KEYWORDS: Data modeling, Network security, Network architectures, Systems modeling, Computer security, Information security, Sensors, Analytical research, Databases, Defense and security
We address the problem of detecting insider threats before they can do harm. In many cases, co-workers notice indications of suspicious activity prior to insider threat attacks. A partial solution to this problem requires an understanding of how information can better traverse the communication network between human intelligence and insider threat analysts. Our approach employs modern mobile communications technology and scale free network architecture to reduce the network distance between human sensors and analysts. In order to solve this problem, we propose a Vector Relational Data Modeling approach to integrate human “sensors,” geo-location, and existing visual analytics tools. This integration problem is known to be difficult due to quadratic increases in cost associated with complex integration solutions. A scale free network integration approach using vector relational data modeling is proposed as a method for reducing network distance without increasing cost.
KEYWORDS: Systems modeling, Data modeling, Network architectures, Information architecture, Intelligence systems, Systems modeling, Data modeling, Network architectures, Sensors, Modeling and simulation, Digital libraries, Transparency, Cameras
The Global Information Network Architecture is an information technology based on Vector Relational Data Modeling, a unique computational paradigm, DoD network certified by USARMY as the Dragon Pulse Informa- tion Management System. This network available modeling environment for modeling models, where models are configured using domain relevant semantics and use network available systems, sensors, databases and services as loosely coupled component objects and are executable applications. Solutions are based on mission tactics, techniques, and procedures and subject matter input. Three recent ARMY use cases are discussed a) ISR SoS. b) Modeling and simulation behavior validation. c) Networked digital library with behaviors.
Small military units operate under stressful conditions with limited resources. A lightweight mobile surveillance system
could reduce the effort to conduct sentry duties, and could help prevent ambushes or other types of attacks. We explore
the use of built-in sensors and networking abilities of modern "smartphones" to fill this gap. Current smartphones use
accelerometers to sense changes in orientation of the phone. This same capability can be used to detect vibrations in the
ground produced by approaching footsteps or vehicles. We discuss the sensitivity of the phone, the filtering techniques,
and the footstep signatures registered by the phone. We then discuss the possible deployment configurations of single
and multiple sensors to create a sensor grid that can be networked together. Key concerns are ground noise, sensitivity
of the phone, and distance between networked phones.
We describe the concept for a logic-tree based geographic information system (GIS) that can infer subsurface geology
and material properties using geoinformatics concepts. A proof-of-concept system was devised and tested integrating the
capabilities of traditional terrain- and image-analysis procedures with a GIS to manipulate geospatial data. Structured
logic trees were developed to guide an analyst through an interactive, geologic analysis based on querying and
mentoring heuristic logic. The hypotheses were that a GIS can be programmed to 1) follow the fundamental logic
sequence developed for traditional terrain- and image analysis procedures; 2) augment that sequence with correlative
geospatial data from a variety of sources; and 3) integrate the inferences and data to develop "best-guess" estimates. We
also developed a method to estimate depth to bedrock, and expanded an existing method to determine water table depth.
Blind evaluations indicate that an analyst can infer the correct geologic conditions 70-80% of the time using this method.
This geologic analysis technique can be applied wherever an estimate of subsurface geology is needed. We apply the
results of our geological analysis to the prediction of local site specific seismic propagation. Comparisons are made with
synthetic seismograms computed from a limited set of geological vignettes.
KEYWORDS: Acoustics, Sensors, Artillery, Seismic sensors, Signal to noise ratio, Data acquisition, Analytical research, Receivers, Data centers, Neodymium
The US Army Corps of Engineers Research and Development Center participated in a joint ARL-NATO TG-53 field
experiment and data collect at Yuma Proving Ground, AZ in early November 2005. Seismic and acoustic signatures
from both muzzle blasts and impacts of small arms fire and artillery were recorded using 7 seismic arrays and 3 acoustic
arrays. Arrays comprised of 12 seismic and 12 acoustic sensors each were located from 700 m to 18 km from gun
positions. Preliminary analysis of signatures attributed to 60mm, 81mm, 120 mm mortars recorded at a seismic-acoustic
array 1.1 km from gun position are presented. Seismic and acoustic array f-k analysis is performed to detect and
characterize the source signature. Horizontal seismic data are analyzed to determine efficacy of a seismic discriminant
for mortar and artillery sources. Rotation of North and East seismic components to radial and transverse components
relative to the source-receiver path provide maximum surface wave amplitude on the transverse component. Angles of
rotation agree well with f-k analysis of both seismic and acoustic signals. The spectral energy of the rotated transverse
surface wave is observable on the all caliber of mortars at a distance of 1.1 km and is a reliable source discriminant for
mortar sources at this distance. In a step towards automation, travel time stencils using local seismic and acoustic
velocities are applied to seismic data for analysis and determination of source characteristics.
KEYWORDS: Acoustics, Sensors, Artillery, Seismic sensors, Data acquisition, Signal to noise ratio, Meteorology, Receivers, Analytical research, Data centers
The U.S. Army Corps of Engineers Engineer Research and Development Center (ERDC) participated in a joint ARL-NATO TG-53 field experiment and data collection at Yuma Proving Ground, AZ, in early November 2005. Seismic and acoustic signatures from both muzzle blasts and impacts of small arms fire and artillery were recorded using seven seismic arrays and three acoustic arrays. Arrays composed of 12 seismic and 12 acoustic sensors each were located from 700 m to 18 km from gun positions. Preliminary analysis of signatures attributed to 60-mm, 81-mm, and 120-mm mortars recorded at a seismic-acoustic array 1.1 km from gun position are presented. Seismic and acoustic array f-k analysis is performed to detect and characterize the source signature. Horizontal seismic data are analyzed to determine efficacy of a seismic discriminant for mortar and artillery sources. Rotation of North and East seismic components to radial and transverse components relative to the source-receiver path provide maximum surface wave amplitude on the transverse component. Angles of rotation agree well with frequency-wavenumber (f-k) analysis of both seismic and acoustic signals. The spectral energy of the rotated transverse surface wave is observable on all caliber of mortars at a distance of 1.1 km and is a reliable source discriminant for mortar sources at this distance.
Field studies were conducted in 2005 in Yuma, Arizona at the Yuma Proving Grounds (YPG) to document seismic signatures of walking humans. Walker-generated vertical ground vibrations were recorded using standard omni-directional 4.5 Hz peak-resonance geophones. Walker position and speed were measured using portable GPS equipment.
Collected seismic data were processed and hypothetical sensor performance predictions were made using an algorithm developed for the detection and classification of a walking intruder. Sample results for the Yuma study are presented in the form of sensor detection/classification vs. range plots, and color-coded animations of seismic sensor alarm annunciations during walking intruder tests. A perimeter intrusion scenario for a Forward Operating Base is defined that involves a walker approaching a sensor picket-line along a path exactly halfway between two adjacent sensors. This is considered a conservative representation of the perimeter intrusion problem. Summary plots derived from a binomial probability based analysis define intruder detection probabilities for different sensor spacings. For a 215 lb intruder walking in the Yuma test environment, a 90% probability of at least two walker-classified sensor detections is achieved at a sensor spacing of 140 m.
Preliminary investigations show the intruder classification component of the discussed detection/classification algorithm to perform well at rejecting signals associated with a nearby idling vehicle and normal background noise.
This paper describes development and application of a high-fidelity, seismic/acoustic simulation capability for battlefield sensors. The purpose is to provide simulated sensor data so realistic that they cannot be distinguished by experts from actual field data. This emerging capability provides rapid, low-cost trade studies of unattended ground sensor network configurations, data processing and fusion strategies, and signatures emitted by prototype vehicles. There are three essential components to the modeling: (1) detailed mechanical signature models for vehicles and walkers, (2) high-resolution characterization of the subsurface and atmospheric environments, and (3) state-of-the-art seismic/acoustic models for propagating moving-vehicle signatures through realistic, complex environments. With regard to the first of these components, dynamic models of wheeled and tracked vehicles have been developed to generate ground force inputs to seismic propagation models. Vehicle models range from simple, 2D representations to highly detailed, 3D representations of entire linked-track suspension systems. Similarly detailed models of acoustic emissions from vehicle engines are under development. The propagation calculations for both the seismics and acoustics are based on finite-difference, time-domain (FDTD) methodologies capable of handling complex environmental features such as heterogeneous geologies, urban structures, surface vegetation, and dynamic atmospheric turbulence. Any number of dynamic sources and virtual sensors may be incorporated into the FDTD model. The computational demands of 3D FDTD simulation over tactical distances require massively parallel computers. Several example calculations of seismic/acoustic wave propagation through complex atmospheric and terrain environments are shown.
Long duration finite-difference time domain (FDTD) simulations of seismic wave propagation from spatially and time varying sources are necessary to produce synthetic data of ground motion, data that is required for the development of unmanned ground sensor systems, which are the next wave in modern battlefield technology. We have generated data from moving synthetic sources that are typically found in a battlefield scenario, a generic representation of a moving tracked vehicle and a running human. The computational approach and requirements for the long-duration simulation including the geologic model, the moving vehicle force algorithm, the resulting particle velocity wave fields, and example applications of the data are discussed.
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