Overview of Computational Testbed for Evaluating Electro-Optical/Infrared Sensor Systems

被引:6
作者
Kala, Raju V. [1 ]
Fairley, Josh R. [1 ]
Price, Stephanie J. [1 ]
Ballard, Jerry R., Jr. [1 ]
Carrillo, Alex R. [1 ]
Howington, Stacy E. [1 ]
Eslinger, Owen J. [1 ]
Hines, Amanda M. [1 ]
Goodson, Ricky A. [1 ]
机构
[1] USA, Corps Engineers, Engn Res & Dev Ctr, Vicksburg, MS 39180 USA
来源
DETECTION AND SENSING OF MINES, EXPLOSIVE OBJECTS, AND OBSCURED TARGETS XVII | 2012年 / 8357卷
关键词
Computation Testbed; High Performance Computing; Geophysical Modeling and Imaging; MODEL;
D O I
10.1117/12.922910
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
The U. S. Army Engineer Research and Development Center (ERDC) developed a near-surface computational testbed (CTB) for modeling geo-environments. This modeling capability is used to predict and improve the performance of current and future-force sensor systems for surface and near-surface threat detection for a wide range of geo-environments. The CTB is a suite of integrated models and tools used to approximately replicate geo-physical processes such as radiometry, meteorology, moisture transport, and thermal transport that influence the resultant signatures of both natural and man-made materials, as perceived by the sensors. The CTB is designed within a High Performance Computing (HPC) framework to accommodate the size and complexity of the virtual environments required for analyzing and quantifying sensor performance. Specifically, as a rule-of-thumb, the size of the scene should encompass an area that is at a minimum, the size of the spatial coverage of the sensor. This HPC capability allows the CTB to replicate geophysical processes and subsurface heterogeneity with high levels of realism and to provide new insight into identifying the geophysical processes and environmental factors that significantly affect the signatures sensed by multispectral imaging, near-infrared, mid-wave infrared, long-wave infrared, and ground penetrating radar sensors. Additionally, this effort is helping to quantify the performance and optimal time-of-use for sensors to detect threats within highly heterogeneous geo-environments by reducing false alarms from automated target recognition algorithms.
引用
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页数:7
相关论文
共 9 条
[1]  
Berney IV E.S., 2010, TR1023 ERDC US ARM E
[2]   Moisture effects on the dielectric properties of soils [J].
Curtis, JO .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2001, 39 (01) :125-128
[3]  
Kala R.V., 2010, P 9 WORLD C COMP MEC
[4]   RADIATIVE-TRANSFER MODEL FOR HETEROGENEOUS 3-D SCENES [J].
KIMES, DS ;
KIRCHNER, JA .
APPLIED OPTICS, 1982, 21 (22) :4119-4129
[5]   NUMERICAL MODELING OF A SPIRAL-ANTENNA GPR SYSTEM [J].
McFadden, Michael ;
Scott, Waymond R., Jr. .
2009 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-5, 2009, :360-363
[6]  
Peters JF, 2007, PROCEEDINGS OF THE HPCMP USERS GROUP CONFERENCE 2007, P238
[7]  
SCHMIDT J, 1995, THESIS U TEXAS AUSTI
[8]   Description of the IR sensor model for the countermine computational testbed [J].
Scoggins, RK ;
Sabol, BM .
Detection and Remediation Technologies for Mines and Minelike Targets X, Pts 1 and 2, 2005, 5794 :882-888
[9]   Thermal infrared hot spot and dependence on canopy geometry [J].
Smith, JA ;
Ballard, JR .
OPTICAL ENGINEERING, 2001, 40 (08) :1435-1437