Monitoring of parameters of coastal Arctic ecosystems for sustainability control by remote sensing in the short-wave range of radio waves with use of the experimental equipment of coherent reception of a ground-based measuring complex

2017 ◽  
Vol 7 (2) ◽  
pp. 216-231
Author(s):  
Sergej Yurievich Belov

Monitoring of the earth's surface by remote sensing in the short-wave band can provide a quick identification of some characteristics of coastal Arctic ecosystems. This band range allows to diagnose subsurface aspects of the earth, as the scattering parameter is affected by irregularities in the dielectric permittivity of subsurface structures. This method is based on the organization of the monitoring probe and may detect changes in these environments, for example, to assess hazardous natural phenomena, assessing sustainability, as well as some man-made hazards and etc. The problem of measuring and accounting for the scattering power of the earth's surface in the short-range of radio waves is important for a number of purposes, such as e.g diagnosing properties of the medium, which is of interest for geological, environmental studies. In this paper, we propose a new method for estimating the parameters of incoherent signal/noise ratio. The paper presents the results of comparison of the measurement method from the point of view of their admissible relative analytical errors. The new method is suggested. Accuracy new method on the order exceeds the widely-used standard method. Interpretation of the data is based on a statistical multiplicative model of the signal. Testing the method of obtained a signal/noise ratio in this model was produced by the example of a double reflection of the probe signal from the SW ionosphere in a vertical sounding (when using a satellite, the signal passes twice through the atmosphere and ionosphere). In this paper, a sensitivity of the model parameters was studied. To obtain the necessary experimental data, the pulse method of coherent reception was used. Analysis of analytical error of estimation of this parameter allowed to recommend a new method instead of standard method. A comparative analysis showed that the analytical (relative) accuracy of the determination of this parameter by a new method exceeded the widely-used standard method by the factor of ten.

Author(s):  
Sergej Belov ◽  
Sergej Belov ◽  
Ija Belova ◽  
Ija Belova ◽  
Stepan Falomeev ◽  
...  

A new method for estimating the parameter noncoherent signal/noise K of ionospheric signal is offered. A comparative analysis is carrying out. This new method exceeds an order of magnitude widely used standard one by analytical (relative) accuracy of determining a parameter K. It has the same order as the well-known coherent methodology.


Author(s):  
Sergej Belov ◽  
Sergej Belov ◽  
Ija Belova ◽  
Ija Belova ◽  
Stepan Falomeev ◽  
...  

A new method for estimating the parameter noncoherent signal/noise K of ionospheric signal is offered. A comparative analysis is carrying out. This new method exceeds an order of magnitude widely used standard one by analytical (relative) accuracy of determining a parameter K. It has the same order as the well-known coherent methodology.


Author(s):  
R. F. Egerton

An important parameter governing the sensitivity and accuracy of elemental analysis by electron energy-loss spectroscopy (EELS) or by X-ray emission spectroscopy is the signal/noise ratio of the characteristic signal.


2012 ◽  
Vol 71 (5) ◽  
pp. 445-453
Author(s):  
M. D. Rasnikov ◽  
I. T. Rozhkov

Author(s):  
Ryan Xiao ◽  
William Wang ◽  
Ang Li ◽  
Shengqiu Xu ◽  
Binghai Liu

Abstract With the development of semiconductor technology and the increment quantity of metal layers in past few years, backside EFA (Electrical Failure Analysis) technology has become the dominant method. In this paper, abnormally high Signal Noise Ratio (SNR) signal captured by Electro-Optical Probing (EOP)/Laser Voltage Probing (LVP) from backside is shown and the cause of these phenomena are studied. Based on the real case collection, two kinds of failure mode are summarized, and simulated experiments are performed. The results indicate that when a current path from power to ground is formed, the high SNR signal can be captured at the transistor which was on this current path. It is helpful of this consequence for FA to identify the failure mode by high SNR signal.


Author(s):  
Leijin Long ◽  
Feng He ◽  
Hongjiang Liu

AbstractIn order to monitor the high-level landslides frequently occurring in Jinsha River area of Southwest China, and protect the lives and property safety of people in mountainous areas, the data of satellite remote sensing images are combined with various factors inducing landslides and transformed into landslide influence factors, which provides data basis for the establishment of landslide detection model. Then, based on the deep belief networks (DBN) and convolutional neural network (CNN) algorithm, two landslide detection models DBN and convolutional neural-deep belief network (CDN) are established to monitor the high-level landslide in Jinsha River. The influence of the model parameters on the landslide detection results is analyzed, and the accuracy of DBN and CDN models in dealing with actual landslide problems is compared. The results show that when the number of neurons in the DBN is 100, the overall error is the minimum, and when the number of learning layers is 3, the classification error is the minimum. The detection accuracy of DBN and CDN is 97.56% and 97.63%, respectively, which indicates that both DBN and CDN models are feasible in dealing with landslides from remote sensing images. This exploration provides a reference for the study of high-level landslide disasters in Jinsha River.


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