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Latest
News
ACRi
will present three papers at the SPIE Conference on Defense, Security,
and Sensing held from April 5-8 in Orlando, Florida. Those attending
the conference are encouraged to contact Dr. Okamoto if they wish to
schedule meetings during or after the conference. The three papers that
ACRi is presenting are:
High-Power
Interference Suppression Via Reduced Complexity Adaptive
Blind Beamforming Authors:
Garret
Okamoto and Chih-Wei Chen
This
paper evaluates an adaptive beamforming
solution which addresses the significant problem caused by high-power
transmitters located in close proximity to users. Current solutions are
overwhelmed by the rapid increase in number and variety of strong
interference sources. This smart antenna blind beamforming algorithm
requires less computational complexity than standard algorithms, making
it feasible to be added to current and next-generation systems, and
provides a highly adaptive and reliable interference-resistant
communications environment. Simulations show that ACRi’s
high-power interference mitigation solution automatically nulls jamming
signals that are 20 dB to 40 dB stronger than the user signal. The
results show that ACRi’s new beamformer achieves close to the
theoretically best performance obtained by algorithms such as MVDR that
assume the spatial information of the user and interference signals are
known (which may not be feasible when high-power interference is
present and the user is mobile), which is excellent because
ACRi’s algorithm requires significantly less computational
complexity and does not require the spatial information to be known in
advance for the user or the interference signals. Systems with a
limited number of antennas are evaluated because legacy and current
generation systems have as little as two antennas.
Tracking
and Interference Suppression Performance for the Minimal Computational
Complexity Non-Eigen Decomposition Beamformer Authors:
Garret
Okamoto and Chih-Wei Chen
This
paper
evaluates tracking and interference suppression performance for the
ultra low complexity Non-Eigen Decomposition (NED) blind beamforming
algorithm. Current blind beamforming algorithms require too much
computational resources for them to be used by ground and air robotic
systems and other systems with limited available computational power.
This paper focused on the ultra low complexity NED beamforming
algorithm for adaptive interference mitigation. NED does not rely on
the eignenvalues and eigenvectors used by conventional algorithms and
requires significantly less computations, with a total computational
load of O(4M-4) per snapshot for a system with M receiving antennas by
approximating the cross correlation vector of the received signals in
the reference and other antennas. This technique requires neither a
training sequence nor an assumption of incoherency among impinging
signals. By significantly reduces the computational requirements for
beamforming, NED makes it possible for robotics and other systems to
achieve the advantages of beamforming—such as enhanced
reliability, increased range, resistance to co-channel interference
signals, increased throughput and capacity, and extended battery life.
Tracking ability determines what types of applications and scenarios a
technique is applicable for, particularly important in mobile wireless
systems such as the target applications identified for NED (ground
robots, unmanned aerial vehicles, and mobile phone handsets).
Simulation results show that the DOA estimated by NED is almost
identical to the true DOA even when the user moves extremely quickly,
with NED’s fast convergence rate (only 4 iterations needed in
the
highest mobility case) also evident. The high angular movement between
samples corresponds to user speeds ranging from 31 km/h to 124,000 km/h
if the distance between the mobile user and transmitter is 1 km.
Beamforming
Performance for a Reconfigurable Sparse Array Smart Antenna System via
Multi-Mobile Robot Cluster Control Authors:
Garret
Okamoto, Chih-Wei Chen, and Christopher Kitts
This
paper describes and evaluates the beamforming performance for a
flexible sparse array smart antenna system that can be reconfigured
through the use of multiple mobile robots. Current robotic systems are
limited because they cannot utilize beamforming due to their limited
number of antennas and the high computational requirement of
beamformers. The beamforming techniques used in this paper are unique
because unlike current beamformers, the antennas in the sparse array
are not connected together but instead each robot has a single antenna.
This work is made possible through breakthroughs by the authors on
ultralow computational complexity beamforming and multi-mobile robot
cluster control. This new beamforming paradigm provides spatial
reconfigurability of the array to control its location, size,
inter-antenna spacing and geometry via multi-robot collaborative
communications. Simulation results evaluate the effectiveness of
various beamforming techniques when 1, 2, 3, 4, and 8 robots are
utilized. The simulation results are also evaluated for multiple
geometric configurations for the robots, evaluating whether or not
different geometric shapes may provide greater range or interference
mitigation performance for different communications scenarios.
Preliminary over-the-air measurement results are provided via
ACRi’s flexible SDR communications hardware platform that
will be integrated with the individual robotic systems.
September
11, 2009
ACRi
Awarded
a Phase I SBIR Award from the National Science
Foundation
ACRi
has been awarded a Phase I SBIR
contract from the National Science
Foundation for research advancing its “Reconfigurable Sparse
Array Smart Antenna System via Multi-Robot Control”. The
Abstract of this Phase I program is included below. For further
information on this program, including an invitation to the hardware
demonstrations that will be conducted during Phase I, please e-mail
info@adaptivecomms.com and an ACRi representative will promptly respond
to your request.
This
Small Business Innovation Research
(SBIR) Phase I project develops
and evaluates a flexible sparse array smart antenna system that can be
reconfigured through the use of multiple mobile robots. Current robotic
systems are limited because they cannot utilize beamforming due to
their limited number of antennas and the high computational requirement
of beamformers. This pioneering research is made possible through
recent breakthroughs for ultralow computational complexity beamforming
and multi-mobile robot cluster control. Unlike current beamformers, the
antennas in the sparse array will not be physically connected together
but instead each robot will have a single antenna. By developing new
signal processing and robotic control techniques, robotic
communications will be enabled where impossible today due to range,
dead spots, or interference. Over-the-air measurements will make it
possible to finally evaluate how key issues (distance between robots,
geometric shape of the sparse array, etc.) affects system performance.
The
broader
impact/commercial potential of this project is that it can
revolutionize commercial robotic systems and other applications in the
wireless industry. Enabling multi-robot collaborative communications
makes reliable communications possible in worst-case environments.
Performance evaluation of sparse arrays will provide valuable insight
for collaborative communications for other applications such as
distributed sensor networks while the beamformer?s ultralow
computational requirement makes it feasible to be added to current and
future wireless systems. Creation of a new class of robotic
communications will enable robots to be more effective in current
applications and create new markets for the robotic sector. The use of
robots has increased exponentially with robots increasingly relied upon
for defense, law enforcement, and manufacturing, but communication
limitations prevent robots from being effective in many situations.
Preventing this critical loss of communications for robots searching
for people trapped in collapsed buildings or while on scout missions
can save lives and have a great societal impact. This research will
foster new fields of scientific and technological understanding by
enabling Academia and Industry researchers to evaluate the advances
made through this pioneering research, which will enable performance
optimization for smart antenna systems whether the antennas are
physically connected or at different locations.
