scholarly journals Use of Sonification of Radar Data for Noise Control

2017 ◽  
Author(s):  
Kees van den Doel ◽  
Michael Robinson
Keyword(s):  
Temporal Pattern ◽  
User Study ◽  
Radar Data ◽  
Individual Performance ◽  
Frequency Data ◽  
Subsurface Structures ◽  
Peripheral Equipment ◽  
Time Scaling ◽  
Time Invariant ◽  
Deep Sounding

Deep sounding radar surveys for geophysical exploration requires the detection of faint reflections from deep subsurface structures. Signal to noise enhancement through extensive data stacking is effective provided the data noise is incoherent and time-invariant. We describe the use of sonification of radar data for quality control of peripheral equipment, specifically to detect unwanted noise with a temporal pattern. The sonification process consists of filtering and time-scaling radio frequency data and interpreting the result as audio, a process usually referred to as auralization. A small user study was performed to quantify variations in individual performance in detecting these.

scholarly journals Internal ice-sheet radar layer profiles and their relation to reflection mechanisms between Dome C and the Transantarctic Mountains

2001 ◽  
Vol 47 (157) ◽  
pp. 205-212 ◽  
Author(s):  
Martin J. Siegert ◽  
Shuji Fujita
Keyword(s):  
Accurate Determination ◽  
Ice Sheet ◽  
Radar Data ◽  
Internal Reflection ◽  
Frequency Data ◽  
Dual Frequency ◽  
Simple Method ◽  
Antarctic Research ◽  
Transantarctic Mountains

AbstractCauses of ice-sheet layering at ice depths greater than about 900 mina transect between Dome C and the Transantarctic Mountains are examined using 60 MHz radar data, collected in the 1970s by the U.K.–U.S.–Danish collaboration. Normally, a dual-frequency technique is required for accurate determination of internal reflection mechanisms. However, by extracting the depth-related features of 60 MHz radar profiles and comparing them with the dual-frequency data collected by the Japanese Antarctic Research Expedition, we have identified a simple method to estimate internal reflection mechanisms. Two zones can be distinguished: (1) the CA zone, where change in electrical conductivity due to variation in acidity is the major cause of internal reflection, and (2) the PCOF zone, where change in dielectric permittivity due to crystal-orientation fabrics is the major cause of internal reflections. Our analysis shows that the radar data reveal the development of PCOF zones in regions where large amounts of ice shearing are expected. This analysis shows how a similar interpretation of the full radar-data archive may reveal information on internal reflection mechanisms across a large part of the East Antarctic ice sheet.

Measuring Effectiveness of Graph Visualizations: A Cognitive Load Perspective

2009 ◽  
Vol 8 (3) ◽  
pp. 139-152 ◽  
Author(s):  
Weidong Huang ◽  
Peter Eades ◽  
Seok-Hee Hong
Keyword(s):  
Cognitive Load ◽  
Task Performance ◽  
Performance Measures ◽  
User Study ◽  
Processing System ◽  
Mental Effort ◽  
Human Memory ◽  
Individual Performance ◽  
Cognitive Effort ◽  
Graph Visualization

Graph visualizations are typically evaluated by comparing their differences in effectiveness, measured by task performance such as response time and accuracy. Such performance-based measures have proved to be useful in their own right. There are some situations, however, where the performance measures alone may not be sensitive enough to detect differences. This limitation can be seen from the fact that the graph viewer may achieve the same level of performance by devoting different amounts of cognitive effort. In addition, it is not often that individual performance measures are consistently in favor of a particular visualization. This makes design and evaluation difficult in choosing one visualization over another. In an attempt to overcome the above-mentioned limitations, we measure the effectiveness of graph visualizations from a cognitive load perspective. Human memory as an information processing system and recent results from cognitive load research are reviewed first. The construct of cognitive load in the context of graph visualization is proposed and discussed. A model of user task performance, mental effort and cognitive load is proposed thereafter to further reveal the interacting relations between these three concepts. A cognitive load measure called mental effort is introduced and this measure is further combined with traditional performance measures into a single multi-dimensional measure called visualization efficiency. The proposed model and measurements are tested in a user study for validity. Implications of the cognitive load considerations in graph visualization are discussed.

scholarly journals Combination of Kirchhoff migration method and the energy diagram in the process of ground penetrating radar data

2015 ◽  
Vol 18 (4) ◽  
pp. 42-50
Author(s):  
Van Thanh Nguyen ◽  
Thuan Van Nguyen ◽  
Trung Hoai Dang
Keyword(s):  
Ground Penetrating Radar ◽  
High Reliability ◽  
Theoretical Models ◽  
Radar Data ◽  
Velocity Estimation ◽  
Energy Diagram ◽  
Subsurface Structures ◽  
Kirchhoff Migration ◽  
Migration Method ◽  
Ground Penetrating

Kirchhoff migration in ground penetrating radar (GPR) has been the technique of collapsing diffraction events on unmigrated records to points, thus moving reflection events to their proper locations and creating a true image of subsurface structures. Today, the scope of Kirchhoff migration has been broadened and is a tool for electromagnetic wave velocity estimation. To optimize this algorithm, we propose using the energy diagram as a criterion of looking for the correct propagation velocity. Using theoretical models, we demonstrated that the calculated velocities were the same as the root mean square ones up to the top of objects. The results verified on field data showed that improved sections could be obtained and the size as well as depth of anomalies were determined with high reliability.

scholarly journals An Improved QPE over Complex Terrain Employing Cloud-to-Ground Lightning Occurrences

2017 ◽  
Vol 56 (9) ◽  
pp. 2489-2507 ◽  
Author(s):  
Carlos Manuel Minjarez-Sosa ◽  
Christopher L. Castro ◽  
Kenneth L. Cummins ◽  
Julio Waissmann ◽  
David K. Adams
Keyword(s):  
Kalman Filter ◽  
Heavy Precipitation ◽  
Radar Data ◽  
Rain Gauge ◽  
Time Lags ◽  
Sensor Coverage ◽  
Lightning Detection ◽  
Precipitation Estimation ◽  
Cloud To Ground Lightning ◽  
Time Invariant

AbstractA lightning–precipitation relationship (LPR) is studied at high temporal and spatial resolution (5 min and 5 km). As a proof of concept of these methods, precipitation data are retrieved from the National Severe Storms Laboratory (NSSL) NMQ product for southern Arizona and western Texas while lightning data are provided by the National Lightning Detection Network (NLDN). A spatial- and time-invariant (STI) linear model that considers spatial neighbors and time lags is proposed. A data denial analysis is performed over Midland, Texas (a region with good sensor coverage), with this STI model. The LPR is unchanged and essentially equal, regardless of the domain (denial or complete) used to obtain the STI model coefficients. It is argued that precipitation can be estimated over regions with poor sensor coverage (i.e., southern Arizona) by calibrating the LPR over well-covered domains that are experiencing similar storm conditions. To obtain a lightning-estimated precipitation that dynamically updates the model coefficients in time, a Kalman filter is applied to the STI model. The correlation between the observed and estimated precipitation is statistically significant for both models, but the Kalman filter provides a better precipitation estimation. The best demonstration of this application is a heavy-precipitation, high-frequency lightning event in southern Arizona over a region with poor radar and rain gauge coverage. By calibrating the Kalman filter over a data-covered domain, the lightning-estimated precipitation is considerably greater than that estimated by radar alone. Therefore, for regions where both rain gauge and radar data are compromised, lightning provides a viable alternative for improving QPE.

scholarly journals The Application of Depth Migration for Processing GPR Data

2018 ◽  
Vol 35 ◽  
pp. 03004
Author(s):  
Dang Hoai Trung ◽  
Nguyen Van Giang ◽  
Nguyen Thanh Van
Keyword(s):  
Significant Role ◽  
Ground Penetrating Radar ◽  
Field Data ◽  
Velocity Model ◽  
Radar Data ◽  
Energy Diagram ◽  
Depth Migration ◽  
Subsurface Structures ◽  
Calculated Velocity ◽  
Ground Penetrating

Migration methods play a significant role in processing ground penetrating radar data. Beside recovering the true image of subsurface structures from the prior designed velocity model and the raw GPR data, the migration algorithm could be an effective tool in bulding real environmental velocity model. In this paper, we have proposed one technique using energy diagram extracted from migrated data as a criterion of looking for the correct velocity. Split Step Fourier migration, a depth migration, is chosen for facing the challenge where the velocity varies laterally and vertically. Some results verified on field data on Vietnam show that migrated sections with calculated velocity from energy diagram have the best quality.

scholarly journals The application of split step fourier migration to interpreting GPR data in Vietnam

2017 ◽  
Vol 17 (4B) ◽  
pp. 161-166
Author(s):  
Dang Hoai Trung ◽  
Nguyen Van Giang ◽  
Nguyen Thanh Van ◽  
Nguyen Van Thuan ◽  
Vo Minh Triet
Keyword(s):  
Ground Penetrating Radar ◽  
Field Data ◽  
Real Data ◽  
Radar Data ◽  
Electromagnetic Propagation ◽  
Energy Diagram ◽  
Subsurface Structures ◽  
Reliable Performance ◽  
Calculated Velocity ◽  
Ground Penetrating

Migration methods play an essential role in processing ground penetrating radar data. For estimating electromagnetic propagation velocity distribution, the finite - difference migration is used because of its reliable performance with high noise conditions. To optimize this migration algorithm, we propose using energy diagram as a criterion of looking for the correct velocity. If the velocity varies laterally and vertically, split step Fourier migration is used for creating a true image of subsurface structures. We applied these steps to real data in Vietnam. The results verified on field data show that migrated images with calculated velocity from energy diagram have the best quality.

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