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Army HLVDT
Workshop |
Human, Light Vehicle and Tunnel Detection Workshop
June 16-17, 2009
Venue: Sheraton Washington North (tentative)
Important Dates
Paper Submission: June 1, 2009 Registration: Closed
Contacts
Mr. Nino Srour
(301) 394-2623
nsrour@arl.army.mil
Dr. Jim Sabatier
(662) 915-5404
sabatier@olemiss.edu
Dr. Raju Damarla
(301) 394-1266
rdamarla@arl.army.mil
Sheraton Washington North
Website Link
Please submit abstrats and titles to emthrash@olemiss.edu. The deadline for papers is June 1, 2008.
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The Army Research Laboratory (ARL) and the National Center for Physical
Acoustics (NCPA) at the University of Mississippi, in association with the
Research and Development Branch of the Israel Military of Defense (MAFAT) invite
you to participate in an unclassified study group workshop that will focus on
human, light vehicle and tunnel detection using acoustic, seismic, and
electro-magnetic sensors.
The goal of this workshop and study group is to gather experts from
government, academic and industry working on these topics and share the
knowledge in a closed forum. Another goal is to discuss and determine the
limitations of existing approaches and areas to be explored to make progress in
a timely fashion. Detailed goals are attached in the following pages. You are
invited to submit your papers depicting the state of the art approach in
personnel, light vehicle or tunnel detection. |
Human, Light Vehicle and Tunnel Study Group
The Army Research Laboratory and the
National Center for Physical Acoustics , in association with the Research and
Development Branch of the Israel Military of Defense are hosting an unclassified
study group workshop during June 16-17, 2009 that will focus on human, light
vehicle and tunnel detection using acoustic, seismic and magnetic and electric
field sensors. The workshop’s target audience is university and government
scientists and engineers with expertise in sensor phenomenology, signal
processing, detection and network information processing.
The goal of the HLVTD study group is to collaboratively develop tools that
allow networked multimodal sensor systems that take advantage of available
sensor information such as signal features, human schedules, weather and other
human intelligence to improve situational awareness for the soldier. The study
group will publish proceedings from the papers presented at these meetings. This
inaugural workshop on HLVTD specifically aims at understanding the physics to
enable detection of humans, light vehicles and tunnels via physics-based signal
processing approaches. ctivity
are of primary interest. Environmental influences on the sensor and the wave
propagation medium that impact sensor performance is of interest. Some such
influences are background noise, weather, ground topology and vegetation. The
use of human intelligence in aiding Intelligence, Surveillance and
Reconnaissance (ISR) will be explored as a part of soft and hard fusion
paradigm.
Much work has been done to detect and classify heavy military vehicles
that radiate loud signatures. However, that work may not always be applicable
because the signatures for humans, light vehicles, and tunnels are usually weak
and hidden beneath the sensor noise. Therefore, novel physics-based approaches
are paramount in order to extract the signatures out of the noise. Some
description of the phenomenology of the signatures created by the human, light
vehicle, and tunnels are briefly described below.
1. The human body is a
multi-degree of freedom harmonic oscillator resulting from coupled appendages,
including the head, torso, arms and legs. The movement of a human across the
ground and the oscillatory motions of the body appendages provide characteristic
human signatures. The ground is cyclically loaded from footsteps and
accelerometers and geophones have been used to sense seismic energy from this
periodic loading. The motion of arms, legs and other body components are low
frequency harmonic vibrations that have been sensed with Doppler radar and
sonar. Footstep induced electrostatic charge transfer to produce oscillatory
signals that have been sensed with electric field sensors. Ferromagnetic
materials such as weapons, when carried by humans produce oscillatory fields
that are sensed with magnetic field sensors. Additional human signatures result
from voice composed of formants. Formants are the distinguishing or meaningful
frequency components of human speech. Most human activity yields oscillatory
signatures that can be understood from the nature of the human biomechanical
structure and sensed with a wide spectrum of multi-modal sensors.
2. Light
ground-based vehicles, small cars and trucks, produce signatures much like
humans. Airborne and ground borne vibrations emanate from vehicles. Acoustic and
electromagnetic energy from vehicle power train components and secondarily
coupled body panel, frame and suspension signatures are generally harmonic in
nature. Vehicle tire/ground induced energy may be periodic and broadband. Just
as with human motion, the harmonic content of vehicle source signatures in
addition to signatures that propagate through the air or ground can be sensed
with a wide spectrum of sensors. Unlike the military vehicles, civilian vehicles
are relatively quite and produce signals that are difficult to distinguish.
Special signal processing techniques that are based on physics based
phenomenology are needed. This group would study the phenomenology to extract a
rich feature set from all sensor modalities. It will also address the joint
probability distributions of multimodal sensors to improve detection and
classification.
3. Tunnels can be detected by both passive and active means
using both contact and non contact sensors. Sensing modalities can include the
sensors used in human motion and light vehicle detection. For example, arrays of
vibration sensors with mechanical exciters are often used for shallow
tomographic imaging; other techniques including synthetic aperture principles
are of interest. Similarly, vibration sensor arrays can be used to passively
beam form tunneling sound signatures. Many tunnel sounds have unique frequency
characteristics. For example, the resonance of sound in a tunnel may be
exploited to detected tunnels by using the right frequency. Physics based
understanding of the tunnel sound and vibration phenomenology exhibited by
tunnels and tunnel activity will be studied in all sensor modalities. The
characteristics of magnetic and E-fields generated due to the electric lines in
the tunnels may lead to better feature set that may be observable using sensors
on ground and aerial sensors. Finally, alternative sensing modalities such as
microgravity sensors can respond to minute changes in the gravitational force
due to cavities under the ground.
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