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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.

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.

Recently, the photonics-radar technology comes out as an attractive candidate in the arena of smart autonomous transportation, surveillance, and navigation-related applications owing to provide wide-spectra to attain improved and precise radar-resolutions. On the other hand, microwave radars, due to limited bandwidth, are incapable of coping with the demands of next-generation radar technology. Moreover, the atmospheric fluctuations become more prominent at higher frequencies and affect the radar’s performance significantly. Subsequently, the authors develop a 2 × 2 multi-input multi-output (MIMO) employed linear frequency-modulated continuous-wave coherent photonic-radar system (MIMO-Co-PHRAD) using OptiSystem™ and MATLAB™ to attain a prolonged detection-range with an enhanced visibility. The developed MIMO-Co-PHRAD is investigated with heterodyne- and homodyne-detection approaches under weak-to-strong regimes of the atmospheric fluctuations like Rain and Fog. A comparison is also drawn for both the demonstrated MIMO-equipped laser-driven coherent photonic-radar systems. The performance of both the developed MIMO-Co-PHRAD systems is evaluated by measuring the intensity of reflected-echoes, signal-to-noise ratio, and range-Doppler patterns. A contrast with the single-input single-output coherent photonic-radar (SISO-Co-PHRAD) is also established to validate the robustness of the demonstrated MIMO-Co-PHRAD.

In the present century, digital signal processing (DSP) approaches are considered to be one of the most powerful technologies which may shape the science and technology in coming decades. From 1970 onwards, a drastic revolution took place in a wider domain of DSP which has made it popular in several studies such as radar and sonar signal processing, digital televisions, wireless communication scenarios and other multimedia setup etc. Digital filters form the backbone of this DSP architecture and in point of fact the field of digital filter design has drawn justified recognition from the researchers throughout the world for the last 50 years. In connection to this, thousands of research articles may be found from the literature which had extensively addressed on the design of such filters. In order to meet the requirement of narrow transition-band, finite impulse response (FIR) filters are commonly assumed to be of higher order and accordingly it significantly enhances computational complexity. In regard to this, construction of hardware efficient digital filters had drawn significant consideration which aims to include minimum hardware elements during its application and consequently consumes less power. This review paper illustrates various techniques for the implementation of hardware efficient narrow transition-band FIR filter and investigates a number of favourable attributes which are capable in sustaining the stringent requirements of communication standards. A good number of relevant articles are taken from the literature so as to make a robust and complete review.

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 ultra-wideband chaotic radar with wireless synchronization command is proposed and experimentally demonstrated for target localization and tracking. This radar uses the wideband chaotic pulse position modulation (CPPM) signal as the probe signal and the radar structure of single-transmitting-dual-receiving. The echo signal scattered from a target is collected by two receivers. The target is located and tracked accurately in two-dimensional space using the signal processing scheme. In particular, the radar receivers can directly generate the CPPM reference signals through a wireless synchronization command, so that the transceivers can be physically separated without cable or optical fiber connection. Experimental results demonstrate the proposed chaotic radar can locate and track the target accurately. A localization error of 11 cm and a detection resolution of 17 cm can be both achieved. Moreover, this radar possesses the excellent immune performance to the external electromagnetic interferences, which makes it suitable in the complex electromagnetic environment caused by the cooperative work of multiple radars.

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.

Compared with conventional phased array radar, the collocated multiple-input multiple-out (C-MIMO) radar is envisioned to offer greater freedom in waveform design and can simultaneously manage different beams to track multiple targets in the simultaneous multi-beam (SM) working mode. In this study, aiming at the multiple targets tracking (MTT) problem, a joint beam selection integrated with power and bandwidth allocation (JSPBA) scheme for the C-MIMO radar is proposed in the SM mode. By incorporating the modified particle filter, the predicted conditional Cramer–Rao lower bound (PC-CRLB) is calculated, which gives a measure of the best achievable performance for targets tracking. Then, the optimisation model is established with the aim of improving the worst case of PC-CRLB to achieve better performance of the worst-case tracking. Next, a three-step solution method is proposed to solve the JSPBA problem by converting the non-convex problem into a series of convex problems. At last, after the solutions are fed back to the control centre to guide the beam generation in the next tracking epoch, a cognitive tracking system is established. Simulation results confirm the superiority of the proposed method in improving the MTT performance in C-MIMO radar system.

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.

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.

An inherent disadvantage of a Microstrip Patch Antenna (MPA) is its narrow bandwidth and low gain. There are various techniques in the market that either enhances gain or bandwidth of the MPA. The proposed system uses a novel technique which proves to enhance both the bandwidth, as well as the gain up to a great extent, simultaneously. We have tried to overcome these limitations by inserting slots in the proposed Rectangular Microstrip Patch Antenna (RMPA), also known as the slotted array technique. The proposed antenna has been designed for an operating frequency of 9 GHz which lies in the X-band of an electromagnetic system. It has been simulated over an RT Roger/duroid 5880 material that has a dielectric constant of 2.2, using HFSS software. It was observed that the RMPA has a bandwidth of 425.2 MHz, whereas, a bandwidth of 920 MHz has been achieved for slotted RMPA, that means 494.8 MHz of bandwidth enhancement. In addition to this, a gain of 6.92 dB has been achieved for RMPA, whereas, by introducing slots, the gain becomes 19.88 dB, i.e., an enhanced value of 12.96 dB has been achieved. This antenna can be used in various wireless applications such as: Wi-Fi, Bluetooth, and wireless LAN, and satellite and radar communication.

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.

Fully autonomous driving, even under bad weather conditions, requires use of multiple sensor systems including radar imaging. Microwave photonics, especially the optical generation and distribution of radar signals, can overcome many of the electronic disadvantages. This article will give an overview about several photonic components and how they could be incorporated into a photonic synchronized radar system, where all the complexity is shifted to a central station. A first proof-of-concept radar experiment with of the shelf telecommunication equipment shows an angular resolution of 1.1°. Furthermore an overview about possible photonic electronic integration is given, leading to comprising low complexity transmitter and receiver chips.

A microwave photonic (MWP) video imaging radar with a bandwidth tuning range of 0–10 GHz is proposed and experimentally demonstrated. In the transmitting path, high-frequency radar transmission signals with varied bandwidths are generated by optical frequency multiplication of an electrical low-frequency signal with tunable bandwidth, which enables radar to image targets with proper resolution and thus optimizes the balance between the observation distance and resolution. In the receiving path, in order to realize video imaging, the high-frequency echo signals with large bandwidth, after being subjected to MWP down-conversion technology for de-chirping, can be sampled by a low-speed and high-precision analog-to-digital converter Then, a digital signal processor is employed for processing the sampled echo data to realize video imaging. In field experiments, imaging ability with varied resolution is firstly verified by imaging Boeing 737 airliner with different-bandwidth radar signals. Moreover, continuous monitoring the flight process of non-cooperative Boeing 737 airliner and unmanned aerial vehicle also successfully demonstrates the video imaging ability of the proposed MWP radar. The capturing of detail structures and the recognition of target flight posture changes all indicate a great potential of the MWP radar for observing distant-range targets of interest.

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 propose a deep learning-based indoor two-dimensional (2D) localization scheme using a 24 GHz frequency-modulated continuous wave (FMCW) radar. In the proposed scheme, deep neural network and convolutional neural network (CNN) models that use different numbers of FMCW radars were employed to overcome the limitations of the conventional 2D localization scheme that is based on multilateration methods. The performance of the proposed scheme was evaluated experimentally and compared with the conventional scheme under the same conditions. According to the results, the 2D location of the target could be estimated with a proposed single radar scheme, whereas two FMCW radars were required by the conventional scheme. Furthermore, the proposed CNN scheme with two FMCW radars produced an average localization error of 0.23 m, while the error of the conventional scheme with two FMCW radars was 0.53 m.

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.

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.

The authors present cognitive automotive radar (CARr) as a significant capability to the sensing technology suite of autonomous driving vehicles. CARr is a closed-loop intelligent radar system utilising the automotive frequency bands of 24-25 and 76-77 GHz for the purposes of ground vehicle target signature identification. The authors consider specific cases of ground vehicle recognition and ground vehicle class identification in the presence of aspect angle uncertainty using forward-looking automotive radar. The transmit-adaptive waveforms are based from signal-to-noise ratio and mutual information optimisation metrics. In this study, two new adaptive waveform techniques with the flexibility to accommodate angular uncertainty probability distributions are introduced. The classification performance of these new waveforms is compared against the receive-adaptive wideband pulsed and other transmit-adaptive waveforms in the presence of angular uncertainties characterised by the uniform and truncated normal distributions. To ensure the validity of results, high-fidelity electromagnetic simulated radar cross-section signatures generated from scaled-to-true-physical-size ground vehicle computer-aided design models are utilised.

This paper describes a 24 GHz frequency synthesizer for automotive collision avoidance radar. This circuit is designed using 65 nm CMOS technology. The voltage-controlled oscillator (VCO) in modifi...

Spectrum sharing using a joint platform for radar and communication systems has attracted significant attention in recent years. In this paper, we propose a novel dual-function radar-communications (DFRC) strategy to embed quadrature amplitude modulation (QAM) based communication information in the radar waveforms by exploiting sidelobe control and waveform diversity. The proposed information embedding technique can support multiple communication receivers located in the sidelobe region. In addition to the information broadcasting, the developed approach enables multi-user access by allowing simultaneous transmission of distinct information streams to the communication receivers located in different directions. We prove that the proposed technique ensures a significant data rate enhancement compared to the existing techniques. Moreover, the developed DFRC strategy generalizes the mathematical framework of the existing sidelobe control-based information embedding techniques.

Portable, low-cost, microwave radars have attracted researchers’ attention for being an alternative noncontact solution for structural condition monitoring. In addition, by leveraging their capability of providing the target velocity information, the radar-based remote monitoring of complex rotating structures can also be accomplished. Modern radar systems are compact, able to be easily integrated in sensor networks, and can deliver high accuracy measurements. This paper reviews the recent technical advances in low-cost Doppler radar systems for phase-demodulated displacement measurements and time-Doppler analysis for structural health information, including digital signal processing and emerging applications related to radar sensor networks.

In this research article, a beetle shape Multiple-Input-Multiple-Output (MIMO) antenna including dual notched band characteristics are presented for different wireless band applications (UWB, X-Band and Ku Band) which are also experimentally and computationally investigated. A single evoluation antenna is demonstrated which is than converted to MIMO configuration to overcome the demerits when placed in communication channel. The overall volume of the proposed antenna is 25 × 48 × 0.787 mm3 printed on Rogers RT Duroid5870. Dual notched bands are obtained by etching an L-shaped slot on a radiating patch for WiMAX interference and satellite Downlink System interference (DSS) is removed by placing pair of C-shaped parasitic elements near the feed line. The proposed antenna offers measured isolation between two ports less than − 20 dB in entire operating bandwidth (2.57–19.15 GHz). At non-radiating mode, the radiation efficiency of antenna drops down due to the insertion of stop and filters. The wider impedance bandwidth of the antenna suggest that it is not only capable of working in UWB range but also finds applications in X- and Ku-Band applications allocated for Satellite and RADAR. An antenna is also reconfigured using PIN diodes to control each notched bands independently. Proposed MIMO antenna also offers better diversity performance in terms of ECC 9.95 dB, TARC

In recent years, multiple functions traditionally realized by hardware components have been replaced by digital-signal processing, making radar and wireless communication technologies more similar. A joint radar and communication system, referred to as a RadCom system, was proposed to overcome the drawbacks of the conventional existent radar techniques while using the same system for intervehicular communication. Consequently, this system enhances used spectral resources. Conventional orthogonal frequency division multiplexing (OFDM) was proposed as a RadCom waveform. However, due to OFDM’s multiple shortcomings, we propose universal filtered multicarrier (UFMC), a new 5G waveform candidate, as a RadCom waveform that offers a good trade-off between performance and complexity. In addition to that, we propose multicarrier code division multiple access (MC-CDMA) as a multiple-access (MA) technique that can offer great performance in terms of multiuser detection and power efficiency. Moreover, we study how UFMC filter length and MC-CDMA spreading sequences can impact overall performance on both radar and communication separately under a multipath channel. Analysis of the bit error rate (BER) of the UFMC waveform was performed in order to confirm the experiment results.

International audience; In this article, we demonstrate the use of general software-defined radio (SDR) hardware for ground-based interferometric radar (GBIR) system development for static target imaging and displacement estimation purposes. First, a system synchronization approach is proposed within the free and open-source framework GNU Radio, followed by a frequency-domain bandwidth synthesis method used to improve the range resolution with three different waveforms. Second, data preprocessing and target imaging methods are proposed to reduce the negative influences of practical nonideal factors and get high-quality target images. Finally, various experiments are conducted to show the performance of the developed SDR-GBIR system and the proposed methods. It is shown that high-resolution target image and high-accuracy displacement measurement can be obtained by our SDR-GBIR systems.

This paper presents an analysis of a new method of automotive radar self-calibration which uses targets of opportunity. While conventional offline calibration of a phased array antenna requires accurate knowledge of the positions of calibration targets relative to the radar, such information is not available in a dynamic scenario. To compensate for this, we have developed an estimation procedure based on an extended Kalman filter (EKF) to address the challenge of simultaneous localisation, mapping and calibration. The proposed technique makes it possible to compensate for moderate errors of amplitude and phase in the phased array response with just a few measured frames. A significant reduction in the sidelobe rejection of the array response, plus the ability to correct for angular steering errors, are demonstrated via numerical simulations and real data processing.

Mobile devices, climate science, and autonomous vehicles all require advanced microwave antennas for imaging, radar, and wireless communications. We propose a waveguide-fed metasurface antenna architecture that enables electronic beamsteering from a lightweight circuit board with varactor-tuned elements. Our approach uses a unique feed structure and layout that enables spatial sampling at the Nyquist limit of half a wavelength. We detail the design of this Nyquist metasurface antenna and experimentally demonstrate electronic beamsteering in two directions. Nyquist metasurface antennas can realize high performance without costly and power hungry phase shifters, making them a compelling technology for future antenna hardware.

An incoherent optical detection sensor (often referred to as energy or direct detection sensor) used for remote detection and ranging purposes is a useful tool. While the accuracy and robustness of an incoherent sensor relative to a coherent sensor may be lacking particularly in cluttered environments, it has a place in the world due to its simplicity and performance. With this, a best design approach is sought to meet requirements in a stochastic fashion. In developing the design approach, motivations are borrowed from decades of research in radar systems. This article provides a sensor- or top-level design approach for an incoherent optical detection sensor based mainly on paths developed in radar.

Real-time tracking of a waveform frequency content is essential for detection and analysis of fast rare events in communications, radar, radio astronomy, spectroscopy, sensing etc. This requires a method that can provide real-time spectrum analysis (RT-SA) of high-speed waveforms in a continuous and gap-free fashion. Digital signal processing is inefficient to perform RT-SA over instantaneous frequency bandwidths above the sub-GHz range and/or to track spectral changes faster than a few microseconds. Analog dispersion-induced frequency-to-time mapping enables RT-SA of short isolated pulse-like signals but cannot be extended to continuous waveforms. Here, we propose a universal analog processing approach for time-mapping a gap-free spectrogram −the prime method for dynamic frequency analysis− of an incoming arbitrary waveform, based on a simple sampling and dispersive delay scheme. In experiments, the spectrograms of GHz-bandwidth microwave signals are captured at a speed of ~5×109 Fourier transforms per second, allowing to intercept nanosecond-duration frequency transients in real time. This method opens new opportunities for dynamic frequency analysis and processing of high-speed waveforms., Real-time dynamic Fourier analysis of high-speed signals is difficult using either digital or analog schemes. Here, the authors present a universal analog approach that can track the changing frequency spectrum of waveforms in a real-time fashion at the nanosecond level, continuously and with no gaps.

The photonic radar is attaining its popularity significantly for the last few years due to its potential to offer wide bandwidth to achieve an extended target-range with high range- and image-resolution [8-10]. On the other hand, the state-of-the-art microwave radar is incapable to meet these essential requirements of the self-driving vehicles due to its limited bandwidth. Moreover, to work at higher microwave-frequencies to attain high bandwidth, the microwave radar’s performance is affected by atmospheric fluctuations that result in short target-range. So, it becomes imperative to demonstrate and investigate a photonic radar that has the potential to achieve a prolonged target-range in harsh environment perceptions. Subsequently, the authors develop a model of linear frequency-modulated photonic radar to capture the reflected echoes with high power sufficient for target-detection with high accuracy using two simulation software, i.e. Matlab TM and Optisys TM . Further, the demonstrated photonic radar is developed and carried out under the influence of weak-to-strong atmospheric regimes. Our work determines how the weak-to-strong states of atmospheric fluctuations affect the demonstrated photonic radar and which detection strategy, either coherent or non-coherent, should be adopted to attain a prolonged target-range in the presence of harsh weather conditions. The results show better signal-to-noise ratio with high power of reflected echoes to achieve an extended target-range and are aligned in the acceptable ranges.

The evolution of microwave and mm-wave systems for communication and remote sensing is heading towards a massive deployment of phased-array antennas with beamforming capabilities. 5G wireless access networks are expected to employ beamforming to optimize resources allocation, whereas radars will benefit from precise and fast-scanning antennas. Moreover, in the next future, those systems are expected to widely employ photonic technologies for signal generation, acquisition, and distribution. In this scenario, photonics can allow for the development of high-performance beamforming networks, which can easily be integrated in photonics-assisted RF systems, combining broad operational bandwidth, low signal distortion, and high pointing precision with unprecedented flexibility. In this paper, a phase shift-based beamforming network for microwave applications is presented and its performance analyzed. The Si-photonics integrated phase shifters exhibit large phase shift (>360°) and limited amplitude fluctuations (∼2.5 dB). The packaged beamforming network elements show extremely low signal distortion, low steering error (

Modern radar systems are expected to operate reliably in congested environments. A candidate technology for meeting these demands is frequency agile radar (FAR), which randomly changes its carrier frequencies. FAR is known to improve the electronic counter-countermeasures (ECCM) performance while facilitating operation in congested setups. To enhance the target recovery performance of FAR in complex electromagnetic environments, we propose two radar schemes extending FAR to multi-carrier waveforms. The first is Wideband Multi-carrier Agile Radar (WMAR), which transmits/receives wideband waveforms simultaneously with every antenna. To mitigate the demanding hardware requirements associated with wideband waveforms used by WMAR, we next propose multi-Carrier AgilE phaSed Array Radar (CAESAR). CAESAR uses narrowband monotone waveforms, thus facilitating ease of implementation of the system, while introducing {\em spatial agility}. We characterize the transmitted and received signals of the proposed schemes, and develop an algorithm for recovering the targets, based on concepts from compressed sensing to estimate the range-Doppler parameters of the targets. We then derive conditions which guarantee their accurate reconstruction. Our numerical study demonstrates that both multi-carrier schemes improve performance compared to FAR while maintaining its practical benefits. We also demonstrate that the performance of CAESAR, which uses monotone waveforms, is within a small gap from the wideband radar., Comment: 16 pages