scholarly journals Monte Carlo Simulation of the Echo Signals from Low-Flying Targets for Airborne Radar

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Mingyuan Man ◽  
Zhenya Lei ◽  
Yongjun Xie ◽  
Botao Chen ◽  
Qing Wang
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Half Space ◽  
Ground Surface ◽  
Physical Optics ◽  
Airborne Radar ◽  
Average Value ◽  
The Monte Carlo Method ◽  
Multipath Effects ◽  
Actual Environment

A demonstrated hybrid method based on the combination of half-space physical optics method (PO), graphical-electromagnetic computing (GRECO), and Monte Carlo method on echo signals from low-flying targets based on actual environment for airborne radar is presented in this paper. The half-space physical optics method , combined with the graphical-electromagnetic computing (GRECO) method to eliminate the shadow regions quickly and rebuild the target automatically, is employed to calculate the radar cross section (RCS) of the conductive targets in half space fast and accurately. The direct echo is computed based on the radar equation. The reflected paths from sea or ground surface cause multipath effects. In order to accurately obtain the echo signals, the phase factors are modified for fluctuations in multipath, and the statistical average value of the echo signals is obtained using the Monte Carlo method. A typical simulation is performed, and the numerical results show the accuracy of the proposed method.

scholarly journals MINING BLOCK STABILITY PREDICTION BY THE MONTE CARLO METHOD

2006 ◽  
Vol 1 ◽  
pp. 185
Author(s):  
O. Nikitin
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Oil Shale ◽  
Ground Surface ◽  
Mining System ◽  
Room And Pillar Mining ◽  
The Monte Carlo Method ◽  
Geological Conditions ◽  
Pillar Mining ◽  
Failure Prognosis

This paper analyses the stability of the mining blocks by the Monte Carlo method in Estonian oil shale mines, where the room-and-pillar mining system is used. The pillars are arranged in a singular grid. The oil shale bed is embedded at the depth of 40-75 m. The processes in overburden rocks and pillars have caused the subsidence of the ground surface. Visual Basic for Application was used for the modeling. Through Monte Carlo simulation, room-and-pillar stable parameters can be calculated. Model allows determination of the probability of spontaneous collapse of the pillars and surface subsidence by the parameters of registered collapsed mining blocks. Proposed method suits as an express-method for stability analysis and failure prognosis. It is applicable in different geological conditions, where the room-and-pillar mining system is used.

scholarly journals Monte Carlo Methods and the Koksma-Hlawka Inequality

Mathematics ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 725
Author(s):  
Sergey Ermakov ◽  
Svetlana Leora
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Random Processes ◽  
Random Numbers ◽  
Average Order ◽  
New Approach ◽  
Average Value ◽  
Acceptable Accuracy ◽  
Cubature Formulas ◽  
The Monte Carlo Method

The solution of a wide class of applied problems can be represented as an integral over the trajectories of a random process. The process is usually modeled with the Monte Carlo method and the integral is estimated as the average value of a certain function on the trajectories of this process. Solving this problem with acceptable accuracy usually requires modeling a very large number of trajectories; therefore development of methods to improve the accuracy of such algorithms is extremely important. The paper discusses Monte Carlo method modifications that use some classical results of the theory of cubature formulas (quasi-random methods). A new approach to the derivation of the well known Koksma-Hlawka inequality is pointed out. It is shown that for high ( s > 5 ) dimensions of the integral, the asymptotic decrease of the error comparable to the asymptotic behavior of the Monte Carlo method, can be achieved only for a very large number of nodes N. It is shown that a special criterion can serve as a correct characteristic of the error decrease (average order of the error decrease). Using this criterion, it is possible to analyze the error for reasonable values of N and to compare various quasi-random sequences. Several numerical examples are given. Obtained results make it possible to formulate recommendations on the correct use of the quasi-random numbers when calculating integrals over the trajectories of random processes.

scholarly journals A Method for Estimating the Cloud Adjacency Effect on the Ground Surface Reflectance Reconstruction from Passive Satellite Observations through Gaps in Cloud Fields

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1512
Author(s):  
Mikhail V. Tarasenkov ◽  
Matvei N. Zonov ◽  
Marina V. Engel ◽  
Vladimir V. Belov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Radiation Transfer ◽  
Ground Surface ◽  
Interpolation Formula ◽  
Statistical Simulation ◽  
Satellite Observations ◽  
Surface Reflectance ◽  
Surface Areas ◽  
The Monte Carlo Method

A method for estimating the cloud adjacency effect on the reflectance of ground surface areas reconstructed from passive satellite observations through gaps in cloud fields is proposed. The method allows one to estimate gaps of cloud fields in which the cloud adjacency effect can be considered small (the increment of the reflectance Δrsurf≤ 0.005). The algorithm is based on statistical simulation by the Monte Carlo method of radiation transfer in stochastic broken cloudiness with a deterministic cylindrical gap. An interpolation formula is obtained for the radius of the cloud adjacency effect that can be used for the reconstruction the ground surface reflectance in real time without calculations by the Monte Carlo method.

UGR CALCULATION BASED ON THE LUMINANCE SPATIAL-ANGULAR DISTRIBUTION

2020 ◽  
Vol 2020 (4) ◽  
pp. 25-32
Author(s):  
Viktor Zheltov ◽  
Viktor Chembaev
Keyword(s):  
Monte Carlo ◽  
Angular Distribution ◽  
Monte Carlo Method ◽  
Visual Task ◽  
New Method ◽  
Lighting System ◽  
Preliminary Assessment ◽  
System A ◽  
The Monte Carlo Method

The article has considered the calculation of the unified glare rating (UGR) based on the luminance spatial-angular distribution (LSAD). The method of local estimations of the Monte Carlo method is proposed as a method for modeling LSAD. On the basis of LSAD, it becomes possible to evaluate the quality of lighting by many criteria, including the generally accepted UGR. UGR allows preliminary assessment of the level of comfort for performing a visual task in a lighting system. A new method of "pixel-by-pixel" calculation of UGR based on LSAD is proposed.

PSHA software review based on the Monte Carlo method

2020 ◽  
pp. 14-24
Author(s):  
V.A. Mironov ◽  
S.A. Peretokin ◽  
K.V. Simonov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Seismic Hazard ◽  
Hazard Analysis ◽  
Software Review ◽  
Seismic Hazard Analysis ◽  
Probabilistic Seismic Hazard ◽  
Test Calculation ◽  
Seismic Surveys ◽  
The Monte Carlo Method

The article is a continuation of the software research to perform probabilistic seismic hazard analysis (PSHA) as one of the main stages in engineering seismic surveys. The article provides an overview of modern software for PSHA based on the Monte Carlo method, describes in detail the work of foreign programs OpenQuake Engine and EqHaz. A test calculation of seismic hazard was carried out to compare the functionality of domestic and foreign software.

Application of the Monte Carlo Method for the Prediction of Behavior of Peptides

2019 ◽  
Vol 20 (12) ◽  
pp. 1151-1157 ◽  
Author(s):  
Alla P. Toropova ◽  
Andrey A. Toropov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Natural Sciences ◽  
Monte Carlo Technique ◽  
Quantitative Structure ◽  
Structure Property ◽  
The Monte Carlo Method ◽  
Modern Natural

Prediction of physicochemical and biochemical behavior of peptides is an important and attractive task of the modern natural sciences, since these substances have a key role in life processes. The Monte Carlo technique is a possible way to solve the above task. The Monte Carlo method is a tool with different applications relative to the study of peptides: (i) analysis of the 3D configurations (conformers); (ii) establishment of quantitative structure – property / activity relationships (QSPRs/QSARs); and (iii) development of databases on the biopolymers. Current ideas related to application of the Monte Carlo technique for studying peptides and biopolymers have been discussed in this review.

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