Basic Concepts of Radar Polarimetry

Boerner, W.-M.; Yan, Wei-Ling; Xi, An-Qing; Yamaguchi, Yoshio

doi:10.1007/978-94-010-9243-2_8

Cited by 27 publications

(22 citation statements)

References 26 publications

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“…The Polarization Fork In order to determine the "polarization fork operator of Huynen" [51], use is made of the complex polarization ratio p formulation [18], shown in According to the expression of the cross-pol max and cross-pol saddles, they all lie on the unit circle and are the end points of two orthogonal diameters. so their corresponding points lie on the equator of the sphere as Si, 2' T1, and T2 with SS2 and T1T2 perpendicular to each other.…”

Section: 3mentioning

confidence: 99%

“…Although these methods offer some speckle reduction and a limited possibility of automation, we are interested in this paper on a new approach in POL-SAR image analysis which analyses the given complex-valued, coherent polarization data from a more desirable viewpoint which comes closer to electromagnetic vector wave theory.since the POL-SAR data are provided in the 2x2 Sinclair or 4x4 Mueller scattering matrix format which contains all the polarization transformation information of the reflected EM wave after its interaction with terrain/clutter. In the following PMIF method which was developed by Boerner, Kostiflski, James et al[16][17][18][19][20][21][22][63][64][65][66][67], the polarization orientations of the receiving or transmitting antennas of the POL-SAR system are simulated in the computer and matched polarmmetrically to a given data set in order to enhance the features of an image and to reduce unwanted noise and speckle, among other things.3 A FIRST ORDER POLARIZATION ADJUSIENT PROCEDURE FOR BAR IMGERT…”

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confidence: 99%

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Polarimetric matched image filter in POL-SAR image enhancement

et al. 1993

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When determining the nature of speckle in microwave POL-SAR image analysis, various known methods of speckle reduction are reviewed and compared for the purpose of enhancingimage quality in polarimetric matched image filtering. Basic principles of the Polarimetric Matched Image Filter (PMIF) are presented and by utilizing the now widely used NASA-JPL C-Band POL-SAR data sets, collected over the San Francisco Bay area, the PHIF concept, together with various speckle reduction methods are verified and interpreted.Specific emphasis is placed on demonstrating the efficiency and usefulness of applying the PNIF method to the optimization of image discriininants in POL-SAR image analysis.

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Section: 3mentioning

confidence: 99%

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confidence: 99%

Polarimetric matched image filter in POL-SAR image enhancement

et al. 1993

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“…It is widely known fact that using polarimetric information can seriously improve the radar performances for targets detection, identification, and parameters estimation, for clutter and interferences suppression [1,2]. Most of modern radar polarimetry algorithms are based on the measurements of the radar target polarization scattering matrix (PSM), which includes four elements with different amplitudes and phases.…”

Section: Introductionmentioning

confidence: 99%

Basics and first experiments demonstrating isolation improvements in the agile polarimetric FM-CW radar – PARSAX

Krasnov

Babur

Wang

et al. 2010

Int. J. Microw. Wireless Technol.

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Basics and first experiments demonstrating isolation improvements in the agile polarimetric FM-CW radar -PARSAX oleg a. krasnov, galina p. babur, zongbo wang, leo p. ligthart and fred van der zwanThe article describes the IRCTR PARSAX radar system, the S-band high-resolution Doppler polarimetric frequency modulated continuous wave (FM-CW) radar with dual-orthogonal sounding signals, which has the possibility to measure all elements of the radar target polarization scattering matrix simultaneously, in one sweep. The performance of such radar depends of the level of sounding signals orthogonality. In the main operational mode, the radar will be used for atmospheric remote sensing and polarimetric studies of ground-based targets. In such mode it will use a pair of synchronous linearly-frequency modulated (LFM) continuous signals with opposite frequency excursions of 50 MHz and duration of 1 ms. Such a combination of sounding signals has limited orthogonality even for huge BT-products, which produce cross-channel interferences. These interferences in case of radar scene with multiple pointed and distributed targets can completely degrade radar operational performance. In this article, we propose simple and effective technique to suppress interferences and to restore radar performance. The technique has been tested using simulation and has been implemented in multi-channel digital receiver of the PARSAX radar. The real radar measurements presented to illustrate effectiveness of cross-channel interferences suppression. The proposed technique can be useful not only for polarimetric radar design, but also in much wide radar applications, which use waveforms with high orthogonality.

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“…Within this campaign fieldwork, 117 plots fall within in the overlapping area between P and L band images (Figure 3 is mono-static. We determined the scale factor or vertical wavenumber following Boerner et al (1992). The complex coherence was obtained for all polarization channels including linear polarizations (HH, HV and V V ), circular polarization (LL, LR and RR) and the Pauli decompositions (HH + V V and HH − V V ) (Lee and Pottier, 2009).…”

Section: Data Descriptionmentioning

confidence: 99%

Estimation of tree height from PolInSAR : the effects of vertical structure and temporal decorrelation

Ghasemi¹

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I would like to thank the European Space Agency for providing data and helping me whenever I faced an obstacle to process the data and getting results. I am also grateful to Dr.Marco Lavalle for providing AfriSAR campaign data as an early access and AfriSAR team at NASA and ESA for organizing and distributing the data acquired during the 2016 AfriSAR Campaign. I also thank the UAVSAR and ISCE teams at the Jet Propulsion Laboratory, California Institute of Technology for collecting and processing the radar images, and the LVIS team at the Goddard Space Flight Center for collecting and processing the lidar data used in this publication. I would like to thank my fellow doctoral students for their feedback, cooperation and of course friendship. In addition I would like to express my gratitude to the staff of ITC for their support and help during all these years. I would like to thank my friends for accepting nothing less than excellence from me. Last but not the least, I would like to thank my family: my parents and to my sisters for supporting me spiritually throughout writing this thesis and my life in general. vii

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Basic Concepts of Radar Polarimetry

Cited by 27 publications

References 26 publications

Polarimetric matched image filter in POL-SAR image enhancement

Polarimetric matched image filter in POL-SAR image enhancement

Basics and first experiments demonstrating isolation improvements in the agile polarimetric FM-CW radar – PARSAX

Estimation of tree height from PolInSAR : the effects of vertical structure and temporal decorrelation

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