2,468 research outputs found
Emergency Response Person Localization and Vital Sign Estimation Using a Semi-Autonomous Robot Mounted SFCW Radar
The large number and scale of natural and man-made disasters have led to an
urgent demand for technologies that enhance the safety and efficiency of search
and rescue teams. Semi-autonomous rescue robots are beneficial, especially when
searching inaccessible terrains, or dangerous environments, such as collapsed
infrastructures. For search and rescue missions in degraded visual conditions
or non-line of sight scenarios, radar-based approaches may contribute to
acquire valuable, and otherwise unavailable information. This article presents
a complete signal processing chain for radar-based multi-person detection,
2D-MUSIC localization and breathing frequency estimation. The proposed method
shows promising results on a challenging emergency response dataset that we
collected using a semi-autonomous robot equipped with a commercially available
through-wall radar system. The dataset is composed of 62 scenarios of various
difficulty levels with up to five persons captured in different postures,
angles and ranges including wooden and stone obstacles that block the radar
line of sight. Ground truth data for reference locations, respiration,
electrocardiogram, and acceleration signals are included. The full emergency
response benchmark data set as well as all codes to reproduce our results, are
publicly available at https://doi.org/10.21227/4bzd-jm32.Comment: Dataset availabe at https://doi.org/10.21227/4bzd-jm32, code
available at https://github.com/schrchr/radar-vitals-estimatio
Cognitive radar network design and applications
PhD ThesisIn recent years, several emerging technologies in modern radar system
design are attracting the attention of radar researchers and practitioners
alike, noteworthy among which are multiple-input multiple-output
(MIMO), ultra wideband (UWB) and joint communication-radar technologies.
This thesis, in particular focuses upon a cognitive approach
to design these modern radars. In the existing literature, these technologies
have been implemented on a traditional platform in which the
transmitter and receiver subsystems are discrete and do not exchange
vital radar scene information. Although such radar architectures benefit
from these mentioned technological advances, their performance remains
sub-optimal due to the lack of exchange of dynamic radar scene
information between the subsystems. Consequently, such systems are
not capable to adapt their operational parameters “on the fly”, which
is in accordance with the dynamic radar environment. This thesis explores
the research gap of evaluating cognitive mechanisms, which could
enable modern radars to adapt their operational parameters like waveform,
power and spectrum by continually learning about the radar scene
through constant interactions with the environment and exchanging this
information between the radar transmitter and receiver. The cognitive
feedback between the receiver and transmitter subsystems is the facilitator
of intelligence for this type of architecture.
In this thesis, the cognitive architecture is fused together with modern
radar systems like MIMO, UWB and joint communication-radar designs
to achieve significant performance improvement in terms of target parameter
extraction. Specifically, in the context of MIMO radar, a novel
cognitive waveform optimization approach has been developed which facilitates
enhanced target signature extraction. In terms of UWB radar
system design, a novel cognitive illumination and target tracking algorithm
for target parameter extraction in indoor scenarios has been developed.
A cognitive system architecture and waveform design algorithm
has been proposed for joint communication-radar systems. This thesis
also explores the development of cognitive dynamic systems that allows
the fusion of cognitive radar and cognitive radio paradigms for optimal
resources allocation in wireless networks. In summary, the thesis provides
a theoretical framework for implementing cognitive mechanisms in
modern radar system design. Through such a novel approach, intelligent
illumination strategies could be devised, which enable the adaptation of
radar operational modes in accordance with the target scene variations
in real time. This leads to the development of radar systems which are
better aware of their surroundings and are able to quickly adapt to the
target scene variations in real time.Newcastle University, Newcastle upon Tyne:
University of Greenwich
Survey of Inter-satellite Communication for Small Satellite Systems: Physical Layer to Network Layer View
Small satellite systems enable whole new class of missions for navigation,
communications, remote sensing and scientific research for both civilian and
military purposes. As individual spacecraft are limited by the size, mass and
power constraints, mass-produced small satellites in large constellations or
clusters could be useful in many science missions such as gravity mapping,
tracking of forest fires, finding water resources, etc. Constellation of
satellites provide improved spatial and temporal resolution of the target.
Small satellite constellations contribute innovative applications by replacing
a single asset with several very capable spacecraft which opens the door to new
applications. With increasing levels of autonomy, there will be a need for
remote communication networks to enable communication between spacecraft. These
space based networks will need to configure and maintain dynamic routes, manage
intermediate nodes, and reconfigure themselves to achieve mission objectives.
Hence, inter-satellite communication is a key aspect when satellites fly in
formation. In this paper, we present the various researches being conducted in
the small satellite community for implementing inter-satellite communications
based on the Open System Interconnection (OSI) model. This paper also reviews
the various design parameters applicable to the first three layers of the OSI
model, i.e., physical, data link and network layer. Based on the survey, we
also present a comprehensive list of design parameters useful for achieving
inter-satellite communications for multiple small satellite missions. Specific
topics include proposed solutions for some of the challenges faced by small
satellite systems, enabling operations using a network of small satellites, and
some examples of small satellite missions involving formation flying aspects.Comment: 51 pages, 21 Figures, 11 Tables, accepted in IEEE Communications
Surveys and Tutorial
Non-Contact Human Motion Sensing Using Radar Techniques
Human motion analysis has recently gained a lot of interest in the research community due to its widespread applications. A full understanding of normal motion from human limb joint trajectory tracking could be essential to develop and establish a scientific basis for correcting any abnormalities. Technology to analyze human motion has significantly advanced in the last few years. However, there is a need to develop a non-invasive, cost effective gait analysis system that can be functional indoors or outdoors 24/7 without hindering the normal daily activities for the subjects being monitored or invading their privacy. Out of the various methods for human gait analysis, radar technique is a non-invasive method, and can be carried out remotely. For one subject monitoring, single tone radars can be utilized for motion capturing of a single target, while ultra-wideband radars can be used for multi-subject tracking. But there are still some challenges that need to be overcome for utilizing radars for motion analysis, such as sophisticated signal processing requirements, sensitivity to noise, and hardware imperfections. The goal of this research is to overcome these challenges and realize a non-contact gait analysis system capable of extracting different organ trajectories (like the torso, hands and legs) from a complex human motion such as walking. The implemented system can be hugely beneficial for applications such as treating patients with joint problems, athlete performance analysis, motion classification, and so on
Adaptive waveform design for cognitive radar
Advances in technology, especially in sensing, robotics, wireless communications, hardware capabilities and the constant need to confront not only the existing but also new and advanced threats are pushing for the need of advanced radar techniques. In this context, Cognitive Radar (CR) is visualized as the next generation multifunctional, smart and adaptive radar that extends its capabilities and responsibilities far beyond the traditional radar. CR incorporates knowledge gained by the interaction with the environment into its operation therefore forming a closed-loop system aiming to enhance the system performance. A very important element of the CR operation is the ability to adaptively design the transmitted waveforms based on the radar objective and the changes in the environment. In this thesis, we present the different aspects involved in the Cognitive Radar concept with deeper focus on the adaptive waveform design of the system aiming to improve the tracking performance. A method of adaptive waveform design within the sensor management problem ensuring that the total transmitted power is reduced compared to the transmission of a fixed waveform is proposed and finally a promising direction towards the multi-sensor resource allocation and waveform design is presented
HoloFed: Environment-Adaptive Positioning via Multi-band Reconfigurable Holographic Surfaces and Federated Learning
Positioning is an essential service for various applications and is expected
to be integrated with existing communication infrastructures in 5G and 6G.
Though current Wi-Fi and cellular base stations (BSs) can be used to support
this integration, the resulting precision is unsatisfactory due to the lack of
precise control of the wireless signals. Recently, BSs adopting reconfigurable
holographic surfaces (RHSs) have been advocated for positioning as RHSs' large
number of antenna elements enable generation of arbitrary and highly-focused
signal beam patterns. However, existing designs face two major challenges: i)
RHSs only have limited operating bandwidth, and ii) the positioning methods
cannot adapt to the diverse environments encountered in practice. To overcome
these challenges, we present HoloFed, a system providing high-precision
environment-adaptive user positioning services by exploiting multi-band(MB)-RHS
and federated learning (FL). For improving the positioning performance, a lower
bound on the error variance is obtained and utilized for guiding MB-RHS's
digital and analog beamforming design. For better adaptability while preserving
privacy, an FL framework is proposed for users to collaboratively train a
position estimator, where we exploit the transfer learning technique to handle
the lack of position labels of the users. Moreover, a scheduling algorithm for
the BS to select which users train the position estimator is designed, jointly
considering the convergence and efficiency of FL. Our simulation results
confirm that HoloFed achieves a 57% lower positioning error variance compared
to a beam-scanning baseline and can effectively adapt to diverse environments
System engineering for radio frequency communication consolidation with parabolic antenna stacking
2020 Fall.Includes bibliographical references.This dissertation implements System Engineering (SE) practices while utilizing Model Based System Engineering (MBSE) methods through software applications for the design and development of a parabolic stacked antenna. Parabolic antenna stacking provides communication system consolidation by having multiple antennas on a single pedestal which reduces the number of U.S. Navy shipboard topside antennas. The dissertation begins with defining early phase system lifecycle processes and the correlation of these early processes to activities performed when the system is being developed. Performing SE practices with the assistance of MBSE, Agile, Lean methodologies and SE / engineering software applications reduces the likelihood of system failure, rework, schedule delays, and cost overruns. Using this approach, antenna system consolidation via parabolic antenna stacking is investigated while applying SE principles and utilizing SE software applications. SE / engineering software such as IBM Rational Software, Innoslate, Antenna Magus, ExtendSim, and CST Microwave Studio were used to perform SE activities denoted in ISO, IEC, and IEEE standards. A method to achieve multi-band capabilities on a single antenna pedestal in order to reduce the amount of U.S. Navy topside antennas is researched. An innovative approach of parabolic antenna stacking is presented to reduce the amount of antennas that take up physical space on shipboard platforms. Process simulation is presented to provide an approach to improve predicting delay times for operational availability measures and to identify process improvements through lean methodologies. Finally, this work concludes with a summary and suggestions for future work
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