165 research outputs found
Joint Design of surveillance radar and MIMO communication in cluttered environments
In this study, we consider a spectrum sharing architecture, wherein a
multiple-input multiple-output communication system cooperatively coexists with
a surveillance radar. The degrees of freedom for system design are the transmit
powers of both systems, the receive linear filters used for pulse compression
and interference mitigation at the radar receiver, and the space-time
communication codebook. The design criterion is the maximization of the mutual
information between the input and output symbols of the communication system,
subject to constraints aimed at safeguarding the radar performance. Unlike
previous studies, we do not require any time-synchronization between the two
systems, and we guarantee the radar performance on all of the range-azimuth
cells of the patrolled region under signal-dependent (endogenous) and
signal-independent (exogenous) interference. This leads to a non-convex
problem, and an approximate solution is thus introduced using a block
coordinate ascent method. A thorough analysis is provided to show the merits of
the proposed approach and emphasize the inherent tradeoff among the achievable
mutual information, the density of scatterers in the environment, and the
number of protected radar cells.Comment: Submitted to IEEE Transaction on Signal Processing on June 24, 201
A Vector Channel Based Approach to MIMO Radar Waveform Design for Extended Targets
Radar systems have been used for many years for estimating, detecting, classifying, and imaging objects of interest (targets). Stealthier targets and more cluttered environments have created a need for more sophisticated radar systems to gain more precise information about the radar environment. Because modern radar systems are largely defined in software, adaptive radar systems have emerged that tailor system parameters such as the transmitted waveform and receiver filter to the target and environment in order to address this need.
The basic structure of a radar system exhibits many similarities to the structure of a communication system. Recognizing the parallel composition of radar systems and information transmission systems, initial works have begun to explore the application of information theory to radar system design, but a great deal of work still remains to make a full and clear connection between the problems addressed by radar systems and communication systems. Forming a comprehensive definition of this connection between radar systems and information transmission systems and associated problem descriptions could facilitate the cross-discipline transfer of ideas and accelerate the development and improvement of new system design solutions in both fields. In particular, adaptive radar system design is a relatively new field which stands to benefit from the maturity of information theory developed for information transmission if a parallel can be drawn to clearly relate similar radar and communication problems.
No known previous work has yet drawn a clear parallel between the general multiple-input multiple-output (MIMO) radar system model considering both the detection and estimation of multiple extended targets and a similar multiuser vector channel information transmission system model. The goal of this dissertation is to develop a novel vector channel framework to describe a MIMO radar system and to study information theoretic adaptive radar waveform design for detection and estimation of multiple radar targets within this framework.
Specifically, this dissertation first provides a new compact vector channel model for representing a MIMO radar system which illustrates the parallel composition of radar systems and information transmission systems. Second, using the proposed framework this dissertation contributes a compressed sensing based information theoretic approach to waveform design for the detection of multiple extended targets in noiseless and noisy scenarios. Third, this dissertation defines the multiple extended target estimation problem within the framework and proposes a greedy signal to interference-plus-noise ratio (SINR) maximizing procedure based on a similar approach developed for a collaborative multibase wireless communication system to optimally design wave forms in this scenario
QoS-Aware Precoder Optimization for Radar Sensing and Multiuser Communications Under Per-Antenna Power Constraints
In this work, we concentrate on designing the precoder for the multiple-input multiple-output (MIMO) dual functional radar-communication (DFRC) system, where the dual-functional waveform is designed for performing multiuser downlink transmission and radar sensing simultaneously. Specifically, considering the signal-independent interference and signal-dependent clutter, we investigate the optimization of transmit precoding for maximizing the sensing signal-to-interference-plus-noise ratio (SINR) at the radar receiver under the constraint of the minimum SINR received at multiple communication users and per-antenna power budget. The formulated problem is challenging to solve due to the nonconovex objective function and nonconvex per-antenna power constraint. In particular, for the signal-independent interference case, we propose a distance-majorization induced algorithm to approximate the nonconvex problem as a sequence of convex problems whose optima can be obtained in closed form. Subsequently, our complexity analysis shows that our proposed algorithm has a much lower computational complexity than the widely-adopted semidefinite relaxation (SDR)-based algorithm. For the signal-dependent clutter case, we employ the fractional programming to transform the nonconvex problem into a sequence of subproblems, and then we propose a distance-majorization based algorithm to obtain the solution of each subproblem in closed form. Finally, simulation results confirm the performance superiority of our proposed algorithms when compared with the SDR-based approach. In conclusion, the novelty of this work is to propose an efficient algorithm for handling the typical problem in designing the DFRC precoder, which achieves better performance with a much lower complexity than the state-of-the-art algorithm
The University Defence Research Collaboration In Signal Processing
This chapter describes the development of algorithms for automatic detection of anomalies from multi-dimensional, undersampled and incomplete datasets. The challenge in this work is to identify and classify behaviours as normal or abnormal, safe or threatening, from an irregular and often heterogeneous sensor network. Many defence and civilian applications can be modelled as complex networks of interconnected nodes with unknown or uncertain spatio-temporal relations. The behavior of such heterogeneous networks can exhibit dynamic properties, reflecting evolution in both network structure (new nodes appearing and existing nodes disappearing), as well as inter-node relations.
The UDRC work has addressed not only the detection of anomalies, but also the identification of their nature and their statistical characteristics. Normal patterns and changes in behavior have been incorporated to provide an acceptable balance between true positive rate, false positive rate, performance and computational cost. Data quality measures have been used to ensure the models of normality are not corrupted by unreliable and ambiguous data. The context for the activity of each node in complex networks offers an even more efficient anomaly detection mechanism. This has allowed the development of efficient approaches which not only detect anomalies but which also go on to classify their behaviour
Joint bi-static radar and communications designs for intelligent transportation
The cooperation of radar and communications becomes important in vehicular environments due to the demand for radar-assisted communications or communications-assisted radar. In this paper, the tradeoff between bi-static radar and communications in a joint radar-communications setting is studied. We propose three schemes by using time division, superposition or their mixture. For each scheme, three optimization problems are formulated to maximize either the probability of detection for radar subject to a minimum communications rate, the communications rate subject to a minimum probability of detection for radar, or a combined measure of tradeoff. Specifically, given a fixed amount of total time or power for both communications and radar, the optimal power allocation and/or time allocation between radar and communications are derived. Numerical results show that the superposition scheme outperforms the time division scheme and the mixture scheme with considerable performance gains. They also show that the surveillance channel in radar and the communications channel are more important than the direct channel in radar
Co-Designing Statistical MIMO Radar and In-band Full-Duplex Multi-User MIMO Communications
We consider a spectral sharing problem in which a statistical (or widely
distributed) multiple-input-multiple-output (MIMO) radar and an in-band
full-duplex (IBFD) multi-user MIMO (MU-MIMO) communications system concurrently
operate within the same frequency band. Prior works on joint
MIMO-radar-MIMO-communications (MRMC) systems largely focus on either colocated
MIMO radars, half-duplex MIMO communications, single-user scenarios, omit
practical constraints, or MRMC co-existence that employs separate
transmit/receive units. In this paper, we present a co-design framework that
addresses all of these issues. In particular, we jointly design the statistical
MIMO radar codes, uplink (UL)/downlink (DL) precoders of in-band full-duplex
multi-user MIMO communications, and corresponding receive filters using our
proposed metric of compounded-and-weighted sum mutual information. This
formulation includes practical constraints of UL/DL transmit powers, UL/DL
quality-of-service, and peak-to-average-power ratio. We solve the resulting
highly non-convex problem through a combination of block coordinate descent and
alternating projection methods. Extensive numerical experiments show that our
methods achieve monotonic convergence in a few iterations, improve radar target
detection over conventional codes, and yield a higher achievable data rate than
standard precoders.Comment: 20 pages, 8 figures, 1 tabl
Sensor Fusion and Resource Management in MIMO-OFDM Joint Sensing and Communication
This study explores the promising potential of integrating sensing
capabilities into multiple-input multiple-output (MIMO)-orthogonal frequency
division multiplexing (OFDM)-based networks through innovative multi-sensor
fusion techniques, tracking algorithms, and resource management. A novel data
fusion technique is proposed within the MIMO-OFDM system, which promotes
cooperative sensing among monostatic joint sensing and communication (JSC) base
stations by sharing range-angle maps with a central fusion center. To manage
data sharing and control network overhead introduced by cooperation, an
excision filter is introduced at each base station. After data fusion, the
framework employs a three-step clustering procedure combined with a tracking
algorithm to effectively handle point-like and extended targets. Delving into
the sensing/communication trade-off, resources such as transmit power,
frequency, and time are varied, providing valuable insights into their impact
on the overall system performance. Additionally, a sophisticated channel model
is proposed, accounting for complex urban propagation scenarios and addressing
multipath effects and multiple reflection points for extended targets like
vehicles. Evaluation metrics, including optimal sub-pattern assignment (OSPA),
downlink sum rate, and bit rate, offer a comprehensive assessment of the
system's localization and communication capabilities, as well as network
overhead
Human activity signatures captured under different directions using SISO and MIMO radar systems
In this paper, we highlight and resolve the shortcomings of single-input single-output (SISO) millimeter wave (mm-Wave) radar systems for human activity recognition (HAR). A 2 × 2 distributed multiple-input multiple-output (MIMO) radar framework is presented to capture human activity signatures under realistic conditions in indoor environments. We propose to distribute the two pairs of collocated transmitter–receiver antennas in order to illuminate the indoor environment from different perspectives. For the proposed MIMO system, we measure the time-variant (TV) radial velocity distribution and TV mean radial velocity to observe the signatures of human activities. We deploy the Ancortek SDR-KIT 2400T2R4 mm-Wave radar in a SISO as well as a 2 × 2 distributed MIMO configuration. We corroborate the limitations of SISO configurations by recording real human activities in different directions. It is shown that, unlike the SISO radar configuration, the proposed MIMO configuration has the ability to obtain superior human activity signatures for all directions. To signify the importance of the proposed 2 × 2 MIMO radar system, we compared the performance of a SISO radar-based passive step counter with a distributed MIMO radar-based passive step counter. As the proposed 2 × 2 MIMO radar system is able to detect human activity in all directions, it fills a research gap of radio frequency (RF)-based HAR systems.publishedVersio
Robotic Wireless Sensor Networks
In this chapter, we present a literature survey of an emerging, cutting-edge,
and multi-disciplinary field of research at the intersection of Robotics and
Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor
Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system
that aims to achieve certain sensing goals while meeting and maintaining
certain communication performance requirements, through cooperative control,
learning and adaptation. While both of the component areas, i.e., Robotics and
WSN, are very well-known and well-explored, there exist a whole set of new
opportunities and research directions at the intersection of these two fields
which are relatively or even completely unexplored. One such example would be
the use of a set of robotic routers to set up a temporary communication path
between a sender and a receiver that uses the controlled mobility to the
advantage of packet routing. We find that there exist only a limited number of
articles to be directly categorized as RWSN related works whereas there exist a
range of articles in the robotics and the WSN literature that are also relevant
to this new field of research. To connect the dots, we first identify the core
problems and research trends related to RWSN such as connectivity,
localization, routing, and robust flow of information. Next, we classify the
existing research on RWSN as well as the relevant state-of-the-arts from
robotics and WSN community according to the problems and trends identified in
the first step. Lastly, we analyze what is missing in the existing literature,
and identify topics that require more research attention in the future
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