The
University of Maryland faculty, Johns Hopkins University,
the University
of Sydney (Australia), and Signal Systems Corporation are part of a $
2.2
million, three-year Defense Advanced
Research
Projects Agency (DARPA) contract for "Intelligent and Noise-Robust
Interfaces for MEMS Acoustic Sensors." The goal of this contract is to
formulate, design, and implement signal processing systems and
technology that
can adapt, control and utilize the noisy MEMS sensor signals.
The project is part of DARPA's Air-Coupled Acoustic
Microsensor Technology
program.
SSC's technology transition efforts for Smart Microphone
technology is
included in our Acoustic Surveillance Unit (ASU)
product. As part of a DoD contractor team, we are using smart
microphone
technology as part of a low power sensor system design.
Project details
Air-coupled
acoustic
MEMS
offer exciting opportunities for a wide range of
applications for robust sound detection, analysis, and recognition in
noisy
environments. The most important advance these sensors offer is the
potential
for fabricating and utilizing miniature, low-power, and intelligent
sensor
elements and arrays. In particular, MEMS make it possible for the first
time to
conceive of applications which employ arrays of interacting
micro-sensors,
creating in effect spatially distributed sensory fields. To achieve
this
potential, however, it is essential that these sensors be coupled to
signal
conditioning and processing circuitry that can tolerate their inherent
noise and
environmental sensitivity without sacrificing the unique advantages of
compactness and efficiency.
The fundamental challenge that we address in this proposal,
one that is
critical to any real application of MEMS sensors, is how to formulate,
design,
and implement signal processing systems and technology that can adapt,
control,
and utilize the noisy MEMS sensor signals.
More specifically, we focus our technology transition efforts
on
developing a smart microphone, suitable for outdoor acoustic
surveillance on
robotic vehicles. This smart microphone incorporated MEMS sensors for
acoustic
sensing, wind noise flow turbulence sensing, platform vibration
sensing, and a
VLSI-based (analog very large scale integration) adaptive
noise-reduction
circuitry.
These intelligent and noise robust interface capabilities
enable a new class
of small, effective air-coupled surveillance sensors. These sensor
interfaces
and noise reduction circuits are be small enough to be mounted on
future robots.
Our interfaces consume less power than current systems. By including
silicon
cochlea based detection and localization processing, these sensors can
perform
end-to-end acoustic surveillance. The resulting smart microphone
technology is
very power efficient, enabling a networked array of autonomous sensors
that can
be air-dropped, integrated onto miniaturized robots, or deployed by
hand.
To achieve these goals, we propose to develop and utilize
novel technologies
that can perform these functions robustly, inexpensively, and at
extremely low
power. An equally important innovation is the formulation of algorithms
that are
intrinsically matched to the characteristic strengths and weaknesses of
the
technology. These theoretical and technological innovations are fully
intertwined in our research program, and we believe that both
approaches must be
developed simultaneously so as to achieve truly functional and
well-integrated
smart sensory systems that exploit the exciting potential of acoustic
MEMS
sensors.
The fundamental innovative thrust of our work focuses on the
development of
biomimetic auditory interfaces and algorithms, and their
implementations an
analog or hybrid analog-digital VLSI circuits.
The
ASU, pictured is housed in a 4.5-inch circular “hockey puck”
enclosure, which is a minimum of 1.5 inches in height.
While small, the individual ASU node has
been designed for high performance, and has demonstrated bearing
accuracies of 5 degrees or less with standard algorithms (on the order
of 1 degree with
specialized algorithms).
Results
This is our Acoustic Surveillance Unit (ASU) , a state
of the art microphone that
is able to pinpoint the location of
vechicles and with
the help of the VAWS
system
locate gunfire. Below is the basic structure for our current ASU
prototype. Smaller, more power
efficient designs are underway.
The diagram below shows the accuracy of our several ASUs
deployed in a recent
field test. The system uses a network of ASUs to locate vehicles and
gunfire.