21 research outputs found
Joint transmitter selection and resource management strategy based on low probability of intercept optimization for distributed radar networks
In this paper, a joint transmitter selection and resource management (JTSRM) strategy based on low probability of intercept (LPI) is proposed for target tracking in distributed radar network system. The basis of the JTSRM strategy is to utilize the optimization technique to control transmitting resources of radar networks in order to improve the LPI performance, while guaranteeing a specified target tracking accuracy. The weighted intercept probability and transmit power of radar networks is defined and subsequently employed as the optimization criterion for the JTSRM strategy. The resulting optimization problem is to minimize the LPI performance criterion of radar networks by optimizing the revisit interval, dwell time, transmitter selection, and transmit power subject to a desired target tracking performance and some resource constraints. An efficient and fast threeâstep solution technique is also developed to solve this problem. The presented mechanism implements the optimal working parameters based on the feedback information in the tracking recursion cycle in order to improve the LPI performance for radar networks. Numerical simulations are provided to verify the superior performance of the proposed JTSRM strategy
Joint Transmit Resource Management and Waveform Selection Strategy for Target Tracking in Distributed Phased Array Radar Network
In this paper, a joint transmit resource management and waveform selection (JTRMWS) strategy is put forward for target tracking in distributed phased array radar network. We establish the problem of joint transmit resource and waveform optimization as a dual-objective optimization model. The key idea of the proposed JTRMWS scheme is to utilize the optimization technique to collaboratively coordinate the transmit power, dwell time, waveform bandwidth, and pulse length of each radar node in order to improve the target tracking accuracy and low probability of intercept (LPI) performance of distributed phased array radar network, subject to the illumination resource budgets and waveform library limitation. The analytical expressions for the predicted Bayesian Cram\'{e}r-Rao lower bound (BCRLB) and the probability of intercept are calculated and subsequently adopted as the metric functions to evaluate the target tracking accuracy and LPI performance, respectively. It is shown that the JTRMWS problem is a non-linear and non-convex optimization problem, where the above four adaptable parameters are all coupled in the objective functions and constraints. Combined with the particle swarm optimization (PSO) algorithm, an efficient and fast three-stage-based solution technique is developed to deal with the resulting problem. Simulation results are provided to verify the effectiveness and superiority of the proposed JTRMWS algorithm compared with other state-of-the-art benchmarks
A comparison of processing approaches for distributed radar sensing
Radar networks received increasing attention in recent years as they can outperform
single monostatic or bistatic systems. Further attention is being dedicated
to these systems as an application of the MIMO concept, well know
in communications for increasing the capacity of the channel and improving
the overall quality of the connection. However, it is here shown that radar
network can take advantage not only from the angular diversity in observing
the target, but also from a variety of ways of processing the received signals. The
number of devices comprising the network has also been taken into the analysis.
Detection and false alarm are evaluated in noise only and clutter from a theoretical
and simulated point of view. Particular attention is dedicated to the statistics
behind the processing. Experiments have been performed to evaluate practical
applications of the proposed processing approaches and to validate assumptions
made in the theoretical analysis. In particular, the radar network used for
gathering real data is made up of two transmitters and three receivers. More than
two transmitters are well known to generate mutual interference and therefore
require additional e�fforts to mitigate the system self-interference. However,
this allowed studying aspects of multistatic clutter, such as correlation, which
represent a first and novel insight in this topic. Moreover, two approaches for
localizing targets have been developed. Whilst the first is a graphic approach, the
second is hybrid numerical (partially decentralized, partially centralized) which
is clearly shown to improve dramatically the single radar accuracy. Finally the
e�ects of exchanging angular with frequency diversity are shown as well in some
particular cases. This led to develop the Frequency MIMO and the Frequency
Diverse Array, according to the separation of two consecutive frequencies. The
latter is a brand new topic in technical literature, which is attracting the interest
of the technical community because of its potential to generate range-dependant
patterns. Both the latter systems can be used in radar-designing to improve the
agility and the effciency of the radar
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 âon the flyâ, 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
Proceedings of the Fourth MIT/ONR Workshop on Distributed Information and Decision Systems Motivated by Command-Control-Communications (C3) Problems, June 15-June 26, 1981, San Diego, California
"OSP number 85552"--Cover.Library has v. 2 only.Includes bibliographies.Workshop suppported by the Office of Naval Research under contract ONR/N00014-77-C-0532edited by Michael Athans ... [et al.].v.1. Surveillance and target tracking--v.2. Systems architecture and evaluation--v.3. Communication, data bases & decision support--v.4. C3 theory
Radar Technology
In this book âRadar Technologyâ, the chapters are divided into four main topic areas: Topic area 1: âRadar Systemsâ consists of chapters which treat whole radar systems, environment and target functional chain. Topic area 2: âRadar Applicationsâ shows various applications of radar systems, including meteorological radars, ground penetrating radars and glaciology. Topic area 3: âRadar Functional Chain and Signal Processingâ describes several aspects of the radar signal processing. From parameter extraction, target detection over tracking and classification technologies. Topic area 4: âRadar Subsystems and Componentsâ consists of design technology of radar subsystem components like antenna design or waveform design
Proceedings of the 9th MIT/ONR workshop on C3 Systems, held at Naval Postgraduate School and Hilton Inn Resort Hotel, Monterey, California June 2 through June 5, 1986
GRSN 627729"December 1986."Includes bibliographical references and index.Sponsored by Massachusetts Institute of Technology, Laboratory for Information and Decision Systems, Cambridge, Mass., with support from the Office of Naval Research. ONR/N00014-77-C-0532(NR041-519) Sponsored in cooperation with IEEE Control Systems Society, Technical Committee on C.edited by Michael Athans, Alexander H. Levis