Wolfgang-Martin Boerner

Four-Component Scattering Power Decomposition With Rotation of Coherency Matrix

This paper presents an improvement to a decomposition scheme for the accurate classification of polarimetric synthetic aperture radar (POLSAR) images. Using a rotation of the coherency matrix to minimize the cross-polarized component, the four-component scattering power decomposition is applied to fully polarimetric SAR images. It is known that oriented urban area and vegetation signatures are decomposed into the same volume scattering mechanism in the previous decompositions and that it is difficult to distinguish vegetation from oblique urban areas with respect to the radar direction of illumination within the volume scattering mechanism. It is desirable to distinguish these two scattering mechanisms for accurate classification although they exhibit similar polarimetric responses. The new decomposition scheme by implementing a rotation of the coherency matrix first and, subsequently, the four-component decomposition yields considerably improved accurate results that oriented urban areas are recognized as double bounce objects from volume scattering.

On the estimation of radar polarization orientation shifts induced by terrain slopes

In recent studies, D. L. Schuler et al. (2000) applied polarimetric imaging radar-derived orientation angles to measure topography, and J. S. Lee et al. (2000) used orientation angles for polarimetric SAR data compensation, to ensure accurate estimation of geophysical parameters in rugged terrain areas. To support these applications, it is important to accurately estimate shifts in orientation angles induced by the azimuth slope variations. However, in many cases, inconsistency in the estimation of orientation angle shifts was encountered in several areas, introducing noisy and erroneous results. The present authors develop a unified analysis of estimation algorithms based on the circular polarization covariance matrix. The concept of reflection symmetry is used to explain the soundness of the circular polarization method and to show problems associated with other algorithms. L-band polarimetric synthetic aperture radar (SAR) images of Camp Roberts, CA, are used to substantiate this theory.

On foundations of radar polarimetry

Polarization aspects of the radar target scattering problem are reexamined. The optimization problem of radar polarimetry is formulated and Kennaughs method of finding optimal polarizations is modified and extended to nonreciprocal and bistatic cases. Our approach does not necessitate diagonalization of the target scattering operator and therefore, a change-of-basis is not required. The change-of-polarization-basis is motivated by the comparison of experimental data taken with different antenna sets. Unitary matrix algebra is used to derive proper transformation formulas for scattering operators and bilinear voltage forms.

POLSAR Image Analysis of Wetlands Using a Modified Four-Component Scattering Power Decomposition

It is important to monitor environmental changes of the Earths cover by remotely sensed data. This paper analyzes seasonal changes of a wetland by a modified polarimetric four-component scattering power decomposition method. The data sets analyzed here are L- and X-band fully polarimetric synthetic aperture radar (POLSAR) data, which have been acquired by the NICT/JAXA airborne polarimetric and interferometric synthetic aperture radar system in 2004. Since there existed a deficiency in the currently adopted decomposition schemes in that negative powers appear in a few pixels in the image analysis, we modified the approach taking into account physical conditions. It is shown by the modified scheme that the seasonal changes and features of the vegetation near Sakata Lagoon in Niigata, Japan, are observed clearly, demonstrating the utility of POLSAR image analysis for wetland assessments in general.

Scene characterization using subaperture polarimetric SAR data

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.

On the basic principles of radar polarimetry: the target characteristic polarization state theory of Kennaugh, Huynen's polarization fork concept, and its extension to the partially polarized case

Basic principles of radar polarimetry are introduced. The target characteristic polarization state theory is developed first for the coherent case using the three stage, the basis transformation, and the power (Mueller) matrix optimization procedures. Kennaughs and Huynens theories of radar target polarimetry are verified for the monostatic reciprocal case. It is shown that there exist, in total, five unique pairs of characteristic polarization states for the symmetric scattering matrix of which two pairs, the cross-polarization null and copolarization max pairs, are identical, whereas the cross-pol max and the cross-pol saddlepoint pairs are distinct. The theory is verified by an example for which next to the polarization fork the copolarized and cross-polarized power density plots are also presented. The partially polarized case for completely polarized wave incidence is presented and compared with the results for the coherent and the partially coherent cases, the latter of which is still unresolved. >

Redevelopment of Kennaugh's target characteristic polarization state theory using the polarization transformation ration formalism for the coherent case

The Kennaugh target characteristic polarization theory for the monostatic reciprocal coherent case is developed in greater detail. Emphasis is on the transformation of the scattering matrix under the change of polarization basis via the unitary transformation matrix formulated in terms of the polarization ratio rho . Six characteristic polarization state are determined, and displayed on the Poincare sphere and on power and phase plots. Several simple target cases for demonstrating the applicability of this useful concept to radar target classification, imaging, and identification are considered. >

Development of a ground-based polarimetric broadband SAR system for noninvasive ground-truth validation in vegetation monitoring

We have developed a ground-based polarimetric broadband synthetic aperture radar (SAR) system for noninvasive ground-truth validation in polarimetric SAR remote sensing of terrestrial vegetation cover. This system consists of a vector network analyzer, one dual-polarized antenna, and an antenna positioner. It can be operated in a frequency range from 50 MHz to 20 GHz, with a scanning aperture of 20 m in the horizontal and 1.5 m in the vertical direction. Tests carried out with standard reflectors showed that the polarimetric measurement capabilities of this system are satisfactory. Using the polarimetric ground-based SAR (GB-SAR) system, we carried out measurements on a specific vegetation cover pertinent to the remote sensing of forested regions within Sendai City, consisting of three different kinds of trees common within the Kawauchi Campus of Tohoku University. Measurements were collected in spring, summer, and autumn. Three-dimensional (3-D) polarization-sensitive images were reconstructed from the acquired data. Analysis of the 3-D polarimetric images of each measurement found differences (at times strong differences) among the polarization signatures. There were stronger reflections in all of the HH, VH, VV images in the second (summer) measurement, especially in the VH image, due to the substantial growth of branches and leaves in summer. This ground-truth validation system provided valuable information about the scattering mechanisms of the three trees selected for analysis in different seasons, which can be detected by broadband polarimetric ground-based SAR measurements. The experimental results demonstrate the excellent polarimetric performance of the newly developed SAR imaging system, which should find many useful and immediate applications in noninvasive ground-truth validation of diverse terrestrial vegetation covers.

Four-component scattering power decomposition with rotation of coherency matrix

This paper presents an improvement to a decomposition scheme for the accurate classification of polarimetric synthetic aperture radar (POLSAR) images. Using a rotation of the coherency matrix to minimize the cross-polarized component, the four-component scattering power decomposition is applied to fully polarimetric SAR images. It is known that oriented urban area and vegetation signatures are decomposed into the same volume scattering mechanism in the previous decompositions and that it is difficult to distinguish vegetation from oblique urban areas with respect to the radar direction of illumination within the volume scattering mechanism. It is desirable to distinguish these two scattering mechanisms for accurate classification although they exhibit similar polarimetric responses. The new decomposition scheme by implementing a rotation of the coherency matrix first and, subsequently, the four-component decomposition yields considerably improved accurate results that oriented urban areas are recognized as double bounce objects from volume scattering.

Monitoring of the March 11, 2011, Off-Tohoku 9.0 Earthquake With Super-Tsunami Disaster by Implementing Fully Polarimetric High-Resolution POLSAR Techniques

This paper reflects the polarimetric synthetic aperture radar (POLSAR) data utilization for near-real-time earthquake and/or tsunami damage assessment in urban areas. In order to show the potential of the fully polarimetric high-resolution polarimetric SAR (POLSAR) image data sets, a four-component scattering power decomposition scheme has been developed and applied to monitor near-real-time earthquake and tsunami disaster damages. The test site for natural disaster damages has been selected: parts of the coastal area affected by the March 11, 2011, 9.0 magnitude earthquake that struck off Japans northeastern coast and triggered a super-tsunami. The color-coded images of the scattering power decomposition scheme are a simple and straightforward tool to interpret the changes over the earthquake/tsunami affected urban areas and man-made infrastructures. This method also holds other types of natural (typhoon or tornado) and man-made disaster assessment applications. It is found that the double-bounce scattering power is the most promising of the input parameters to detect automated disaster affected urban areas at pixel level. It is also observed that the very-high-resolution POLSAR images are required for superior urban area monitoring over the oriented urban blocks with respect to the illumination of radar.