Inversion of Microwave Scattering Patterns

1971 ◽  
Vol 49 (24) ◽  
pp. 3082-3094 ◽  
Author(s):  
A. Fedotowsky ◽  
G. Boivin ◽  
R. Tremblay
Keyword(s):  
Dielectric Constant ◽  
Radial Variation ◽  
Inversion Method ◽  
Microwave Scattering ◽  
Scattering Pattern ◽  
Dielectric Target

An inversion method which reproduces the radial variation of dielectric constant in a dielectric target from its microwave scattering pattern is presented. Inversion criteria are developed showing what part of the target can be reconstructed. The technique is applied to experimentally measured scattering patterns.

Ü-Net: Deep-Learning Schemes for Ground Penetrating Radar Data Inversion

2020 ◽  
Vol 25 (2) ◽  
pp. 287-292
Author(s):  
Longhao Xie ◽  
Qing Zhao ◽  
Chunguang Ma ◽  
Binbin Liao ◽  
Jianjian Huo
Keyword(s):  
Neural Network ◽  
Dielectric Constant ◽  
Data Compression ◽  
Ground Penetrating Radar ◽  
Quantitative Imaging ◽  
Inversion Method ◽  
Output Unit ◽  
Data Inversion ◽  
Ground Penetrating ◽  
Constant Distribution

Electromagnetic (EM) inversion is a quantitative imaging technique that can describe the dielectric constant distribution of a target based on the EM signals scattered from it. In this paper, a novel deep neural network (DNN) based methodology for ground penetrating radar (GPR) data inversion, known as the Ü-net is introduced. The proposed Ü-net consists of three parts: a data compression unit, U-net, and an output unit. The novel inversion approach, based on supervised learning, uses a neural network to generate the dielectric constant distribution from GPR data. The GPR data can be compressed and reshaped the size using data compression unit. The U-net maps the object features to the dielectric constant distribution. The output unit meshes the dielectric constant distribution more finely. A novel feature of the proposed methodology is the application of instance normalization (IN) to the DNN EM inversion method and a comparison of its performance to batch normalization (BN). The validity of this technique is confirmed by numerical simulations. The Mean-Square Error of the test data sets is 0.087. These simulations prove that the instance normalization is suitable for GPR data inversion. The proposed approach is promising for achieving quality dielectric constant images in real-time.

Simulation of complex dielectric structures

1970 ◽  
Vol 48 (21) ◽  
pp. 2623-2628
Author(s):  
A. Fedotowsky ◽  
G. Boivin ◽  
A. K. Sen ◽  
R. Tremblay
Keyword(s):  
Dielectric Constant ◽  
Continuous Variation ◽  
Experimental Results ◽  
Microwave Scattering ◽  
Dielectric Structures

Methods for simulating dielectric targets having a continuous variation of the dielectric constant for microwave scattering purposes are described. Experimental results are also presented.

scholarly journals An inversion method based on multi-angular approaches for estimating bare soil surface parameters from RADARSAT-1

2009 ◽  
Vol 6 (1) ◽  
pp. 207-241 ◽  
Author(s):  
M. R. Sahebi ◽  
J. Angles
Keyword(s):  
Surface Roughness ◽  
Dielectric Constant ◽  
Soil Moisture ◽  
Soil Surface ◽  
Bare Soil ◽  
Earth Observation ◽  
Radar Signal ◽  
Inversion Method ◽  
Inversion Algorithm ◽  
Soil Surface Roughness

Abstract. The radar signal recorded by earth observation (EO) satellites is known to be sensitive to soil moisture and soil surface roughness, which influence the onset of runoff. This paper focuses on the inversion of these parameters using a multi-angular approach based on RADARSAT-1 data with incidence angles of 35° and 47° (in mode S3 and S7). This inversion was done based on three backscatter models: Geometrical Optics Model (GOM), Oh Model (OM) and Modified Dubois Model (MDM), which are compared in order to obtain the best configuration. For roughness expressed in rms of heights, mean absolute errors of 1.23 cm, 1.12 cm and 2.08 cm, and for dielectric constant, mean absolute errors of 2.46, 4.95 and 3.31 were obtained for the MDM, GOM and the OM simulation, respectively. This means that the MDM provided the best results with minimum errors. Based on these results, the latter inversion algorithm was applied on the images and the final results are presented in two different maps showing pixel and homogeneous zones for surface roughness and soil moisture.

An Inversion Method on Formation Dielectric Constant and Resistivity by using High Frequency Electromagnetic Wave Logging

2002 ◽  
Vol 45 (3) ◽  
pp. 450-460 ◽  
Author(s):  
Guang-Long XING ◽  
Mei-Ling ZHANG ◽  
Man-Fen LIU ◽  
Shan-De YANG
Keyword(s):  
Dielectric Constant ◽  
Electromagnetic Wave ◽  
High Frequency ◽  
Inversion Method

Modeling of Microwave Scattering From Cloud Ice Crystal Aggregates and Melting Aggregates: A New Approach

2010 ◽  
Vol 7 (3) ◽  
pp. 572-576 ◽  
Author(s):  
Giovanni Botta ◽  
Kültegin Aydin ◽  
Johannes Verlinde
Keyword(s):  
Dielectric Constant ◽  
Cross Sections ◽  
Melting Process ◽  
Effective Dielectric Constant ◽  
Ice Crystal ◽  
New Approach ◽  
Microwave Scattering ◽  
Spheroidal Shape ◽  
Cloud Ice ◽  
Scattering Cross Sections

Ice crystal aggregates and their melting process are modeled with a new approach for determining their microwave scattering characteristics and are compared with those obtained using effective dielectric constant representations. The aggregates are constructed from columnar crystals of random lengths (with the width being a function of the length), which are composed of a string of touching ice spheres with diameters equal to the column's width. The aggregates are melted using a model that incorporates the primary aspects of experimentally observed features of the melting process. The generalized multiparticle Mie method is used for computing the scattering cross sections of the dry and melting aggregates. The T-matrix method is used for computations involving a bulk representation of each aggregate with an effective dielectric constant model and an oblate spheroidal shape. The 3- and 35.6-GHz backscattering cross sections show significant differences between the two methods for both dry and melting aggregates. For sizes larger than 3 mm, these differences range from several decibels at 3 GHz to well over 7 dB at 35.6 GHz. Significant differences are also observed in the extinction cross sections during the melting process. It is concluded that the effective dielectric constant models of dry and melting ice crystal aggregates do not represent the interactions between the constituent crystals (and water droplets during melting) of the aggregates very well. Hence, bulk models must be used with caution particularly at millimeter wavelengths.

scholarly journals Dielectric constant extraction of graphene nanostructured on SiC substrates from spectroscopy ellipsometry measurement using Gauss–Newton inversion method

2016 ◽  
Author(s):  
Hervin Maulina ◽  
Iman Santoso ◽  
Emmistasega Subama ◽  
Pekik Nurwantoro ◽  
Kamsul Abraha ◽  
...  
Keyword(s):  
Dielectric Constant ◽  
Inversion Method ◽  
Ellipsometry Measurement
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