Search

The sharing waveform based integrated radar and communication (IRC) has great potential to apply in Internet of Things (IoT) devices due to its equipment miniaturizing and high efficiency of spectrum and energy, etc. However, the sharing waveform scheme demands a trade-off between radar and communication performances. In this paper, we focus on the design of multiple phase shift keying (MPSK) based linear frequency modulation (LFM) sharing waveform by exploring the trade-off among energy leakage, peak-to-side lobe ratio (PSLR) and symbol rate. First, we derive the energy leakage and PSLR with respect to the symbol rate. Next, a novel LFM-MPSK waveform design is carried out by formulating a communication frame based optimization, where the symbol rate is maximized with the constraints of the energy leakage and PSLR. Then, a branch and reduce algorithm is proposed to solve the optimization. Compared with the conventional one, the proposed LFM-MPSK waveform has a higher symbol rate with the same energy leakage and PSLR. Besides, the proposed waveform design alleviates the difficulty of the trade-off among the energy leakage, PSLR and symbol rate due to more Pareto solutions. Finally, all the analytical results are validated by simulations.

The advantages of optical fiber as a transmission medium for microwave signals have led to an increasing interest in implementing RF photonic links in radar frontends. Many critical radar applications, such as those found in modern military systems, often require a large spur-free dynamic range (SFDR) that is beyond the reach of conventional intensity modulated-direct detection (IM-DD) fiber-optic links. For a solution, we propose a coherent amplitude-modulated link with optical down-conversion that can achieve high dynamic range by employing a receiver with balanced detection and digital linearization. The link is presented along with experimental validation. The measurements show notable dynamic range enhancements over prior arts in down-conversion RF photonic links.

Robust channel estimation in time-varying channels is used to guarantee the quality of communication services, especially for Vehicle-to-Everything (V2X) scenarios. To improve the channel estimation accuracy and reduce the pilot overhead, multi-input multi-output (MIMO) radar is deployed to assist millimeter wave (mmWave) channel estimation. In this paper, we propose a MIMO radar aided channel estimation scheme using deep learning (DL) for the uplink mmWave multiuser (MU)-MIMO communications. To allocate pilot resources reasonably, we design a transmission frame structure of joint radar module and communication module, which divides the estimation scheme into two stages, i.e., the arrival/departure (AoA/AoDs) estimation stage and the gain estimation stage. In view of the imperfections of array elements in practice, we propose an AoA/AoDs estimation algorithm based on subspace reconstruction in the AoA/AoDs estimation stage named two-step angle estimation (TSAE) algorithm. In the gain estimation stage, a DL based channel gain estimator is designed. An autoencoder combined with residual structure named residual denoising autoencoder (RDAE) is proposed to eliminate the noise on wireless signals, which is passed into the least square (LS) estimation module to obtain gains. Simulation results demonstrate that the MIMO radar aided and DL-based channel estimator provides the efficient estimation performance of the high-mobility mmWave channel with fewer training resources.

This work presents a cross correlation-based true-speed-over-ground estimation approach based on experiences from an earlier system. The radar system parameters as well as the antenna configuration were adapted to fit the requirements of the presented application. Also, challenges regarding the previously limited velocity range are addressed and an appropriate solution is proposed. The entire system was thoroughly tested in a train scenario over a wide range of velocities. Very promising measurement results are presented and compared to related approaches.

Wireless communications and sensing at terahertz (THz) band are increasingly investigated as promising short-range technologies because of the availability of high operational bandwidth at THz. In order to address the extremely high attenuation at THz, ultra-massive multiple-input multiple-output (MIMO) antenna systems have been proposed for THz communications to compensate propagation losses. However, the cost and power associated with fully digital beamformers of these huge antenna arrays are prohibitive. In this paper, we develop wideband hybrid beamformers based on both model-based and model-free techniques for a new group-of-subarrays (GoSA) ultra-massive MIMO structure in low-THz band. Further, driven by the recent developments to save the spectrum, we propose beamformers for a joint ultra-massive MIMO radar-communications system, wherein the base station serves multi-antenna user equipment (RX), and tracks radar targets by generating multiple beams toward both RX and the targets. We formulate the GoSA beamformer design as an optimization problem to provide a trade-off between the unconstrained communications beamformers and the desired radar beamformers. To mitigate the beam split effect at THz band arising from frequency-independent analog beamformers, we propose a phase correction technique to align the beams of multiple subcarriers toward a single physical direction. To further decrease the ultra-massive MIMO computational complexity and enhance robustness, we also implement deep learning solutions to the proposed model-based hybrid beamformers. Numerical experiments demonstrate that both techniques outperform the conventional approaches in terms of spectral efficiency and radar beampatterns, as well as exhibiting less hardware cost and computation time., 17pages14figures. Accepted in IEEE Journal of Selected Topics in Signal Processing

Multiple-input multiple-output (MIMO) has been used in wireless communications to increase data rates via multiplexing or improve performance via diversity. Additionally, in radar systems, MIMO promises improved parameter identifiability and target resolution. Frequency diverse (FD)-MIMO radar can effectively distinguish targets that are closely spaced in the same angle cell by exploiting its range-angle-dependent transmit beamform. Therefore, in this paper, we first propose an integrated waveform design by embedding weighted, phase-modulated communication signals in the FD-MIMO radar waveform. Then, we derive the Cramer-Rao lower bound (CRLB) of the location estimation and analyze the communication performance achieved when the communication receiver extracts information from the integrated signals. Next, transmit beamforming is optimized to achieve the best tradeoff between the radar and communication performances of the system. Due to the nonconvexity of the optimization problem, we apply sequential parametric convex approximation (SPCA) and semidefinite relaxation (SDR) methods to solve the problem. The simulation results reveal the effects of some parameters, such as the frequency interval, symbol period, and communication symbol sequence, on radar and communication performance and demonstrate the tradeoff between radar and communication obtained by optimizing the transmit beamforming vector.

Microwave photonic (MWP) radar has the advantages of generating and processing wide bandwidth microwave signals, reconfigurability, high immunity to electromagnetic interference compared to microwave electronic radar. It has the potential to be used in applications such as intelligent autonomous and cyber-physical systems. Recent advances in microwave photonic technology led to the generation, fast processing, and control of broadband signals. Because of the advancements in photonic technologies, next-generation microwave photonic radar is becoming more prominent. This article reviews the most recent advancements and future directions in MWP radars. This review article overviews the different components of microwave photonic radar, different design challenges, and issues pertaining to it. We present a comparative study of different MWP radars on different applications. It also discusses possible future research directions of MWP radar.

The detection and tracking performance of passive radar systems can be enhanced by exploiting multiple emitters and one receiver site by allowing for multiple bistatic geometries. This article investigates the measurement accuracy of passive radar systems that employ the advanced television system committee (ATSC 1.0) signal as a signal of opportunity. The monostatic and bistatic modified Cramer–Rao lower bound for the range and velocity measurements are derived as a quantitative way to evaluate the performance variation when exploiting multiple transmitters. The effect of 3D target position on the signal-to-noise ratio, with respect to stationary transmitters and receiver, is highlighted. Furthermore, signal-to-interference-and-noise ratio modeling is included by considering the direct signal interference suppression performance for a set of transmitters. An example in Columbus, Ohio, for a single receiver and multiple digital television transmitters that are spatially distributed is presented to find the optimal emitter that yields the best range and velocity measurement in the analyzed area. Target-tracking experiments show an agreement between the optimal emitter map and the tracking quality for the set of transmitters.

Accurate and stable time and frequency transfer (TFT) is typically required in distributed sensing. While this has historically been a limiting factor in the design of netted radars, the rise of modern TFT techniques has paved the way to nanosecond level time accuracy, absolute phase synchronization, and sub-Hertz frequency accuracy. In particular, netted systems composed of mobile nodes have benefited immensely from TFT based on global navigation satellite systems (GNSS). However, GNSS systems are liable to denial of service interruption. This article demonstrates the use of a fiber-optic White Rabbit (WR) network in an operational multistatic radar—NeXtRAD, and directly compares the results to one-way multichannel GPS disciplined oscillators acting under common-view TFT.

Photonics-based radar technologies can implement better performance in some main functionalities of the radar systems. The outstanding question is whether these technologies are suitable for the practical application of modern or future radars. Here, we comprehensively analyze key radar parameters and summarize the requirements for the practical applications. Then, we present the corresponding photonics-based technologies capable of meeting actual radar needs. From the aspect of radar signal requirements, we compare the typical microwave photonic technologies for the radar signal generation at this stage and guide the improvement direction. The paper reviews the photonics-based radar signal generation based on a phase-locked dual-comb in detail. Further, the innovative and scalable capabilities of the scheme are presented, including the multi-band radar signal generation for multiple functions radar, and high accuracy beamforming for advanced active phased array radar. The enhanced performances include more flexible carrier frequency, large modulation bandwidth, tunable pulse duration, configurable pulse repetition frequency, full coherence, and continuous phase shift with ultra-high accuracy. The proposed novel photonics-based technology will greatly push forward the application of microwave photonics technologies in actual radar systems.

The increasing bandwidth requirement of new wireless applications has lead to standardization of the millimeter wave spectrum for high-speed wireless communication. The millimeter wave spectrum is part of 5G and covers frequencies between 30 and 300 GHz corresponding to wavelengths ranging from 10 to 1 mm. Although millimeter wave is often considered as a communication medium, it has also proved to be an excellent 'sensor', thanks to its narrow beams, operation across a wide bandwidth, and interaction with atmospheric constituents. In this paper, which is to the best of our knowledge the first review that completely covers millimeter wave sensing application pipelines, we provide a comprehensive overview and analysis of different basic application pipeline building blocks, including hardware, algorithms, analytical models, and model evaluation techniques. The review also provides a taxonomy that highlights different millimeter wave sensing application domains. By performing a thorough analysis, complying with the systematic literature review methodology and reviewing 165 papers, we not only extend previous investigations focused only on communication aspects of the millimeter wave technology and using millimeter wave technology for active imaging, but also highlight scientific and technological challenges and trends, and provide a future perspective for applications of millimeter wave as a sensing technology., 36 pages, submitted to IEEE Sensors Journal

Unified waveform design for automotive joint radar-communications (JRC) leverages the scarce spectrum efficiently and has become a key topic for investigation of late. Designing such a waveform necessitates meeting the requirements of both systems, thereby making it a challenging task. The contribution of this paper is to formulate the JRC design problem into an optimization problem and propose an algorithm to maximize the signal-to-clutter-plus-noise-ratio (SCNR) of radar system and signal-to-noise-ratio (SNR) at communicating vehicle, simultaneously. Central to this are the exploitation of the communication link to acquire environment/ channel information and enhance radar tasks, flexibility to impart trade-off between the two systems during design as well the formulation of the optimization problem to include sidelobe constraints and yield solutions robust to Doppler shifts. The designed waveforms exhibit enhanced radar performance in terms of probability of detection and communication performance in terms of bit error rate (BER), while taking into account the trade-off between two systems. The numerical simulations corroborate the claim of optimized performance with environment/ channel information, ease of effecting trade-off and the use of design flexibility.

Fast Fourier transform (FFT) is one of the fundamental signal processing algorithms widely used in radar applications. The Radon–Fourier transform (RFT) can be seen as an FFT generalization that can overcome some of its limitations. This work derives three spectral RFT (SRFT) based approaches to address major challenges of the multiple-input multiple-output automotive radars. First, two SRFT-based approaches are derived to increase maximal target detection range by mitigation of target migration in range and direction of arrival, jointly, and by multidwell integration processing, which increases the radar coherent integration time without compromising its detection update rate. Next, SRFT-based approach is proposed to address the cluster-to-track association problem that arises in multiple distributed target tracking scenarios that characterize automotive radar operation in dense urban environments.

In-band full duplex (IBFD) radio represents one of the key technologies for future wireless communication and radar applications. A major challenge of this technology is to mitigate the strong self-interfer-ence (SI) so that the residual SI level falls below the receiver's noise floor. Radio frequency (RF) self-inter-ference cancellation (SIC) is essential for preventing an IBFD receiver from becoming saturated by the SI. We commence with an in-depth review of the promising analog least mean square (ALMS) adaptive filtering architecture, conceived for RF SIC in the IBFD radio RF front-end. The cancellation circuits employing this architecture can be implemented purely by analog components without any involvement of more power-thirsty digital signal processing. The behaviors, performance, and implementation of the ALMS loop are presented. Finally, their applications in various IBFD radios are discussed, and future research directions are provided.

An adaptive ranging technique for maintaining high-accuracy ranging between nodes in coherent distributed antenna arrays is presented. Coherent distributed antenna arrays are networks of wireless systems coordinated coherently at the level of the wavelength of the wireless signal. Enabling coherent operation between separate mobile nodes for active and passive microwave remote sensing requires accurate knowledge of the relative positions of the nodes in the array. In this article, a novel adaptive ranging technique based on the near-optimal waveform for high-accuracy ranging, a two-tone waveform, is designed and demonstrated in software-defined radio platforms representing array nodes. Ranging accuracy is dependent on both signal-to-noise ratio and the separation of the two tones in the waveform; however, in realistic environments, factors such as attenuation or antenna misalignment are not easily predicted, which can lead to degradation of the ranging measurement. Selecting one appropriate waveform for range measurements is, thus, not feasible unless the bandwidth assigned to it is always higher than required for the needed range accuracy. Rather than allocating such an unnecessarily wide bandwidth, this article presents a controller that regulates the spectral resources adaptively to meet the desired reference accuracy while minimizing the total occupied bandwidth. The controller continuously monitors the statistical parameters of the received signal, such as signal-to-noise ratio, in a perception stage and adapts the spectral characteristics of the transmitted waveform in an action stage. The adaptive action, based on a Cramer–Rao lower bound analysis, maintains the signal statistical characteristics below a specified bound to maintain high coherent gain. Experimental results demonstrate the ability to maintain ranging standard deviation of 1.5 mm (standard deviation of time delay estimates equals $10^{-11}$ s), which yields 90% or more of the possible achievable coherent gain at carrier frequencies up to 13.33 GHz.

Interference avoidance will be an essential feature of wireless communication systems in the future. Interference avoidance to narrowband users is particularly difficult with Orthogonal Frequency Division Multiplexing (OFDM) due to the side lobes of the subcarriers. Spectrum-nulling algorithms based on cancellation signals have been studied in the literature. In this letter, we describe a general technique to design spectrum nulls for arbitrary signal and canceler bases. Appropriately chosen nonorthogonal canceler bases can result in data rate- and energy-efficient design of spectrum nulls. We also describe an iterative algorithm to cancel the resulting inter-carrier interference at the receiver. Spectrum nulls that meet requirements for avoiding interference to weather radars in the 5 GHz band can be designed using this technique. Bit error rates have been evaluated using simulations.

We compute the minimum cost for an optimal quantum radar, and we compare it with the cost of actual real world classical radars as a function of range. Our calculations show that the minimum cost quantum radar at X-band is many orders of magnitude more expensive than the corresponding classical radar, even assuming the most optimistic wideband-phased array radar architecture. We also assume that the quantum radar is optimal; that is, the effective signal-to-noise ratio is 6 dB better than for a classical radar with the same transmit power and bandwidth at low photon flux per mode. Finally, we discuss many practical issues and potential solutions.

Spectrum sharing of wireless vehicle-to-vehicle (V2V) communication and automotive radar in intelligent transportation systems (ITS) can provide higher spectrum utilization efficiency. However, spectrum sharing between two systems might bring severe interference, which needs to be well solved. To address the communication-radar spectrum sharing (CRSS) and inter-system interference issue, we first model the radar interference estimation as an off-grid compressed sensing problem. Then, we propose an interference cancellation algorithm based on the atomic norm (AN) minimization theory. Simulation results show that the proposed algorithm facilitates the coexistence between radar and communication and improves the V2V communication performance efficiently in the presence of automotive radar interference.

As the only method for all-weather, all-time and long-distance target detection and recognition, radar has been intensively studied since it was invented, and is considered as an essential sensor for future intelligent society. In the past few decades, great efforts were devoted to improving radar's functionality, precision, and response time, of which the key is to generate, control and process a wideband signal with high speed. Thanks to the broad bandwidth, flat response, low loss transmission, multidimensional multiplexing, ultrafast analog signal processing and electromagnetic interference immunity provided by modern photonics, implementation of the radar in the optical domain can achieve better performance in terms of resolution, coverage, and speed which would be difficult (if not impossible) to implement using traditional, even state-of-the-art electronics. In this tutorial, we overview the distinct features of microwave photonics and some key microwave photonic technologies that are currently known to be attractive for radars. System architectures and their performance that may interest the radar society are emphasized. Emerging technologies in this area and possible future research directions are discussed.

This article presents a design for implementing an ultrawideband (UWB) software-defined radar (SDRadar) using a bandwidth reconstruction technique, called frequency stacking, for a stepped frequency signal to create a synthetic wideband waveform (SWW). Practical methods of overcoming traditional limitations of SDRadar and stepped chirp radar are introduced, and the performance is demonstrated using a commercial battery-powered universal software radio peripheral (USRP) software-defined radio (SDR). Application-specific considerations are made and performance tradeoffs are demonstrated. Furthermore, the method is shown to be the coherence solution for otherwise noncoherent low-cost communications’ SDR systems. The proposed design has multiple applications in low-cost, reconfigurable ground-penetrating radar (GPR) and small unmanned aerial vehicle (UAV) synthetic aperture radar (SAR) platforms.

In recent years, software defined radio and digital signal processing have been widely used in communication and radar. As a result, the hardware and RF front-end for radar and wireless communication tends to be similar. Thus, using the same RF and hardware platform for joint radar-communication becomes viable. Joint radar-communication would bring more efficient plan and usage for the radio spectral resource. Furthermore, it could enable new applications that require information exchange and precise localization at the same time. In this paper, cyclic prefixed single carrier (CP-SC) and its variations are chosen as the waveforms for joint radar-communication. CP-SC waveform and its variations are popular in wireless communication and have been chosen by a few standards like IEEE 802.11ad and LTE-advanced. Efficient algorithms are proposed to use such waveforms for range and speed detection/estimation of targets. The proposed algorithms are derived from the maximum likelihood (ML) principle and have low computational complexity. Simulations show that the estimation performance of the proposed method is almost the same as that of ML and is much better than that of the channel estimation based method.

A unified data communication and radar sensing system towards millimeter-wave (mm-wave) applications with extended coverage is proposed and experimentally demonstrated. In the unified system, the transmission and reception of mm-wave signals are implemented by microwave photonics technologies, and the orthogonal frequency division multiplexing (OFDM) signal is employed for communications and radar sensing simultaneously. The superheterodyne optical carrier suppression (HeteroOCS) is used to up-convert the intermediate frequency (IF) OFDM signal to the mm-wave band in the central office (CO). The optical mm-wave signal is transmitted to the remote antenna units (RAUs) via optical fibers. The echo signal is received by the RAU which is remotely connected to the CO by an analog photonic link based on a polarization modulator (PolM). In the transmitter and receiver links, the chromatic dispersion of optical fibers is overcome by the HeteroOCS and the PolM, respectively. The baseband units (BBU) centralized in the CO is used to process the radar sensing signal. A pre-delayed trigger signal is proposed to overcome the fiber length limitation. A proof-of-concept experiment is performed. Two targets with distances of 1.64 m and 3.40 m are successfully detected separately. The communication function of the system is also verified. 1 m wireless transmission of 1.56 Gb/s data rate is achieved below the forward error correction limit.

The effect of the radar skin return from the platform on which a cross-eye jammer is mounted is significant in many practical cross-eye jamming scenarios. However, all published analyses of skin-return affected cross-eye jamming have significant limitations. These limitations are addressed by deriving equations for the distribution of the cross-eye gain in the presence of skin return. The values of these results are demonstrated by using them to gain insight into how skin return affects cross-eye jamming.

In this paper, we investigate the hybrid beamforming problem in joint radar-communications at terahertz (THz) bands. In order to address the extremely high attenuation at THz, ultra-massive multiple-input multiple-output (UM-MIMO) antenna systems have been proposed for THz communications to compensate propagation losses. Further, we propose a new group-of-subarrays (GoSA) UM-MIMO structure to reduce the hardware cost. We formulate the GoSA beamformer design as an optimization problem to provide a trade-off between the unconstrained communications beamformers and the desired radar beamformers. Numerical experiments demonstrate that the proposed approach outperforms the conventional approaches in terms of spectral efficiency and hardware costs.

Special attention has been devoted to joint wireless communication and radar sensing systems in recent years. However, since communication and radar have conflict requirements in terms of waveforms, transceiver developments, and signal processing algorithms, realization of this system concept is still a great challenge. In this paper, we introduce an airborne multi-input multi-output (MIMO) radar, along with the modified orthogonal frequency-division multiplexing (OFDM) and space–time coding (STC) waveform schemes, for the implementation of the joint wireless communication and synthetic aperture radar (SAR) imaging. The proposed system, which simultaneously transmits multidimensional waveforms with reconfigurable channels, can acquire adequate degrees of freedom. Thereby, it becomes a feasible method to perform both data transmission and high-resolution SAR imaging at the same time without intramodal interference. Theoretical analysis is validated by laboratory and flight experiments. Through our analysis, we aim to open up a new perspective of using MIMO radar to realize joint wireless communication and SAR imaging.

Increased amounts of bandwidth are required to guarantee both high-quality/high-rate wireless services (4G and 5G) and reliable sensing capabilities, such as for automotive radar, air traffic control, earth geophysical monitoring, and security applications. Therefore, coexistence between radar and communication systems using overlapping bandwidths has come to be a primary investigation field in recent years. Various signal processing techniques, such as interference mitigation, precoding or spatial separation, and waveform design, allow both radar and communications to share the spectrum. This article reviews recent work on coexistence between radar and communication systems, including signal models, waveform design, and signal processing techniques. Our goal is to survey contributions in this area to provide a primary starting point for new researchers interested in these problems.

The ongoing automation of driving functions in cars results in the evolution of advanced driver assistance systems (ADAS) into ones capable of highly automated driving, which will in turn progress into fully autonomous, self-driving cars. To work properly, these functions first must be able to perceive the car's surroundings by such means as radar, lidar, camera, and ultrasound sensors. As the complexity of such systems increases along with the level of automation, the demands on environment sensors, including radar, grow as well. For radar performance to meet the requirements of self-driving cars, straightforward scaling of the radar parameters is not sufficient. To refine radar capabilities to meet more stringent requirements, fundamentally different approaches may be required, including the use of more sophisticated signal processing algorithms as well as alternative radar waveforms and modulation schemes. In addition, since radar is an active sensor (i.e., it operates by transmitting signals and evaluating their reflections) interference becomes a crucial issue as the number of automotive radar sensors increases. This article gives an overview of the challenges that arise for automotive radar from its development as a sensor for ADAS to a core component of self-driving cars. It summarizes the relevant research and discusses the following topics related to highperformance automotive radar systems: 1) shortcomings of the classical signal processing algorithms due to underlying fundamental assumptions and a signal processing framework that overcomes these limitations, 2) use of digital modulations for automotive radar, and 3) interference-mitigation methods that enable multiple radar sensors to coexist in conditions of increasing market penetration. The overview presented in this article shows that new paradigms arise as automotive radar transitions into a more powerful vehicular sensor, which provides a fertile research ground for further investigation.

In this article, we introduce a novel planar chipless radiofrequency identification (RFID) tag. The tag is composed of multiple miniaturized reflecting resonators based on a slowwave structure. To validate the proposed approach, a tag with a coding capacity of 16 b was designed with a compact size of 15 t 21mm2. Tags with different pattern configurations were fabricated using a Rogers RO4003 substrate, and their radar cross-section (RCS) responses were measured. Compared to conventional multiresonator tags, the proposed tag offers a good miniaturization ratio and spectral coding efficiency. In addition, the measurements revealed a high quality factor (Q-factor) and coding robustness, which demonstrates the efficiency of the used approach to develop high-performance chipless tags.

With an incredible increase in the number of wireless devices and an ever-growing demand for high data rates, 5G needs to provide a solution to satisfy the demand for the next decade. Multiple-input multiple-output (MIMO) systems are seen as one of the primary solutions—allowing for spatial multiplexing and the use of millimeter-wave (mmWave) frequencies, which can provide much larger bandwidths and, thus, data rates. MIMO is very closely related to phased arrays, which have been used for radar for the past few decades and requires many antennas and transceivers—on the order of hundreds or thousands for massive MIMO. To make such systems affordable, low-cost, low-power, and low-complexity is required—inherently compromising other system characteristics, such as linearity. The main focus of this paper will be in summarizing the challenges, recent advances, and potential future breakthroughs concerning MIMO/digital array sensitivity to interferers and nonlinear distortion. Specifically, this paper gives an overview of MIMO/digital array architectures and different techniques currently researched for the characterization and mitigation of spatial and spectral interferers and nonlinearities, which can be used to extend the effective dynamic range of low-cost MIMO/digital array systems.

Joint radar-communications dual function has drawn lots of attention since it can make a better use of the scarce wireless frequency resources and expensive hardware platforms. In case of joint radar-communications signal co-use, many communication sequences have poor range sidelobes and thus are not very suitable for the radar function. In this paper, we present a single carrier joint radar-communications method operating in the pulsed radar mode. Digital communication sequences are first partitioned into blocks which are then mapped to digital phase-coded sequences, like binary phase-shift keying (BPSK) and quadrature phase-shift keying (QPSK) sequences. The phases of the digital sequences are perturbed a bit such that certain degrees of freedom are available to optimize for lower range sidelobes. Insignificant phase perturbation will be deemed as phase noise by a communication receiver and then phase codes can be correctly decoded; in radar-processing channels, range compression are performed with known and optimized phase perturbation such that low-range sidelobes are obtained. An implementation scheme is presented. Numerical results with BPSK and QPSK sequences indicate that little phase perturbation can significantly drop the range sidelobe level but will insignificantly rise the bit error rate.

We propose a millimeter-wave joint radar-communications (JRC) system comprising a bi-static automotive radar and vehicle-to-vehicle communications. We study the applicability of known phase-modulated-continuous-wave (PMCW) and orthogonal-frequency-division-multiple-access waveforms for bi-static-JRC. In both cases, we design multiplexing strategies to ensure the parameter identifiability, derive JRC statistical bounds and numerically demonstrate superior performance of proposed low-complexity JRC super-resolution algorithms over conventional two-dimensional fast Fourier transform/MUltiple SIgnal Classification.

Both economic incentives and policy trends motivate the study of spectrum sharing between radar and wireless communications as a means to mitigate spectrum scarcity. This paper proposes a novel, temporal signal processing algorithm for a radar to mitigate interference from cyclostationary, linearly modulated digital communications (LMDC) interference such as orthogonal frequency division multiplexing (OFDM) or code division multiple access (CDMA). The proposed algorithm has the form of a novel whitening filter followed by a matched filter, and as such it optimizes the statistical deflection among the class of all linear detection filters. The derived cyclostationary whitening filter has equivalent mathematical representations as: 1) the form of a multiuser detector followed by an interference canceler, and 2) a frequency-shift (FRESH) filter. Performance results indicate that the derived cyclostationary whitener can produce signal-to-interference-plus-noise ratio (SINR) improvements ranging from negligible to up to $\text{20 dB}$ for the parameters used in this study. The cyclostationary whitener leads to the greatest SINR improvements when the interference-plus-noise is dominated by only a few LMDC signals, such as might occur in a near-far scenario.

Conventional techniques in chipless radio frequency identification (RFID) systems are incapable of fully overcoming the key challenges of modern identification applications, including high data capacity, low tag cost, and reliable operation. The idea of electromagnetic imaging in chipless RFID systems is a promising technique that shows many advantages over other conventional approaches. This paper reviews conventional chipless RFID technology and provides a comprehensive analysis of advanced millimeter wave spatial-based (also known as image-based) chipless RFID systems with an optimized multiple-input multiple-output-synthetic aperture radar technique for high-resolution image acquisition and a quick reading process.

Due to an increasing demand in channel capacity and bandwidth, there has been a growing interest in the millimeter wave (mmWave) spectrum [1]-[3]. Many researchers overcame the challenges of implementing extremely high frequency systems and secured large bandwidths comparable to that of fiber optics [4]. The mmWave spectrum offers numerous advantages not only in the wireless communication field but also in the field of sensors and radar technology [5]. Indeed, transmitting shorter wavelengths helps radars achieve higher range accuracy with smaller antenna footprints.

A novel photonic-based multiple-input multiple-output (MIMO) radar architecture is reported based on optical frequency combs and dispersion induced wavelength-dependent time delay. Using the proposed system architecture, we only need one photonic-based radar waveform generator at the transmitter side, whereas only a single receiver, consisting of a photodetector, a low-pass filter and an analog-to-digital convertor, is required at the receiver side. The key significance of the work is that all channels of the MIMO radar system share a single photonic-based transceiver, which can solve the bottleneck problem that has long restricted the application of MIMO radar with a large-scale antenna array, i.e., each channel in a MIMO radar system needs an independent transmitter and an independent receiver. The proposed photonic-based MIMO radar architecture is analyzed, demonstrated and verified by simulation using a $10\times10$ MIMO radar system and a $15\times15$ MIMO radar system. The maximum MIMO radar array size that can be supported by the system architecture is also discussed, and constraints on the number of transmitting antennas and receiving antennas are theoretically given.

Mutual interference between automotive radar sensors is becoming a major concern due to the rapid increase of vehicles equipped with such systems. While there has been a plenty of studies on the interference of frequency modulated continuous wave (FMCW) radars, no work on chirp sequence (CS) radars has been reported in the literature in spite of their growing popularity in the automotive field. In this regard, this work presents an investigation of mutual interference for automotive CS radars. We analytically derive formulas describing the probability of ghost target appearance, and the signal-to-interference mitigation gain for interference of different waveforms, including continuous wave, FMCW, and CS waveforms, with comparison to an equivalent FMCW radar model. The derived formulas on the signal-to-interference mitigation gain are also verified by simulation results.

In this paper, a dual-band photonics-based radar system used for precise displacement measures in a multitarget scenario is described. The radar was designed for monitoring applications to prevent both structural failures of buildings and landslides. The radar system exploits the technique of stepped frequency continuous wave signal modulation and the displacement of the targets is evaluated through differential phase measurements. In this work, encouraged by the results already achieved in the single-target scenario, we present an investigation extended to the case of multiple targets. We aim to evaluate the accuracy of the displacement estimation both from a simulated and experimental point of view, and to understand how multiple targets impact on the final estimate of displacements. Simulation results demonstrate that it is possible to achieve a typical accuracy of less than 0.2 mm for distances up to 400 m. These results are confirmed by preliminary experimental outcomes, which take into account different operative conditions with multiple targets. Finally, concluding remarks and perspectives draw the agenda for our future investigations.

Recent changes in U.S. policy call for spectrum sharing between radar and wireless communications. In order to inform choices of protection criteria for a radar sharing spectrum with communications systems, this paper models communications interference and its effects on a cell-averaging adaptive-threshold radar detector. First, we propose a statistical model for communications interference based on existing models and original simulations, and we find support for both Gaussian and non-Gaussian models, depending on the application. Then, we assess the impact of communications interference on radar detection. Our results suggest that when interference is not well modeled as white Gaussian noise, mean interference-to-noise ratio (INR) is not sufficient to characterize interference effects on radar, and additional interference characteristics such as kurtosis/impulsiveness and coherence time can significantly impact radar performance. We also find degradation in radar performance in relatively low-INR Gaussian interference (e.g., about $-6$ to $-\text{2 dB}$ mean INR at the output of the matched filter).

Studies have demonstrated the usefulness of micro-Doppler signatures for classifying dynamic radar targets such as humans, helicopters, and wind turbines. However, these classification works are based on the assumption that the propagation channel consists of only a single moving target. When multiple targets move simultaneously in the channel, the micro-Dopplers, in their radar backscatter, superimpose thereby distorting the signatures. In this paper, we propose a method to detect multiple targets that move simultaneously in the propagation channel. We first model the micro-Doppler radar signatures of different movers using dictionary learning techniques. Then, we use a sparse coding algorithm to separate the aggregate radar backscatter signal from multiple targets into their individual components. We demonstrate that the disaggregated signals are useful for accurately detecting multiple targets.

In order to meet the demands of “Internet above the clouds,” we propose a multiple-antenna aided adaptive coding and modulation (ACM) for aeronautical communications. The proposed ACM scheme switches its coding and modulation mode according to the distance between the communicating aircraft, which is readily available with the aid of the airborne radar or the global positioning system. We derive an asymptotic closed-form expression of the signal-to-interference-plus-noise ratio (SINR) as the number of transmitting antennas tends to infinity, in the presence of realistic co-channel interference and channel estimation errors. The achievable transmission rates and the corresponding mode-switching distance-thresholds are readily obtained based on this closed-form SINR formula. Monte-Carlo simulation results are used to validate our theoretical analysis. For the specific example of 32 transmit antennas and four receive antennas communicating at a 5-GHz carrier frequency and using 6-MHz bandwidth, which are reused by multiple other pairs of communicating aircraft, the proposed distance-based ACM is capable of providing as high as 65.928-Mb/s data rate when the communication distance is less than 25 km.

Multiple-input multiple-output (MIMO) radar enjoys the advantage of increased degrees-of-freedom and spatial diversity gain, but it cannot effectively resolves the targets closely spaced in the same angle cell (but different range cells). Frequency diverse array (FDA)-MIMO radar can handle this problem by exploiting its range-dependent beampattern. FDA-MIMO radar was, thus, suggested for range–angle estimation of targets. Nevertheless, it is necessary to provide theoretical performance analysis for such a relatively new radar technique. Since multiple signal classification (MUSIC) algorithm is widely adopted in most of the FDA-MIMO literature, this paper derives the Cramer–Rao lower bound and mean square error expressions in MUSIC-based range–angle estimation algorithms for a general FDA-MIMO radar. Furthermore, the corresponding range and angle resolution thresholds in target detection and localization are also derived. Numerical results verify that the FDA-MIMO indeed outperforms conventional MIMO radar in both range–angle estimation and resolution threshold performance.

As the use of automotive radar increases, performance limitations associated with radar-to-radar interference will become more significant. In this paper, we employ tools from stochastic geometry to characterize the statistics of radar interference. Specifically, using two different models for the spatial distributions of vehicles, namely, a Poisson point process and a Bernoulli lattice process, we calculate for each case the interference statistics and obtain analytical expressions for the probability of successful range estimation. This paper shows that the regularity of the geometrical model appears to have limited effect on the interference statistics, and so it is possible to obtain tractable tight bounds for the worst case performance. A technique is proposed for designing the duty cycle for the random spectrum access, which optimizes the total performance. This analytical framework is verified using Monte Carlo simulations.

Increasing safety and automation in transportation systems has led to the proliferation of radar and IEEE 802.11pbased dedicated short-range communication (DSRC) in vehicles. However, current implementations of vehicular radar devices are expensive, use a substantial amount of bandwidth, and are susceptible to multiple security risks. In this paper, we use the IEEE 802.11 orthogonal frequency-division multiplexing communications waveform, as found in IEEE 802.11a/g/p, to perform radar functions. In this paper, we present an approach that determines the mean-normalized channel energy from frequencydomain channel estimates and models it as a direct sinusoidal function of target range, enabling closest target range estimation. In addition, we propose an alternative to vehicular forward collision detection by extending IEEE 802.11 DSRC and WiFi technology to radar, extending the foundation ofjoint communications and radar frameworks. Furthermore, we perform an experimental demonstration near DSRC spectrum using IEEE 802.11 standard compliant software defined radios with potentially minimal modification through algorithm processing on frequency-domain channel estimates. The results of this paper show that our solution delivers sufficient accuracy and reliability for vehicular RADAR if we use the largest bandwidth available to IEEE 802.11p (20 MHz). This indicates significant potential for industrial devices with joint vehicular communications and radar capabilities.

Frequency modulation continuous wave (FMCW) radar receivers generally suffer from transmitter leakage due to insufficient TX-to-RX isolation. One of the effective approaches to solving this problem is using reflected power cancelers (RPCs) that cancel the leakage from the transmitter adaptively. In this paper, a linear time invariant (LTI) model of the RPC is derived in order to carry out a comprehensive study of the mechanism of leakage cancelation and output noise performance for CW radar applications. Loop frequency responses for receiving signal, loop stability, and the influence of dc offset of IQ mixer are analyzed by a simplified transfer function. A detailed noise model of the RPC is established based on the LTI model to study the output noise components of the RPC under a large incident leakage, then the internal noise cancelation mechanism is elucidated. A prototype with its operating frequency range from 820 to 1020 MHz at UHF band is implemented. Measured loop frequency responses are in agreement with simulation results obtained with the proposed model. Furthermore, measured cancelation ratios for leakages of different ramp rates comply with the normalized power gain at corresponding frequency offsets. The input-referred receiving noise of the RPC prototype is measured to be −155 dBm/Hz at 100-kHz offset under +10-dBm incident leakage power. The proposed LTI model provides a useful tool for the design of high-performance RPC for FMCW systems in different application environments.

[EN] Multiple-input multiple-output (MIMO) radars have been shown to improve target detection for surveillance applications thanks to their proven high-performance properties. In this paper, the design, implementation, and results of a complete 3-D imaging frequency-modulated continuous-wave MIMO radar demonstrator are presented. The radar sensor working frequency range spans between 16 and 17 GHz, and the proposed solution is based on a 24-transmitter and 24-receiver MIMO radar architecture, implemented by timedivision multiplexing of the transmit signals. A modular approach based on conventional low-cost printed circuit boards is used for the transmit and receive systems. Using digital beamforming algorithms and radar processing techniques on the received signals, a high-resolution 3-D sensing of the range, azimuth, and elevation can be calculated. With the current antenna configuration, an angular resolution of 2.9° can be reached. Furthermore, by taking advantage of the 1-GHz bandwidth of the system, a range resolution of 0.5 m is achieved. The radio-frequency front-end, digital system and radar signal processing units are here presented. The medium-range surveillance potential and the high-resolution capabilities of the MIMO radar are proved with results in the form of radar images captured from the field measurements.

This paper presents a rotatable cyclic Vernier digital-to-time converter (DTC) with 1.8 ps timing resolution on an 80 ns time scale. The proposed DTC features high timing resolution, and can be utilized in beam-steering arrays, which is infeasible for ordinary Vernier DTCs. The proposed DTC was implemented within a passive time-equivalent direct-sampling ultra-wideband impulse-radio radar system and was fabricated in 65 nm CMOS technology. This radar system is capable of quantizing direct-sampled impulse waveforms to provide full degrees of freedom for backend digital signal processing. The measured differential nonlinearity/integral nonlinearity of the DTC was +4.6/−3 and 12.4/−9.4 where the LSB was 1.8 ps, and the total power consumption was 133 mW. Also, a new method for localization between wireless sensor nodes of equivalent-time direct-sampling radar is presented in this paper; this method can theoretically achieve resolution as high as that of regular radar.

The mitigation of third-order intermodulation distortion produced by a nonlinear tunable bandpass filter (BPF) in a digital receiver channel is demonstrated. An iterative solution is proposed, in the use of the least-mean-square algorithm, as an effective way to allow the correction coefficients to adapt to the changes in the system characteristics when the center frequency is changed. Results are shown using a two-pole, varactor-loaded BPF, and an Analog Devices AD9371 transceiver.

The paper proposes a cooperative scheme for the coexistence of a multiple-input-multiple-output (MIMO) communication system and a matrix completion (MC) based, collocated MIMO (MIMO-MC) radar. To facilitate the coexistence, and also deal with clutter, both the radar and the communication systems use transmit precoding. For waveform flexibility, the radar uses a random unitary waveform matrix. We prove that for such waveforms and any precoding matrix, the error performance of MC is guaranteed. The radar transmit precoder, the radar subsampling scheme, and the communication transmit covariance matrix are jointly designed in order to maximize the radar SINR, while meeting certain communication rate and power constraints. The joint design is implemented at a control center, which is a node with whom both systems share physical layer information, and which also performs data fusion for the radar. We provide efficient algorithms for the proposed optimization problem, along with insight on the feasibility and properties of the proposed design. Simulation results show that the proposed scheme significantly improves the spectrum sharing performance in various scenarios.

Coexistence between 802.11 wireless local area network (WLAN) and radars operating in co/adjacent channel scenarios (notably 5GHz) is a problem of considerable importance that requires new innovations. We propose a modified Wi-Fi link design that mitigates the interference from a pulsed search radar such that the WLAN network continues to operate outside the exclusion region. For low density parity check encoding adopted in high throughput WLANs such as 802.11n and.11ac, the modified receiver includes a new interleaver and a log-likelihood ratio (LLR) mapping function to mitigate the impact of radar interference. Two detection approaches are proposed to detect the radar pulse interference to Wi-Fi; time domain cyclic prefix auto-correlation detection and frequency domain data subcarrier based detection. The detection approaches are derived analytically and their performances are evaluated via simulation. We investigate the impact of interleaver length and LLR mapping function parameters via simulations to obtain the desirable frame error rate. Under the known radar pulse arrival at the Wi-Fi receiver, the modified system can significantly mitigate the radar interference for all interference to noise ratio (INR) values by using the frame interleaver. Using the radar pulse detectors in the system, the modified system can mitigate the interference at high and low INRs, while it can partially mitigate the interference in the range of 3

In this paper, a new Ka-band Doppler radar with an ability to remotely monitor respiration rate, heartbeat rate (HR), and heart rate variability (HRV) is presented. Exploiting the advantage of high sensitivity of Ka-band radar in sensing of chest-wall movement, we make more accurate reconstruction of cardiopulmonary activities from low-quality received signal. The advantage of using Ka-band radar is obtained by paying a penalty, which is harmonic interferences that make measuring of cardiopulmonary details infeasible in lots of real scenarios. In this paper, by using a more complete model of return signal, a new routine is introduced for the robust detection of breathing and HR that extremely alleviates the problems associated with harmonic interferences. Besides, a more suitable model is proposed, which can cover time-variability cardiorespiratory features. Taking advantage of this model and based on the unconditional orthonormal representation of band-limited signals, a filter with time-varying coefficients is proposed to extract HRV. This extraction is done without resorting to tracking HR trace that makes it more precise and robust than the conventional approach. The indicated filter enables us to suggest a novel approach to remove random body motion effects. By experimental data, the applicability of the new radar for a wide range of real world scenarios is investigated, and its advantages beside conventional approaches are proved practically in different aspects.