Trajectory Design and Power Control for Joint Radar and Communication Enabled Multi-UAV Cooperative Detection Systems

In this article, we consider a distributed joint radar-communication (JRC) multiple-input multiple-output (MIMO) system that performs both radar and communication objectives simultaneously. By introducing radar and communication performance metrics, optimized power allocation is achieved for different transmitters of the JRC system. The objective of the radar subsystem is to achieve a desired target localization accuracy quantified in terms of the Cramer-Rao bound of the location estimates, whereas the objective of the communication subsystem is to improve the classical Shannon capacity. First, we consider non-cooperative radar- and communication-centric operations, and the power allocations are respectively optimized for these cases. Next, we present two novel resource allocation strategies for the cooperative JRC system. In the first strategy, joint resource optimization for radar and communication subsystems is performed by exploiting the same waveform resources, resulting in high spectrum efficiency. The second approach provides enhanced flexibility by exploiting separate sets of waveforms that are respectively dedicated to the radar and communication subsystems, enabling the JRC system to independently change radar subsystem waveforms based only on the radar surveillance profile, without impacting the communication subsystem waveforms. Simulation results clearly demonstrate significant performance gain of the proposed cooperative JRC system over radar- or communication-centric power allocation schemes.

Radar usually employs several signal processing methods successively for detection. Each processing step influences the radar detection performance. Thus, analysis of the radar detection performance considering the complete signal processing flow provides significant reference for radar detector design. In this paper, with the assumption that matched filtering, square-law detection, non-coherent integration, cell averaging constant false alarm rate detection and double-threshold detection are employed sequentially for radar detection, radar detection performance in K distributed sea clutter plus Rayleigh distributed thermal noise is analyzed. Mathematical expressions of radar false alarm probability and detection probability are derived. Radar detection performances for four types of Swerling fluctuating targets in various circumstances are presented by simulation. And comprehensive effect of K distributed sea clutter plus Rayleigh distributed thermal noise on radar detection performance is analyzed.

The radar system designer is constrained by limited budgets for resources such as cost, weight, prime power, and volume. Under these constraints, the designer attempts to maximize the radar system performance. After selecting the operating frequency band and the basic design approach, the primary way to improve radar performance is to increase the average radiated power (P) and the antenna aperture area (A). Search radar performance scales with the power-aperture product PA, track radar performance scales in proportion to PA/sup 2/, and fire control radar performance scales as PA/sup 3/ of PA/sup 4/. After allocating resources to all other sub-systems (e.g. computers and signal processors), the system designer must determine how to balance resource allocation between P and A. This analysis determines the optimal allocation of the critical resource that is exhausted before others. If the resource cost of P and A are linear and independent, the analysis shows that for a search radar the critical resource should be divided equally between P and A. For a track radar, one-third of the critical resource should be allocated to P and two-thirds to A. For a fire control radar, one-fourth or one-fifth of the critical resource should be allocated to P, with the remainder allocated to A. The analysis also provides results to optimally balance P and A in the case where the resource costs are non-linear functions. The appendix reviews the relationship between P, A, and radar performance.

In this paper, we consider a beampattern design problem for a dual-functional radar-communication (DFRC) system with the aid of the reconfigurable intelligent surface (RIS). The goal of the design is to meet the communication requirements of the users while the beampattern can match the ideal beampattern. We formulate the beampattern design as a non- convex optimization problem by jointly optimizing the transmit and passive beamformers. To solve the problem, three methods, namely the semidefinite relaxation (SDR)-based method, penalty- based method, and Riemannian conjugate gradient (RCG)-based method are proposed. The simulation results illustrate that: i) the radar performance can be significantly enhanced with the aid of RIS; ii) a tradeoff should be made between the communication performance and radar performance; iii) 4 control bits are sufficient to make the performance close to that of continuous phase shift.

Digital programmable metasurfaces (DPMs) can dynamically modulate electromagnetic waves in space, time, and frequency domains with powerful capabilities. In contrast, joint radar and communication (JRC) is an important avenue to use the electromagnetic waves universally and intelligently. Hence, combining DPM and JRC may produce a promising way to achieve universal and intelligent electromagnetic terminals. Herein, a mechanism of extremely flexible JRC based on DPM is proposed, in which DPM can improve the flexibility of JRC in processing multidimensional information, and JRC endows DPM with the capabilities of perception, expression, and cognition to promote its intelligent level. Three kinds of functions are explored to interpret the mechanism. First, encryption and decryption of wireless secure communications are realized through DPM; second, range profile imaging is accomplished by using DPM‐based biphase‐coded signals; and third, wireless communication and radar detection are simultaneously presented using DPM. The combination of DPM and JRC greatly decreases the complexity of signal processing and simplifies the architecture of the JRC system, and promotes the intelligent level of DPM.

The traditional probe–pass integration system embeds communication information into a radar waveform, which leads to a high level of waveform autocorrelation sidelobes and a poor false symbol rate at low signal-to-noise ratios. This article proposes a three-dimensional indexed modulation-based design method for probe–pass integration waveforms. This method realises communication information modulation and demodulation by simultaneously indexing orthogonal waveform selection, transmitting pulse PRI changes and carrier frequency changes in three dimensions, and applying compressed perception technology to solve the problems of PRI shortcuts and carrier frequency, resulting in a velocity term in the received waveform that cannot be accumulated by phase reference to realise velocity super-resolution. Finally, the radar detection performance and communication performance are simulated and analysed, and the simulation results reveal that the method proposed in this paper can not only satisfy the radar detection performance requirements but also achieve a lower unsigned rate on the basis of an improved communication rate.

There are more than 19,000 objects in earth orbit as of 2018. These space objects are tracked by the space surveillance network (SSN). We found it necessary of own radar facilities for searching a lost satellite and space debris through an accident on a small satellite of the past. To establish an own radar facility by a civilian agency as a laboratory of a University, issues concerning many costs, a licensed radio band for transmitters, and a fixed installation location arise. We propose that one of the solutions on this issue is a Passive Coherent Location (PCL) radar. The PCL radar is a low cost and compact radar system due to using ‘illuminators of opportunity’ as their source of radar transmission instead of a dedicated transmitter. This paper describes a feasibility study on a PCL radar system for space debris detection. The proposed PCL system consists of Earth-orbiting satellites which are transmitting radio waves and a ground-based receiving system. The receiving system consists of a parabolic antenna with high gain and portable SDR equipment with a wideband frequency range. The cost of this system was estimated at less than $20,000, and the weight was less than 50 kg. The volume of the facility is 0.2 % of that of an existing active radar for space debris detection. As a result of the feasibility simulations, it became clear that this proposed PCL radar has a detection capability of space debris from LEO to GEO. Using the JCSAT-3A system, the detectable size converted into the physical silhouette area was 0.70 m2 at an altitude of 400 km. Using the NOAA-19 system, the detectable size was 0.93 m2 at an altitude of 800 km.

This paper presents PhysioChair which is a novel sensing technique integrated in smart chairs for noninvasive and continuous detection of multiple physiological signatures. A dual-frequency radar system is designed and integrated in the PhysioChair, including a 5.8 GHz single-antenna radar for chest movement detection and a 120 GHz miniaturized radar for pulse detection. The dual-frequency multi-radar sensing system is calibrated to ensure systematic synchronization. Besides the conventional vital signs such as respiration, heartbeat and pulse, this paper proposes techniques and approaches to make it possible for the PhysioChair to estimate additional physiological signatures including heart rate variability (HRV), pulse transit time (PTT), pulse wave velocity (PWV), and blood pressure (BP). Experiments have been launched in an office environment with Photoplethysmography (PPG) and digital sphygmomanometer as reference. The experimental results show a great performance of the proposed PhysioChair in detection of weak physiological signatures. Compared to the ground truth, the estimated physiological signatures such as HRV and BP have mean relative errors below 3%, and 6 out of 7 subjects have an over 90% probability of absolute errors less than 5mmHg. The results reveal the possibility for the PhysioChair to be employed outside the clinic, such as applications in the vast internet-of-things (IoT) and in-home health monitoring.

A communication setup is considered where a single transmitter wishes to convey messages to one or two receivers and simultaneously estimate the states of the receivers through the backscattered signals of the emitted waveform. The scenario at hand is motivated by joint radar and communication, which aims to co-design radar sensing and communication over shared spectrum and hardware. In this paper, we model the communication channel as a simple memoryless channel with independent and identically distributed (i.i.d.) time-varying state sequences and we model the backscattered signals by (strictly causal) generalized feedback. For single-receiver systems of this form, we fully characterize the capacity-distortion tradeoff, defined as the largest rate at which a message can reliably be conveyed to the receiver while simultaneously allowing the transmitter to sense the state sequence with a given allowed distortion. Our results show a tradeoff between the achievable rates and distortions, and that this tradeoff only stems from a common choice of the input distribution (the waveform) but not from other properties of the utilized codes. To better illustrate the capacity-distortion tradeoff, we propose a numerical method to compute the optimal inputs (waveforms) that achieve the desired tradeoff. For two-receiver systems with two states, we characterize the capacity-distortion tradeoff region of physically degraded broadcast channels (BC) as a rather straightforward extension of the single receiver case. Here, a tradeoff not only arises between sensing and communication performances but also between the various rates and the distortions of the different states. Similarly to the single-receiver case, the optimal co-design scheme exploits the generalized feedback signals only for sensing but not for improving communication performance. This is different for general two-receiver BCs, where optimal co-design schemes exploit generalized feedback also to improve capacity. However, as we show, also for BCs the optimal sensing performance only depends on the chosen input distribution (waveform) but not on the code construction used to accomplish the communication task. For general BCs, we provide inner and outer bounds on the capacity-distortion region, as well as a sufficient condition when this capacity-distortion region is equal to the product of the capacity region and the set of achievable distortions, in which case no tradeoff between sensing and communication occurs. A number of illustrative examples demonstrate that the optimal co-design schemes outperform conventional schemes that split the resources between sensing and communication, both for single-receiver and BC systems.

The respiratory and heartbeat signals can accurately reflect the health status of the tester, which is of great clinical significance. Compared with the traditional contact detection method, the non-contact radar detection method does not require the tester to wear any sensor equipment and will not cause any discomfort to the tester. The frequency modulated continuous wave (FMCW) radar has the characteristics of simple structure, high resolution, strong stability, and low transmission power and is used for the detection of respiratory and heartbeat signals. This paper designs a low-power, low-cost respiratory, and heartbeat signal detection system based on FMCW radar. In addition, the variational modal decomposition (VMD) method is used to separate respiration and heartbeat signals to obtain accurate respiration and heartbeat rates. The results show that the radar system for detecting respiratory and heartbeat signals has high detection accuracy.

The paper presents the results of research on a histogram-based approach to numerical analysis of statistical distributions of signals in radar detection systems. The idea of this method consists in the numerical calculation of histogram equivalents of probability density functions or cumulative density functions of signals after each stage of a signal processing path. The considerations are illustrated by simulation examples. Their results are compared to the results of Monte Carlo simulations.

Resource allocation is investigated in MIMO single-relay channels based on half-duplex adaptive amplify-and-for-ward (AF) and adaptive decode-and-forward (DF) with feedback. With the channel state information at the destination, two power allocation and precoding schemes are proposed to achieve the lower capacity bounds with the total transmit power constraints for AF and DF. Simulation results show that adaptive AF and adaptive DF have higher spectrum efficiency than direct transmission in every scenario, especially in the lower SNR regime and for the small number of receive antennas case and the half distance between relay and destination case.

For the next generation of wireless communication network, a heterogeneous network architecture with macro cells, small cells, and relays offers numerous advantages, such as higher spectrum efficiency, better fairness in resource allocation, and energy efficient usage as well as optimal coverage. However, this approach encounters various network management challenges, including interference mitigation techniques. In this paper, we consider a multi-user half-duplex amplify-and-forward-MIMO relay system, where a macro basis station communicates with edge cell users via relays and each node has multiple antennas. In this context, we propose two interference alignment (IA) schemes, for which a hybrid approach of the problem formulation based on zero-forcing (ZF) and minimum-mean-square-error optimization criteria was developed to deal with interferences in perfect and imperfect channel state information (CSI) cases. In the case of perfect CSI, simulation results show that this approach provides a SNR gain of about 4 dB regarding BER performance in comparison to that achieved by the reference approach, where all filters are determined solely based on ZF criterion. Furthermore, the achieved capacity and effective signal-to-interference-plus-noise ratio at each edge node are improved by around 5 dB. Having CSI errors, the system performance is significantly improved using the robust design IA approach by minimizing the expected value of cost functions.

In this paper, we study the trajectory and resource allocation design for downlink energy-efficient secure unmanned aerial vehicle (UAV) communication systems, where an information UAV assisted by a multi-antenna jammer UAV serves multiple ground users in the existence of multiple ground eavesdroppers. The resource allocation strategy and the trajectory of the information UAV, and the jamming policy of the jammer UAV are jointly optimized for maximizing the system energy efficiency. The joint design is formulated as a non-convex optimization problem taking into account the quality of service (QoS) requirement, the security constraint, and the imperfect channel state information (CSI) of the eavesdroppers. The formulated problem is generally intractable. As a compromise approach, the problem is divided into two subproblems which facilitates the design of a low-complexity suboptimal algorithm based on alternating optimization approach. Simulation results illustrate that the proposed algorithm converges within a small number of iterations and demonstrate some interesting insights: (1) the introduction of a jammer UAV facilitates a highly flexible trajectory design of the information UAV which is critical to improving the system energy efficiency; (2) by exploiting the spatial degrees of freedom brought by the multi-antenna jammer UAV, our proposed design can focus the artificial noise on eavesdroppers offering a strong security mean to the system.

Unmanned aerial vehicles (UAVs) have attracted considerable attention, thanks to their high flexibility, on-demand deployment and the freedom in trajectory design. The communication channel quality can be effectively improved by using UAV to build a line-of-sight communication link between the transmitter and the receiver. Furthermore, there is increasing demand for communication security improvement, as the openness of a wireless channel brings serious threat. This paper formulates a secrecy capacity optimization problem of a UAV-enabled relay communication system in the presence of malicious eavesdroppers, in which the secrecy capacity is maximized by jointly optimizing the UAV relay’s location, power allocation, and bandwidth allocation under the communication quality and information causality constraints. A successive convex approximation–alternative iterative optimization (SCA-AIO) algorithm is proposed to solve this highly coupled nonconvex problem. Simulation results demonstrate the superiority of the proposed secrecy transmission strategy with optimal trajectory design and resource allocation compared with the benchmark schemes and reveal the impacts of communication resources on system performance.