARs (e.g., an ultrahigh frequency or P-band SAR) in Earth orbit.     

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     

Radar imaging of moving targets in foliage using multifrequency multiaperture polarimetric SAR

Because of the low signal-to-clutter ratio, it is a difficult problem to detect and image moving targets in foliage. In this paper, a multifrequency multiaperture polarimetric synthetic aperture radar (MFMA POLSAR) system is proposed for imaging of moving targets in foliage. The MFMA POLSAR extends the multifrequency antenna array SAR (MF-SAR) system to multiple polarizations. Full polarization is used in MFMA POLSAR to achieve an optimal polarization adaptive to the environment such that the images obtained by different apertures are of the best coherence that is used to obtain the highest accuracy of the phase estimation. It is also shown that the MFMA POLSAR cannot only accurately locate both the slow and the fast moving targets but also reveal moving targets in foliage.     

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%     

Orientation angle preserving a posteriori polarimetric SAR calibration

Fully polarimetric synthetic aperture radar (SAR) data analysis has found wide application for terrain classification, land-use, soil moisture, and ground cover classification. Critical to all analyses and applications is accurate calibration of the relative amplitudes of and phases between the various polarimetric channels. Here we propose an a posteriori method imposing only the weakest of constraints, scattering reciprocity, on the polarimetric data. Calibration parameters are self-consistently estimated from full 4/spl times/4 polarimetric covariance matrices. Whilst the complete set of calibration parameters is underdetermined, we give several reasonable heuristic methods to provide a complete calibration. Stronger constraints reduce the number of independent parameters and provide an overdetermined set of equations but at a cost - the loss of polarimetric fidelity when the underlying assumptions are violated. Without recourse to in situ calibration targets, the extent of the polarimetric distortion that results from polarimetric calibration remains unknown. We apply our new method to simulated data, anechoic chamber data and polarimetric SAR imagery. We also present comparisons with alternate calibration methods and different approximate solutions of the new technique.     

Calibration of a polarimetric radar using a rotatable dihedralcorner reflector

Based on the existing mathematical formalisms of radar polarimetry, it is necessary to perform accurate and diversified polarimetric measurements in the real world to thoroughly investigate signature definition, identification, and classification of radar targets. For this study the Delft Atmospheric Research Radar (DARR) is used. This ground-based polarimetric FM-CW radar operates in the S-band. The purpose of the present paper is the polarimetric calibration of the DARR. Among the passive reflectors, a rotatable dihedral corner reflector is a suitable calibration object. It enables one to measure different scattering matrices with only one reflector. One alignment must be performed and the scattering matrices are measured at the same range. By measuring several scattering matrices, the accuracy of the calibration result can be estimated. A measurement campaign with a rotatable dihedral corner reflector was therefore performed. The experimental results and the calibration procedure are presented in this paper     

Calibration of radars using polarimetric techniques

A method that uses the properties of rain medium itself to obtain accurate weather radar system gain calibration is discussed. This technique is based on the principle that the rainfall rate measured using absolute reflectivity (Z) and differential reflectivity ( Z_DR) is the same as that obtained from specific differential phase (K_DP). The measurements required for this technique are Z, Z_DR, and K _DP. The rainfall rate estimates obtained from Z and Z_DR are compared with the estimates obtained from K_DP. The scatter plot between the two rainfall estimates should lie close to a 1:1 line, and any systematic deviation from this line can be removed by appropriately adjusting the system gain. It is noted that Z_DR can be calibrated accurately because it is a differential power measurement, and K_DP is obtained from differential phase measurement, which is unaffected by system calibration. The sensitivity and accuracy of this technique are studied, and theoretical and simulation results for C-band frequencies are presented     

Calibration of bistatic polarimetric radar systems

A calibration technique for laboratory type polarimetric, bistatic instrumentation radars is presented. It describes the errors induced by the standard radiation transfer approach (I-SRT) in a way similar to that for the monostatic case. A 12-term error correction and absolute polarimetric calibration is performed with two external reference targets. Only the polarimetric bistatic reference of the first target must be theoretically determined. The scattering reference of the second target is determined by a measurement during the calibration process (single reference calibration). The simulation of a third cross-polarization measurement is performed by an antenna rotation and a remeasurement of the second target. Thus all data are gained for the determination of the error terms and measurements of unknown objects can be full polarimetrically calibrated. The procedures are shown for an adapted dihedral corner reflector. Misalignment errors are discussed     

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。     

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.     

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     

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。     

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     

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.     

Calibration of polarimetric radar systems with good polarizationisolation

A practical technique is proposed for calibrating single-antenna polarimetric radar systems using a metal sphere plus any second target with a strong cross-polarized radar cross section. This technique assumes perfect isolation between antenna ports. It is shown that all magnitudes and phases (relative to one of the like-polarized linear polarization configurations) of the radar transfer function can be calibrated without knowledge of the scattering matrix of the second target. Comparison of the values measured (using this calibration technique) for a tilted cylinder in the X-band with theoretical values shows agreement within ±0.3 dB in magnitude and ±5° in phase. The radar overall cross-polarization isolation was 25 dB. The technique is particularly useful for calibrating a radar under field conditions, because it does not require the careful alignment of calibration targets     

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.     

Unsupervised segmentation of polarimetric SAR data using thecovariance matrix

A method for unsupervised segmentation of polarimetric synthetic aperture radar (SAR) data into classes of homogeneous microwave polarimetric backscatter characteristics is presented. Classes of polarimetric backscatter are selected on the basis of a multidimensional fuzzy clustering of the logarithm of the parameters composing the polarimetric covariance matrix. The clustering procedure uses both polarimetric amplitude and phase information, is adapted to the presence of image speckle, and does not require an arbitrary weighting of the different polarimetric channels; it also provides a partitioning of each data sample used for clustering into multiple clusters. Given the classes of polarimetric backscatter, the entire image is classified using a maximum a posteriori polarimetric classifier. Four-look polarimetric SAR complex data of lava flows and of sea ice acquired by the NASA/JPL airborne polarimetric radar (AIRSAR) are segmented using this technique     

Segmentation of textured polarimetric SAR scenes by likelihood approximation

A hierarchical stepwise optimization process is developed for polarimetric synthetic aperture radar image segmentation. We show that image segmentation can be viewed as a likelihood approximation problem. The likelihood segment merging criteria are derived using the multivariate complex Gaussian, the Wishart distribution, and the K-distribution. In the presence of spatial texture, the Gaussian-Wishart segmentation is not appropriate. The K-distribution segmentation is more effective in textured forested areas. The validity of the product model is also assessed, and a field-adaptable segmentation strategy combining different criteria is examined.