Nonparametric Bayesian time-series modeling and clustering of time-domain ground penetrating radar landmine responses

2010 ◽  
Author(s):  
Kenneth D. Morton, Jr. ◽  
Peter A. Torrione ◽  
Leslie Collins
Keyword(s):  
Time Series ◽  
Time Domain ◽  
Ground Penetrating Radar ◽  
Time Series Modeling ◽  
Nonparametric Bayesian ◽  
Ground Penetrating ◽  
Bayesian Time Series

scholarly journals Study Effect of Objects Orientation in the Mediums On GPR Signal Reflections Using FDTD Simulation

2018 ◽  
Vol 3 (11) ◽  
pp. 73-77
Author(s):  
Aye Mint Mohamed Mostapha ◽  
Gamil Alsharahi ◽  
Abdellah Driouach
Keyword(s):  
Finite Difference ◽  
Time Domain ◽  
Ground Penetrating Radar ◽  
High Frequency ◽  
Electromagnetic Waves ◽  
Ground Surface ◽  
Propagation Path ◽  
Fdtd Simulation ◽  
Ground Penetrating ◽  
Dielectric Objects

Ground penetrating radar (GPR) is a very effective tool for detecting and identifying objects below the ground surface.  based on  the propagation and reflection of high-frequency electromagnetic waves. The GPR reflection can be affected by many things like the type of objects orientation, their shapes ..ect. The purpose of this paper is to  study by simulation the effect of objects orientation in two different mediums (dry and wet sand) on the GPR signal reflection using Reflexw software which is based on a numerical method known as finite difference in time domain (FDTD).  The simulations that have been realized included a conductor  and dielectric objects. The results obtained have led us to find that the propagation path, the reflection strength and the signal form change with the change of object orientation and nature. To confirm the validity of the results, we compared them with experimental results previously published by researchers under the same conditions.

scholarly journals Advances in Bayesian Time Series Modeling and the Study of Politics: Theory Testing, Forecasting, and Policy Analysis

2006 ◽  
Vol 14 (1) ◽  
pp. 1-36 ◽  
Author(s):  
Patrick T. Brandt ◽  
John R. Freeman
Keyword(s):  
Time Series ◽  
Policy Analysis ◽  
Theory Testing ◽  
Multiple Time ◽  
Shape Error ◽  
Time Series Modeling ◽  
International Conflicts ◽  
Bayesian Approaches ◽  
Recent Developments ◽  
Bayesian Time Series

Bayesian approaches to the study of politics are increasingly popular. But Bayesian approaches to modeling multiple time series have not been critically evaluated. This is in spite of the potential value of these models in international relations, political economy, and other fields of our discipline. We review recent developments in Bayesian multi-equation time series modeling in theory testing, forecasting, and policy analysis. Methods for constructing Bayesian measures of uncertainty of impulse responses (Bayesian shape error bands) are explained. A reference prior for these models that has proven useful in short- and medium-term forecasting in macroeconomics is described. Once modified to incorporate our experience analyzing political data and our theories, this prior can enhance our ability to forecast over the short and medium terms complex political dynamics like those exhibited by certain international conflicts. In addition, we explain how contingent Bayesian forecasts can be constructed, contingent Bayesian forecasts that embody policy counterfactuals. The value of these new Bayesian methods is illustrated in a reanalysis of the Israeli-Palestinian conflict of the 1980s.

GPR attenuation and its numerical simulation in 2.5 dimensions

Geophysics ◽  
1997 ◽  
Vol 62 (2) ◽  
pp. 403-414 ◽  
Author(s):  
Tong Xu ◽  
George A. McMechan
Keyword(s):  
Time Domain ◽  
Ground Penetrating Radar ◽  
Finite Difference Time Domain ◽  
Superposition Method ◽  
Frequency Data ◽  
Buried Pipe ◽  
Ground Penetrating ◽  
Cole Model ◽  
Difference Time

Modeling of ground‐penetrating radar (GPR) data in 2.5 dimensions is implemented by superposition of 2-D finite‐difference, time‐domain solutions of Maxwell's equations for different horizontal wavenumbers. Dielectric, magnetic, and conductive losses are included in a single formulation. Attenuations associated with dielectric and magnetic relaxations are introduced by superposition of Debye functions at a set of relaxation frequencies and using memory variables to replace convolutions between the field variables and the decay functions. Better fits to data may always be obtained using the superposition method than by the Cole‐Cole model. Good fits to both loss‐tangent versus frequency data from lab measurements, and to 500 and 900 MHz field GPR profiles of a buried pipe and the surrounding layers, demonstrate the flexibility and viability of the modeling algorithm. Discrepancies between lab and in‐situ measurements may be attributed to scale differences and local variations that make lab samples less representative of the site than the GPR profile.

The application of time domain ground penetrating radar to evaluate railway track ballast

1999 ◽  
Vol 32 (8) ◽  
pp. 463-468 ◽  
Author(s):  
G.P. Gallagher ◽  
Q. Leiper ◽  
R. Williamson ◽  
M.R. Clark ◽  
M.C. Forde
Keyword(s):  
Time Domain ◽  
Ground Penetrating Radar ◽  
Railway Track ◽  
Ground Penetrating
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