Relevant bibliographies by topics / Polarimetric signature

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Polarimetric signature'

Author: Grafiati
Published: 25 May 2024

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Journal articles on the topic "Polarimetric signature"

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Takahashi, J., Y. Itoh, T. Matsuo, Y. Oasa, Y. P. Bach, and M. Ishiguro. "Polarimetric signature of the oceans as detected by near-infrared Earthshine observations." Astronomy & Astrophysics 653 (September 2021): A99. http://dx.doi.org/10.1051/0004-6361/202039331.

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Context. The discovery of an extrasolar planet with an ocean has crucial importance in the search for life beyond Earth. The polarimetric detection of specularly reflected light from a smooth liquid surface is anticipated theoretically, though the polarimetric signature of Earth’s oceans has not yet been conclusively detected in disk-integrated planetary light. Aims. We aim to detect and measure the polarimetric signature of the Earth’s oceans. Methods. We conducted near-infrared polarimetry for lunar Earthshine and collected data on 32 nights with a variety of ocean fractions in the Earthshine-contributing region. Results. A clear positive correlation was revealed between the polarization degree and ocean fraction. We found hourly variations in polarization in accordance with rotational transition of the ocean fraction. The ratios of the variation to the typical polarization degree were as large as ~0.2–1.4. Conclusions. Our observations provide plausible evidence of the polarimetric signature attributed to Earth’s oceans. Near-infrared polarimetry may be considered a prospective technique in the search for exoplanetary oceans.
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Ryzhkov, Alexander V., Terry J. Schuur, Donald W. Burgess, and Dusan S. Zrnic. "Polarimetric Tornado Detection." Journal of Applied Meteorology 44, no. 5 (May 1, 2005): 557–70. http://dx.doi.org/10.1175/jam2235.1.

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Abstract Polarimetric radars are shown to be capable of tornado detection through the recognition of tornadic debris signatures that are characterized by the anomalously low cross-correlation coefficient ρhv and differential reflectivity ZDR. This capability is demonstrated for three significant tornadic storms that struck the Oklahoma City, Oklahoma, metropolitan area. The first tornadic debris signature, based on the measurements with the National Severe Storms Laboratory’s Cimarron polarimetric radar, was reported for a storm on 3 May 1999. Similar signatures were identified for two significant tornadic events during the Joint Polarization Experiment (JPOLE) in May 2003. The data from these storms were collected with a polarimetric prototype of the Next-Generation Weather Radar (NEXRAD). In addition to a small-scale debris signature, larger-scale polarimetric signatures that might be relevant to tornadogenesis were persistently observed in tornadic supercells. The latter signatures are likely associated with lofted light debris (leaves, grass, dust, etc.) in the inflow region and intense size sorting of hydrometeors in the presence of strong wind shear and circulation.
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Snyder, Jeffrey C., Howard B. Bluestein, Vijay Venkatesh, and Stephen J. Frasier. "Observations of Polarimetric Signatures in Supercells by an X-Band Mobile Doppler Radar." Monthly Weather Review 141, no. 1 (January 1, 2013): 3–29. http://dx.doi.org/10.1175/mwr-d-12-00068.1.

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Abstract Polarimetric weather radars significantly enhance the capability to infer the properties of scatterers within a resolution volume. Previous studies have identified several consistently seen polarimetric signatures in supercells observed in the central United States. Nearly all of these studies used data collected by fixed-site S- and C-band radars. Because there are few polarimetric mobile radars, relatively little has been documented in high-resolution polarimetric data from mobile radars. Compared to S and C bands, there has been very limited examination of polarimetric signatures at X band. The primary focus of this paper is on one signature that has not been documented previously and one that has had little documentation at X band. The first signature, seen in at least seven supercell datasets collected by a mobile, X-band, polarimetric radar, consists of a narrow band of locally reduced reflectivity factor ZH and differential reflectivity, typically near the location where the hook echo “attaches” to the main body of the storm echo. No consistent pattern is seen in radial velocity VR or copolar cross correlation ρHV. The small size of this feature suggests a significant heterogeneity in precipitation microphysics, the cause and impact of which are unknown. The greater resolution and the scattering differences at X band compared to other frequencies may make this feature more apparent. The second signature consists of anomalously low ρHV in areas of high ZH along the left section (relative to storm motion) of the bounded weak-echo region. Examples of other polarimetric signatures at X band are provided.
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Vyas, A., and B. Sashtri. "SAR POLARIMETRIC SIGNATURES FOR URBAN TARGETS – POLARIMETRIC SIGNATURE CALCULATION AND VISUALIZATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXIX-B7 (August 2, 2012): 535–40. http://dx.doi.org/10.5194/isprsarchives-xxxix-b7-535-2012.

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Kumjian, Matthew R., and Alexander V. Ryzhkov. "Polarimetric Signatures in Supercell Thunderstorms." Journal of Applied Meteorology and Climatology 47, no. 7 (July 1, 2008): 1940–61. http://dx.doi.org/10.1175/2007jamc1874.1.

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Abstract Data from polarimetric radars offer remarkable insight into the microphysics of convective storms. Numerous tornadic and nontornadic supercell thunderstorms have been observed by the research polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) in Norman, Oklahoma (KOUN); additional storm data come from the Enterprise Electronics Corporation “Sidpol” C-band polarimetric radar in Enterprise, Alabama, as well as the King City C-band polarimetric radar in Ontario, Canada. A number of distinctive polarimetric signatures are repeatedly found in each of these storms. The forward-flank downdraft (FFD) is characterized by a signature of hail observed as near-zero ZDR and high ZHH. In addition, a shallow region of very high ZDR is found consistently on the southern edge of the FFD, called the ZDR “arc.” The ZDR and KDP columns and midlevel “rings” of enhanced ZDR and depressed ρHV are usually observed in the vicinity of the main rotating updraft and in the rear-flank downdraft (RFD). Tornado touchdown is associated with a well-pronounced polarimetric debris signature. Similar polarimetric features in supercell thunderstorms have been reported in other studies. The data considered here are taken from both S- and C-band radars from different geographic locations and during different seasons. The consistent presence of these features may be indicative of fundamental processes intrinsic to supercell storms. Hypotheses on the origins, as well as microphysical and dynamical interpretations of these signatures, are presented. Implications about storm morphology for operational applications are suggested.
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Johnson, Marcus, Youngsun Jung, Daniel T. Dawson, and Ming Xue. "Comparison of Simulated Polarimetric Signatures in Idealized Supercell Storms Using Two-Moment Bulk Microphysics Schemes in WRF." Monthly Weather Review 144, no. 3 (February 16, 2016): 971–96. http://dx.doi.org/10.1175/mwr-d-15-0233.1.

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Abstract Microphysics parameterization becomes increasingly important as the model grid spacing increases toward convection-resolving scales. The performance of several partially or fully two-moment (2M) schemes within the Weather Research and Forecasting (WRF) Model, version 3.5.1, chosen because of their well-documented advantages over one-moment (1M) schemes, is evaluated with respect to their ability in producing the well-known polarimetric radar signatures found within supercell storms. Such signatures include the ZDR and KDP columns, the ZDR arc, the midlevel ZDR and ρHV rings, the hail signature in the forward-flank downdraft, and the KDP foot. Polarimetric variables are computed from WRF Model output using a polarimetric radar simulator. It is found that microphysics schemes with a 1M rimed-ice category are unable to simulate the ZDR arc, despite containing a 2M rain category. It is also found that a hail-like rimed-ice category (in addition to graupel) may be necessary to reproduce the observed hail signature. For the microphysics schemes that only contain a graupel-like rimed-ice category, only very wet graupel particles are able to reach the lowest model level, which did not adequately reduce ZDR in this signature. The most realistic signatures overall are found with microphysics schemes that are fully 2M with a separate hail category.
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Van Den Broeke, Matthew S. "Polarimetric Tornadic Debris Signature Variability and Debris Fallout Signatures." Journal of Applied Meteorology and Climatology 54, no. 12 (December 2015): 2389–405. http://dx.doi.org/10.1175/jamc-d-15-0077.1.

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AbstractValues of polarimetric radar variables may vary substantially between and through tornadic debris signature (TDS) events. Tornadoes with higher intensity ratings are associated with higher average and extreme values of reflectivity factor at horizontal polarization ZHH and lower values of copolar cross-correlation coefficient ρhv. Although values of these variables often fluctuate through reported tornado life cycles, ZHH repeatably decreases and ρhv repeatably increases across the volume scan immediately following reported tornado demise. Land cover has a relatively small effect on values of the polarimetric variables within TDSs, although near-radar urban TDSs may exhibit relatively high ZHH values. TDS areal extent is typically larger aloft than near the surface, although this trend may reverse in the most intense tornadoes. Maximum altitude to which a TDS is visible is more strongly a function of tornado intensity than of land cover or ambient shear and instability. Debris often disappears once lofted but may also be observed to spread out downstream with the storm-relative flow or to fall out along the parent storm’s northwest flank in a debris fallout signature (DFS). DFS characteristics, although variable, most commonly include ZHH values of 30–35 dBZ, ρhv values of 0.60–0.80, and values of differential reflectivity ZDR that are repeatably near 0 dB.
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Andrić, Jelena, Matthew R. Kumjian, Dušan S. Zrnić, Jerry M. Straka, and Valery M. Melnikov. "Polarimetric Signatures above the Melting Layer in Winter Storms: An Observational and Modeling Study." Journal of Applied Meteorology and Climatology 52, no. 3 (March 2013): 682–700. http://dx.doi.org/10.1175/jamc-d-12-028.1.

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AbstractPolarimetric radar observations above the melting layer in winter storms reveal enhanced differential reflectivity ZDR and specific differential phase shift KDP, collocated with reduced copolar correlation coefficient ρhv; these signatures often appear as isolated “pockets.” High-resolution RHIs and vertical profiles of polarimetric variables were analyzed for a winter storm that occurred in Oklahoma on 27 January 2009, observed with the polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) in Norman. The ZDR maximum and ρhv minimum are located within the temperature range between −10° and −15°C, whereas the KDP maximum is located just below the ZDR maximum. These signatures are coincident with reflectivity factor ZH that increases toward the ground. A simple kinematical, one-dimensional, two-moment bulk microphysical model is developed and coupled with electromagnetic scattering calculations to explain the nature of the observed polarimetric signature. The microphysics model includes nucleation, deposition, and aggregation and considers only ice-phase hydrometeors. Vertical profiles of the polarimetric radar variables (ZH, ZDR, KDP, and ρhv) were calculated using the output from the microphysical model. The base model run reproduces the general profile and magnitude of the observed ZH and ρhv and the correct shape (but not magnitude) of ZDR and KDP. Several sensitivity experiments were conducted to determine if the modeled signatures of all variables can match the observed ones. The model was incapable of matching both the observed magnitude and shape of all polarimetric variables, however. This implies that some processes not included in the model (such as secondary ice generation) are important in producing the signature.
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Van Den Broeke, Matthew S., and Sabrina T. Jauernic. "Spatial and Temporal Characteristics of Polarimetric Tornadic Debris Signatures." Journal of Applied Meteorology and Climatology 53, no. 10 (October 2014): 2217–31. http://dx.doi.org/10.1175/jamc-d-14-0094.1.

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AbstractNonmeteorological scatter, including debris lofted by tornadoes, may be detected using the polarimetric radar variables. For the 17 months from January 2012 to May 2013, radar data were examined for each tornado reported in the domain of an operational polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D). Characteristics of the tornadic debris signature (TDS) were recorded when a signature was present. Approximately 16% of all tornadoes reported in Storm Data were associated with a debris signature, and this proportion is shown to vary regionally. Signatures were more frequently seen with tornadoes that were rated higher on the enhanced Fujita (EF) scale, with tornadoes causing higher reported total property damage, with tornadoes that were closer to the radar and thus intercepted by the beam at lower altitude, and associated with tornadoes with greater total pathlength. Tornadic debris signatures were most common in spring, when more strong tornadoes occur, and in autumn, when natural debris is more available. Debris-signature areal extent is shown to increase consistently with EF-scale rating and tornado longevity. Vertical extent of a TDS is shown to be greatest for strong, long-lived tornadoes with large radii of damaging wind. Land cover is also shown to exhibit some control over TDS characteristics—in particular, a large percentage of tornadoes with substantial track over urban land cover exhibited a TDS and do so very quickly after reported tornadogenesis, as compared with tornadoes over other land-cover classifications. TDS characteristics over grassland and cropland tended to be similar.
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Griffin, Casey B., David J. Bodine, and Robert D. Palmer. "Kinematic and Polarimetric Radar Observations of the 10 May 2010, Moore–Choctaw, Oklahoma, Tornadic Debris Signature." Monthly Weather Review 145, no. 7 (July 2017): 2723–41. http://dx.doi.org/10.1175/mwr-d-16-0344.1.

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Tornadoes are capable of lofting large pieces of debris that present irregular shapes, near-random orientations, and a wide range of dielectric constants to polarimetric radars. The unique polarimetric signature associated with lofted debris is called the tornadic debris signature (TDS). While ties between TDS characteristics and tornado- and storm-scale kinematic processes have been speculated upon or investigated using photogrammetry and single-Doppler analyses, little work has been done to document the three-dimensional wind field associated with the TDS. Data collected by the Oklahoma City, Oklahoma (KTLX), and Norman, Oklahoma (KOUN), WSR-88D S-band radars as well as the University of Oklahoma’s (OU) Advanced Radar Research Center’s Polarimetric Radar for Innovations in Meteorology and Engineering (OU-PRIME) C-band radar are used to construct single- and dual-Doppler analyses of a tornadic supercell that produced an EF4 tornado near the towns of Moore and Choctaw, Oklahoma, on 10 May 2010. This study documents the spatial distribution of polarimetric radar variables and how each variable relates to kinematic fields such as vertical velocity and vertical vorticity. Special consideration is given to polarimetric signatures associated with subvortices within the tornado. An observation of negative differential reflectivity ([Formula: see text]) at the periphery of tornado subvortices is presented and discussed. Finally, dual-Doppler wind retrievals are compared to single-Doppler axisymmetric wind fields to illustrate the merits of each method.
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Dissertations / Theses on the topic "Polarimetric signature"

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Galletti, Michele. "Fully Polarimetric Analysis of Weather Radar Signatures." Doctoral thesis, Universitätsbibliothek Chemnitz, 2010. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-201000174.

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Diese (Doktor)arbeit beschäftigt sich mit Radar-Polarimetrie, insbesondere mit der Untersuchung der Eigenschaften von polarimetrischen Variablen, die potenziellen Nutzen für die Radar-Meteorologie haben. Für den Einsatz in Dual-Polarisations-Radargeräten wird der Polarisationsgrad analysiert. Diese Variable wird in künftigen operationellen Radargeräten verfügbar sein. Der Polarisationsgrad hängt vom transmittierten Polarisationszustand und in weiterer Folge auch vom Betriebsmodus des Radargeräts ab. Der Hauptbetriebsmodus von operationellen Radargeräten sendet und empfängt gleichzeitig sowohl die horizontale als auch die vertikale Komponente. Der sekundäre Betriebsmodus sendet und empfängt simultan die horizontal polarisierte Komponente. In dieser Arbeit werden beide Polarisationsgrade untersucht. Da operationelle Systeme derzeit auf den Dual-Polarisationsmodus aufgerüstet werden, sollte künftig die Anwendungsmöglichkeiten von vollpolarimetrischen Wetterradarsystemen untersucht werden. Aus allen Variablen, die in diesem Betriebsmodus zur Verfügung stehen, wurde die Entropie (des gemessen Objektes) ausgewählt und wegen seiner engen Beziehung zum Polarisationsgrad näher untersucht
The present doctoral thesis deals with radar polarimetry, namely with the investigation of properties of polarimetric variables potentially useful in radar meteorology. For use with dual-polarization radars, the degree of polarization is analyzed. This variable is available to planned operational radars. The degree of polarization is dependent on transmit polarization state and, consequently, it is dependent on the radar system operating mode. The primary operating mode of operational radars consists in simultaneous transmission and simultaneous receive of both horizontal and vertical components. The secondary operating mode consists of horizontal transmission and simultaneous receive. Both degrees of polarization are investigated in this thesis. Also, as operational systems are being updated to dual-polarization, research should start investigating the capabilities of fully polarimetric weather radar systems. Among the numerous variables available from this operating mode, the target entropy was chosen for investigation, also because of its close relation to the degree of polarization
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Lewis, Gareth Dafydd. "Polarimetric signatures of roughened surfaces." Thesis, Cranfield University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.422187.

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Sumrain, Shadi. "DETECTION OF POLARIMETRIC SIGNATURES USING HIGH-EFFICIENCY POLARIMETRIC IMAGING TECHNIQUES." University of Akron / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=akron1125081616.

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Dural, Gülbin M. "Polarimetric ISAR imaging to identify basic scattering mechanisms using transient signatures /." The Ohio State University, 1988. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487596307359511.

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Beamer, Diane K. "Polarization Signatures in Vector Space." University of Dayton / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1530977525748664.

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Chamberlain, Neil Frederick. "Recognition and analysis of aircraft targets by radar, using structural pattern representations derived from polarimetric signatures /." The Ohio State University, 1989. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487599963593822.

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Adya, Vandana. "Detection of Signal Parameters and Backscattering Polarimetric Imaging Signatures using Molecular Optical Contrast Agents and Preclinical Liquid Phantoms." University of Akron / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=akron1225204620.

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Valluru, Keerthi Srivastav. "Study of Biomolecular Optical Signatures for Early Disease Detection and Cell Physiology Monitoring." University of Akron / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=akron1213627946.

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Farajipour, Parisa. "In Vitro Biomarker Detection for Early Diagnosis of Neurodegenerative Diseases via the Ocular Fluid." University of Akron / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=akron1259778648.

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Wu, Hsin-Wei, and 吳信緯. "Polarimetric Signature Imaging of Anisotropic Bio-medical Tissues." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/92025495435194380024.

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碩士
國立陽明大學
生醫光電工程研究所
98
Polarimetric imaging of Stokes vector (I, Q, U, V) can provide 4 independent signatures showing the linear and circular polarization properties of samples of interest including biological tissues and cells. Using a Stokes digital imaging system, we measured the Stokes vector images of tissue samples from sections of rat livers. The derived Mueller matrix elements can quantitatively provide five-signature spectral imaging data of the bio-samples. The imaging of four independent optical properties: anisotropy, scattering, depolarization and retardation phase of the test sample are derived and reported. Our experimental results are consistent with the general trend predicted by the theoretical model. This polarimetric multi-signature optical technology is a new option of bio-sensing technology to inspect the structures of tissue samples and is potentially useful for critical disease discrimination and medical diagnostics applications.
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Books on the topic "Polarimetric signature"

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V, Nghiem S., and United States. National Aeronautics and Space Administration., eds. Polarimetric signatures of sea ice. [Washington, DC: National Aeronautics and Space Administration, 1995.

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Polarimetric signatures of sea ice. [Washington, DC: National Aeronautics and Space Administration, 1995.

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Book chapters on the topic "Polarimetric signature"

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Lopez-Sanchez, J. M., J. D. Ballester-Berman, F. Vicente-Guijalba, S. R. Cloude, H. McNairn, J. Shang, H. Skriver, et al. "Agriculture and Wetland Applications." In Polarimetric Synthetic Aperture Radar, 119–78. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-56504-6_3.

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AbstractBased on experimental results, this chapter describes applications of SAR polarimetry to extract relevant information on agriculture and wetland scenarios by exploiting differences in the polarimetric signature of different scatterers, crop types and their development stage depending on their physical properties. Concerning agriculture, crop type mapping, soil moisture estimation and phenology estimation are reviewed, as they are ones with a clear benefit of full polarimetry over dual or single polarimetry. For crop type mapping, supervised or partially unsupervised classification schemes are used. Phenology estimation is treated as a classification problem as well, by regarding the different stages as different classes. Soil moisture estimation makes intensive use of scattering models, in order to separate soil and vegetation scattering and to invert for soil moisture from the isolated ground component. Then, applications of SAR polarimetry to wetland monitoring are considered that include the delineation of their extent and their characterisation by means of polarimetric decompositions. In the last section of the chapter, the use of a SAR polarimetric decomposition is shown for the assessment of the damages consequential to earthquakes and tsunamis.
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Chen, Kun-Shan, Cheng-Yen Chiang, and Ying Yang. "Polarimetric SAR Signature of Complex Scene." In Signal and Image Processing for Remote Sensing, 94–120. 3rd ed. Boca Raton: CRC Press, 2024. http://dx.doi.org/10.1201/9781003382010-8.

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Manson, Anthony C., and Wolfgang-M. Boerner. "Interpretation of High-Resolution Polarimetric Radar Target Down-Range Signatures Using Kennaugh’s and Huynen’s Target Characteristic Operator Theories." In Inverse Methods in Electromagnetic Imaging, 695–720. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5271-3_3.

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Manson, Anthony C., and Wolfgang-M. Boerner. "Interpretation of High-Resolution Polarimetric Radar Target Down-Range Signatures Using Kennaugh’s and Huynen’s Target Characteristic Operator Theories." In Inverse Methods in Electromagnetic Imaging, 695–720. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-010-9444-3_42.

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"Modelling spectroscopic and polarimetric signatures of exoplanets." In Extra-Solar Planets, 67–96. CRC Press, 2010. http://dx.doi.org/10.1201/b10365-12.

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Stam, Daphne. "Modelling spectroscopic and polarimetric signatures of exoplanets." In Extra-Solar Planets, 49–77. Taylor & Francis, 2010. http://dx.doi.org/10.1201/b10365-6.

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Kasen, D. "A hole in Ia? Spectroscopic and polarimetric signatures of SN Ia asymmetry due to a companion star." In Cosmic Explosions in Three Dimensions, 166–72. Cambridge University Press, 2004. http://dx.doi.org/10.1017/cbo9780511536236.019.

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Conference papers on the topic "Polarimetric signature"

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Migliaccio, Maurizio, Ferdinando Nunziata, and Attilio Gambardella. "Polarimetric signature for oil spill observation." In 2008 IEEE/OES US/EU-Baltic International Symposium (BALTIC). IEEE, 2008. http://dx.doi.org/10.1109/baltic.2008.4625555.

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Mujat, Mircea, Alexander Spier, and Aristide Dogariu. "Polarimetric signature of dense scattering media." In Optical Science and Technology, SPIE's 48th Annual Meeting, edited by Joseph A. Shaw and J. Scott Tyo. SPIE, 2003. http://dx.doi.org/10.1117/12.506109.

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Verma, Abhinav, Subhadip Dey, Narayanarao Bhogapurapu, Dipankar Mandal, Dipanwita Haldar, and Avik Bhattacharya. "Polarimetric SAR Signature for Crop Characterization." In IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2021. http://dx.doi.org/10.1109/igarss47720.2021.9553979.

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Cremer, Frank, Wim de Jong, Klamer Schutte, Joel T. Johnson, and Brian A. Baertlein. "Surface mine signature modeling for passive polarimetric IR." In AeroSense 2002, edited by J. Thomas Broach, Russell S. Harmon, and Gerald J. Dobeck. SPIE, 2002. http://dx.doi.org/10.1117/12.479142.

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Wu, Stewart H., De-Ming Yang, Arthur Chiou, Soe-Mie F. Nee, and Tsu-Wei Nee. "Polarimetric signature imaging of anisotropic bio-medical tissues." In BiOS, edited by Ramesh Raghavachari and Rongguang Liang. SPIE, 2010. http://dx.doi.org/10.1117/12.845510.

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Lee, J. S., T. Ainsworth, E. Krogagor, and W. M. Boerner. "Polarimetric Analysis of Radar Signature of a Manmade Structure." In 2006 IEEE International Symposium on Geoscience and Remote Sensing. IEEE, 2006. http://dx.doi.org/10.1109/igarss.2006.21.

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Krogager, Ernst, Jong-Sen Lee, Wolfgang-Martin Boerner, and Thomas L. Ainsworth. "Polarimetric Analysis of Radar Signature of a Manmade Structure." In 2006 International Radar Symposium. IEEE, 2006. http://dx.doi.org/10.1109/irs.2006.4338094.

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Lee, Jong-Sen, Ernst Krogager, Thomas L. Ainsworth, and Wolfgang-Martin Boerner. "Polarimetric Analysis of Radar Signature of a Manmade Structure." In 2006 7th International Symposium on Antennas, Propagation & EM Theory. IEEE, 2006. http://dx.doi.org/10.1109/isape.2006.353488.

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Lee, Jong-Sen, Ernst Krogager, Thomas L. Ainsworth, and Wolfgang-Martin Boerner. "Polarimetric Analysis of Radar Signature of a Manmade Structure." In 2007 Asia-Pacific Microwave Conference - (APMC 2007). IEEE, 2007. http://dx.doi.org/10.1109/apmc.2007.4555167.

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Verma, Abhinav, Subhadip Dey, Narayanarao Bhogapurapu, Carlos Lopez-Martinez, and Avik Bhattacharya. "Dual Polarimetric Sar Signature For Human-Made Target Characterization." In 2021 IEEE International India Geoscience and Remote Sensing Symposium (InGARSS). IEEE, 2021. http://dx.doi.org/10.1109/ingarss51564.2021.9792130.

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Reports on the topic "Polarimetric signature"

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Giles, R. H., W. T. Kersey, M. S. McFarlin, B. G. Woodruff, R. Finley, and W. E. Nixon. A Multiple Resolution Study of Ka-Band HRR Polarimetric Signature Data. Fort Belvoir, VA: Defense Technical Information Center, August 2000. http://dx.doi.org/10.21236/ada461958.

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2

Bringi, V. M., and J. Hubbert. Validation of Polarimetric Radar Signatures Using the 2D-Video Distrometer. Fort Belvoir, VA: Defense Technical Information Center, October 1997. http://dx.doi.org/10.21236/ada334153.

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3

Chipman, Russell A., Pierre-Yves Gerligand, and Matthew H. Smith. Polarization Diversity Active Imaging: Mueller Matrix Imaging Polarimetry of Spheres and Cones Estimation of the Refractive Index from the Polarization Signatures. Fort Belvoir, VA: Defense Technical Information Center, January 1998. http://dx.doi.org/10.21236/ada338562.

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