52 research outputs found
Joint waveform and guidance control optimisation for target rendezvous
The algorithm developed in this paper jointly selects the optimal transmitted waveform and the control input so that a radar sensor on a moving platform with linear dynamics can reach a target by minimising a predefined cost. The cost proposed in this paper accounts for the energy of the transmitted radar signal, the energy of the platform control input and the relative position error between the platform and the target, which is a function of the waveform design and control input. Similarly to the Linear Quadratic Gaussian (LQG) control problem, we demonstrate that the optimal solution satisfies the separation principle between filtering and optimisation and, therefore, the optimum can be found analytically. The performance of the proposed solution is assessed with a set of simulations for a pulsed Doppler radar transmitting linearly frequency modulated chirps. Results show the effectiveness of the proposed approach for optimal waveform design and optimal guidance control
Sensing as a Service in 6G Perceptive Networks: A Unified Framework for ISAC Resource Allocation
In the upcoming next-generation (5G-Advanced and 6G) wireless networks,
sensing as a service will play a more important role than ever before.
Recently, the concept of perceptive network is proposed as a paradigm shift
that provides sensing and communication (S&C) services simultaneously. This
type of technology is typically referred to as Integrated Sensing and
Communications (ISAC). In this paper, we propose the concept of sensing quality
of service (QoS) in terms of diverse applications. Specifically, the
probability of detection, the Cramer-Rao bound (CRB) for parameter estimation
and the posterior CRB for moving target indication are employed to measure the
sensing QoS for detection, localization, and tracking, respectively. Then, we
establish a unified framework for ISAC resource allocation, where the fairness
and the comprehensiveness optimization criteria are considered for the
aforementioned sensing services. The proposed schemes can flexibly allocate the
limited power and bandwidth resources according to both S&C QoSs. Finally, we
study the performance trade-off between S&C services in different resource
allocation schemes by numerical simulations
Collaborative Trajectory Planning and Resource Allocation for Multi-Target Tracking in Airborne Radar Networks under Spectral Coexistence
This paper develops a collaborative trajectory planning and resource allocation (CTPRA) strategy for multi-target tracking (MTT) in a spectral coexistence environment utilizing airborne radar networks. The key mechanism of the proposed strategy is to jointly design the flight trajectory and optimize the radar assignment, transmit power, dwell time, and signal effective bandwidth allocation of multiple airborne radars, aiming to enhance the MTT performance under the constraints of the tolerable threshold of interference energy, platform kinematic limitations, and given illumination resource budgets. The closed-form expression for the Bayesian Cramér–Rao lower bound (BCRLB) under the consideration of spectral coexistence is calculated and adopted as the optimization criterion of the CTPRA strategy. It is shown that the formulated CTPRA problem is a mixed-integer programming, non-linear, non-convex optimization model owing to its highly coupled Boolean and continuous parameters. By incorporating semi-definite programming (SDP), particle swarm optimization (PSO), and the cyclic minimization technique, an iterative four-stage solution methodology is proposed to tackle the formulated optimization problem efficiently. The numerical results validate the effectiveness and the MTT performance improvement of the proposed CTPRA strategy in comparison with other benchmarks
Analysis and Design of Joint Communication and Sensing for Wireless Cellular Networks
Joint communication and sensing (JCAS) has emerged as an important piece of technology that will radically change ordinary wireless communication and radar systems. This research area, which has significantly grown over the last decade, aims to develop integrated systems that can provide both communication and sensing/radar functionalities simultaneously. The convergence of both systems into the same joint platform facilitates a more efficient use of the hardware and spectrum resources, enabling new civilian and professional applications.
This thesis focuses on the integration of JCAS functionalities into mobile cellular networks, such as fifth-generation new radio (5G NR) and sixth generation (6G) communication systems, which are developing toward higher frequency ranges at millimeter-wave (mm-wave) bands, coming with wider bandwidths, and have massive antenna arrays, providing a great framework to develop sensing functionalities. By implementing JCAS, the different nodes of the cellular network, such as the base station and user equipment, can sense and reconstruct their surroundings. However, the JCAS operation yields multiple design challenges that need to be addressed. To this end, this thesis aims to develop novel algorithms in two relevant research areas that comprise self-interference (SI) cancellation and beamforming optimization techniques for JCAS systems.
This work analyzes the potential sensing performance of mobile cellular networks, proposing a joint framework and identifying the main radar processing techniques to support JCAS. The fundamental SI challenge stemming from the simultaneous operation of the transmitter and receiver is investigated, and different JCAS cancellation techniques are proposed. The performance and feasibility of the proposed JCAS system is evaluated through simulation and measurement experiments at different frequency bands and scenarios, identifying mm-wave frequencies as the key enabler for future JCAS systems.
Alternative antenna architectures and beamforming methods for mm-wave JCAS platforms are proposed by considering both communication and sensing requirements. Specifically, this thesis proposes novel beamforming methods that provide multiple beams, supporting efficient beamformed communications while an additional beam senses the environment simultaneously. In addition, the proposed beam-forming algorithms address the SI challenge by implementing an efficient spatial suppression scheme to suppress the direct transmitter–receiver coupling
A Comprehensive Overview on 5G-and-Beyond Networks with UAVs: From Communications to Sensing and Intelligence
Due to the advancements in cellular technologies and the dense deployment of
cellular infrastructure, integrating unmanned aerial vehicles (UAVs) into the
fifth-generation (5G) and beyond cellular networks is a promising solution to
achieve safe UAV operation as well as enabling diversified applications with
mission-specific payload data delivery. In particular, 5G networks need to
support three typical usage scenarios, namely, enhanced mobile broadband
(eMBB), ultra-reliable low-latency communications (URLLC), and massive
machine-type communications (mMTC). On the one hand, UAVs can be leveraged as
cost-effective aerial platforms to provide ground users with enhanced
communication services by exploiting their high cruising altitude and
controllable maneuverability in three-dimensional (3D) space. On the other
hand, providing such communication services simultaneously for both UAV and
ground users poses new challenges due to the need for ubiquitous 3D signal
coverage as well as the strong air-ground network interference. Besides the
requirement of high-performance wireless communications, the ability to support
effective and efficient sensing as well as network intelligence is also
essential for 5G-and-beyond 3D heterogeneous wireless networks with coexisting
aerial and ground users. In this paper, we provide a comprehensive overview of
the latest research efforts on integrating UAVs into cellular networks, with an
emphasis on how to exploit advanced techniques (e.g., intelligent reflecting
surface, short packet transmission, energy harvesting, joint communication and
radar sensing, and edge intelligence) to meet the diversified service
requirements of next-generation wireless systems. Moreover, we highlight
important directions for further investigation in future work.Comment: Accepted by IEEE JSA
Radar Detection, Tracking and Identification for UAV Sense and Avoid Applications
Advances in Unmanned Aerial Vehicle (UAV) technology have enabled wider access for the general public leading to more stringent flight regulations, such as the line of sight restriction, for hobbyists and commercial applications. Improving sensor technology for Sense And Avoid (SAA) systems is currently a major research area in the unmanned vehicle community. This thesis overviews efforts made to advance intelligent algorithms used to detect, track, and identify commercial UAV targets by enabling rapid prototyping of novel radar techniques such as micro-Doppler radar target identification or cognitive radar. To enable empirical radar signal processing evaluations, an S-Band and X-Band frequency modulated, software-defined radar testbed is designed, implemented, and evaluated with field measurements. The final evaluations provide proof of functionality, performance measurements, and limitations of this testbed and future software-defined radars. The testbed is comprised of open-source software and hardware meant to accelerate the development of a reliable, repeatable, and scalable SAA system for the wide range of new and existing UAVs
Physical Layer Security in Integrated Sensing and Communication Systems
The development of integrated sensing and communication (ISAC) systems has been spurred by the growing congestion of the wireless spectrum. The ISAC system detects targets and communicates with downlink cellular users simultaneously. Uniquely for such scenarios, radar targets are regarded as potential eavesdroppers which might surveil the information sent from the base station (BS) to communication users (CUs) via the radar probing signal. To address this issue, we propose security solutions for ISAC systems to prevent confidential information from being intercepted by radar targets.
In this thesis, we firstly present a beamformer design algorithm assisted by artificial noise (AN), which aims to minimize the signal-to-noise ratio (SNR) at the target while ensuring the quality of service (QoS) of legitimate receivers. Furthermore, to reduce the power consumed by AN, we apply the directional modulation (DM) approach to exploit constructive interference (CI). In this case, the optimization problem is designed to maximize the SINR of the target reflected echoes with CI constraints for each CU, while constraining the received symbols at the target in the destructive region.
Apart from the separate functionalities of radar and communication systems above, we investigate sensing-aided physical layer security (PLS), where the ISAC BS first emits an omnidirectional waveform to search for and estimate target directions. Then, we formulate a weighted optimization problem to simultaneously maximize the secrecy rate and minimize the Cram\'er-Rao bound (CRB) with the aid of the AN, designing a beampattern with a wide main beam covering all possible angles of targets. The main beam width of the next iteration depends on the optimal CRB. In this way, the sensing and security functionalities provide mutual benefits, resulting in the improvement of mutual performances with every iteration of the optimization, until convergence.
Overall, numerical results show the effectiveness of the ISAC security designs through the deployment of AN-aided secrecy rate maximization and CI techniques. The sensing-assisted PLS scheme offers a new approach for obtaining channel information of eavesdroppers, which is treated as a limitation of conventional PLS studies. This design gains mutual benefits in both single and multi-target scenarios
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