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As a noncontact and noninvasive sensor, radar offers attractive modality for human motion recognition in many fields, such as surveillance, smart homes, and assisted living. As a dynamic process, a comprehensive multidomain analysis in stream is crucial for human motion recognition. In this article, a novel spatial–temporal convolution long short-term memory (ST-ConvLSTM) network using dynamic range-Doppler frames (DRDF) based on portable frequency-modulated continuous-wave (FMCW) radar is proposed to address this problem. First, DRDF is introduced to characterize different human motions in time, range, Doppler, and radar cross section (RCS) domains with a time-sequenced range-Doppler maps. Then, ConvLSTM cell is investigated to extract continuous 2-D image features by combining both convolution operation and LSTM cell. Furthermore, a spatial attention module is utilized to emphasize the spatial distribution of human motion in the range-Doppler domain, while a temporal attention module is designed to obtain optimal temporal weights considering behavior continuity. Finally, an extensive radar dataset from 16 volunteers demonstrated its feasibility and superiority in the classification of six typical daily human motions. The contributions of attention modules and its robustness facing individual diversity are also investigated and discussed. [ABSTRACT FROM AUTHOR]

Radar-based gesture recognition can play a vital role in autonomous vehicles’ interaction with vulnerable road users (VRUs). However, in automotive scenarios the same gesture produces strongly differing radar responses owing to the wide range of variations such as position, orientation, or ego-motion. Since including all kinds of modifications in a measured dataset is laborious, gesture simulations alleviate the measurement effort and increase the robustness against edge and corner cases. Hence, this article presents a flexible geometric human target model allowing the direct introduction of a wide range of modifications, while it facilitates the handling of shadowing effects and multiradar constellations. Using the proposed simulation model, a dataset recorded with a radar sensor network consisting of three chirp sequence (CS) radars is resimulated based on the motion data simultaneously captured with a stereo video system. Completely substituting the measured by the simulated data for training, a convolutional neural network (CNN) classifier still achieves 80.4% cross-validation accuracy on a challenging gesture set, compared with 89.4% for training on the measured data. Moreover, using the simulated data the classifier is shown to successfully generalize to new scenarios not observed in measurements. [ABSTRACT FROM AUTHOR]

This work provides a proof-of-concept for a linear-position sensor using an ultrawideband (UWB) frequency-modulated continuous wave (FMCW) radar system operating at 126–182 GHz. It is the first work to show environmental compensated and calibration-free distance measurements with micron accuracy at medium range using millimeter-wave (mmWave) radar technology. We addressed hardware imperfections, parameter estimation, and the free-space path, i.e., refractive index and near-field effects. The proposed signal processing chain is robust to interference and of low computational cost. Experiments reveal a systematic error of $\pm 1~\mu \text{m}$ over 4.8 m (0.8–5.6 m), and a random error at a minimum of 30 nm, providing very high sensitivity. [ABSTRACT FROM AUTHOR]

Identity authentication based on Doppler radar respiration sensing is gaining attention as it requires neither contact nor line of sight and does not give rise to privacy concerns associated with video imaging. Prior research demonstrating the recognition of individuals has been limited to isolated single-subject scenarios. When two equidistant subjects are present, identification is more challenging due to the interference of respiration motion patterns in the reflected radar signal. In this research, respiratory signature separation techniques are functionally combined with machine learning (ML) classifiers for reliable subject identity authentication. An improved version of the dynamic segmentation algorithm (peak search and triangulation) was proposed, which can extract distinguishable airflow profile-related features (exhale area, inhale area, inhale/exhale speed, and breathing depth) for medium-scale experiments of 20 different participants to examine the feasibility of extraction of an individual’s respiratory features from a combined mixture of motions for subjects. Independent component analysis with the joint approximation of diagonalization of eigenmatrices (ICA-JADE) algorithm was employed to isolate individual respiratory signatures from combined mixtures of breathing patterns. The extracted hyperfeature sets were then evaluated by integrating two different popular ML classifiers, k-nearest neighbor (KNN) and support vector machine (SVM), for subject authentication. Accuracies of 97.5% for two-subject experiments and 98.33% for single-subject experiments were achieved, which supersedes the performance of prior reported methods. The proposed identity authentication approach has several potential applications, including security/surveillance, the Internet-of-Things (IoT) applications, virtual reality, and health monitoring. [ABSTRACT FROM AUTHOR]

A frequency-modulated ultrawideband (FM-UWB) hybrid transceiver, with a high system reuse ratio up to 90%, is fabricated in the 65-nm CMOS process for both short-range wireless communication and high-resolution radar ranging. The radio frequency (RF) front-ends (RFFEs) based on module stacking and current reuse achieve significant RF power savings of about 30% and 50% for the transmitter and the receiver (RX), respectively. The presented IF zero-crossing delay discrimination benefits a high radar resolution less than 1 cm. A multimode relaxation oscillator (OSC) for the reconfigured triangular subcarrier generation and a dual-path ring voltage-controlled oscillator (VCO) for the linear FM, stacked by a wideband push–pull power amplifier (PA), generate an FCC-compliant UWB signal. An active balun embedded low-noise amplifier (LNA) and two symmetric-detuning band-passed filters (BPFs) are stacked with the bandwidth extension to linearly demodulate the UWB FM signal. Experimental results show that the 3.75–4.25-GHz hybrid transceiver has an energy efficiency of 1.9 nJ/bit with an active area of 0.7 mm2 and a power dissipation of 1.9 mW and achieves the RX sensitivity of −71 dBm and the transmitted power of −14.1 dBm, with a bit error rate (BER) of 10−4 at a distance of 4 m under the data rate (DR) of 0.1–1.0 Mbps. The transceiver also achieves the noise figure (NF) of 4.8 dB and the phase noise of −78.6 dBc/Hz at 1-MHz offset frequency. [ABSTRACT FROM AUTHOR]

A high-power Y-junction circulator is proposed for radar applications in the Ku-band (12–18 GHz). The design consists of two identical circulators combined using power splitters at all ports. The overall circulator network achieves 20-dB isolation level and return loss over the Ku-band with a peak power level of 14 kW. An internally matched divider is used at one port of the overall system to eliminate the cavity resonances produced by the practical asymmetries between the two circulators. The asymmetry problem is analyzed in detail to understand the consequences of these practical variations fully. Experimental validation is done by a fabricated prototype and shows a good agreement between the simulated and the measured results with differences in the range of ±2 dB. [ABSTRACT FROM AUTHOR]

Compared with a conventional Doppler radar in which target displacement results in phase modulation, target displacement in a self-injection-locked oscillator (SILO)-based radar results in frequency modulation. Since the instantaneous phase is the time integral of frequency, the SILO-based radar is considered to have higher sensitivity than the conventional Doppler radar. However, a direct comparison between the SILO-based radar and the conventional Doppler radar is still needed to quantitatively understand the sensitivity difference. This article provides a rigorous time-domain analysis of the sensitivity of the SILO-based radar with a delay-based frequency demodulator for small-amplitude periodic motions. The analysis follows an approach similar to the time-domain analysis for the conventional Doppler radar. It reveals that two null detection point mechanisms could arise in SILO-based radar systems. The target distance may introduce one null detection point, and the delay added in the frequency demodulator may introduce another. Furthermore, this article also proposes an SILO-based radar with dual null detection points’ removal. Unlike the Doppler radar, where $I/Q$ demodulation eliminates the null detection point introduced by the target distance, $I/Q$ demodulation in the SILO-based radar only eliminates the null detection point introduced by the delay cable. To overcome the other null detection point mechanism, a phase shifter is introduced after the LNA. Experiments were carried out to validate the proposed time-domain analysis and demonstrate that both the techniques need to be used simultaneously to remove both null detection points in the system. The sensitivity comparison was performed using a conventional Doppler radar and an SILO-based radar built with identical microwave components. [ABSTRACT FROM AUTHOR]

A photonics-based leakage cancellation and echo signal de-chirping approach for frequency-modulated continuous-wave radar systems is proposed based on a dual-drive Mach–Zehnder modulator (DD-MZM). The de-chirp reference signal and the leakage cancellation reference signal are combined and applied to the upper arm of the DD-MZM, while the received signal, including the leakage signal and echo signals, is applied to the lower arm of the DD-MZM. When the amplitudes and delays of the leakage cancellation reference signal and the leakage signal are precisely matched, the leakage signal is canceled in the optical domain. The de-chirped signal is obtained after the leakage-free optical signal is detected in a photodetector. An experiment is performed. The cancellation depth of the leakage signal after de-chirping is around 23 dB when the center frequency and bandwidth of the linearly frequency-modulated signal are 11.5 and 2 GHz, respectively. When the leakage cancellation is not employed, the leakage will seriously affect the imaging results and distance measurement accuracy. When the leakage cancellation is enabled, the imaging results of multiple targets can be clearly distinguished, the distance measurement error of a moving target is significantly reduced to less than 10 cm, and a dynamic range increase of 21 dB is achieved. [ABSTRACT FROM AUTHOR]

Range migration (or range focusing) techniques are widely used in optical, acoustic, and microwave real-time image reconstruction methods. They have been successfully applied to far-field 3-D imaging where they rely on plane-wave assumptions, which ignore the data amplitude variation over the acquisition aperture. The accuracy of the plane-wave assumption, however, quickly degrades in close-range imaging, where amplitude variations are significant and where the range to the target is on the order of the range sampling step. Here, we present a range-focusing method of improved accuracy, which is applicable to both far-zone and close-range monostatic radar. It refocuses the system point-spread function (PSF) to any range location, taking into account both magnitude and phase changes. The approach can be applied with any Fourier-based imaging algorithm utilizing the Lippmann–Schwinger equation as the underlying scattering model. Here, it is validated through examples based on simulated and measured data where the images are reconstructed with quantitative microwave holography (QMH). QMH employs measured PSFs to achieve quantitative imaging in real-time. The proposed range-migration method is applicable with measured PSFs, too, leading to reduced system-calibration effort and the ability to focus an image at any desired range. [ABSTRACT FROM AUTHOR]

A multiple-frequency continuous-wave (MFCW) agile radar system has the ability to cope with various physiological conditions of a human subject. Following the mathematic model, a favorable carrier frequency for detection is pursued by analyzing the amplitude and composition of the baseband signal. In Experiment-1, a CMOS dual-band transceiver prototype emulate searching a subject from a distance. The frequencies of the dual-band system are 4.26–4.95 GHz and 17.06–19.79 GHz. During the experiment, the respiratory signal could be detected up to 12 m, and the heartbeat signal up to 6 m. Even with a wooden or a brick barrier in the path, the vital-sign detection remained satisfactory. Later, a concurrent MFCW detection is performed in Experiment-2 for more precise analyses. From the concurrent results, the breathing status can be inferred, and by cross-correlating the results after the ensemble empirical mode decomposition (EEMD) and principal component analysis (PCA), the nonlinear effects of respiratory harmonics or intermodulation tones are reduced, resulting in an accurate heart rate extraction. The receiver front-end and the signal source are manufactured using a 180-nm CMOS process, both packaged on an RO4003C printed-circuit board (PCB). [ABSTRACT FROM AUTHOR]

This article presents a stepped-frequency hybrid modulation (SFHM) methodology, which is proposed to work in conjunction with a frequency scanning array to effectively perform respiration monitoring, 2-D localization for stationary human subjects, and target trajectory tracking for moving ones. Conventional frequency-shift keying (FSK) radar can accurately detect the absolute distance and small displacement but suffers from the problem of a maximum unambiguous range. In comparison, continuous-wave radar with a chirp signal has no range limitation but suffers from a limited displacement measurement accuracy. To solve the two problems, SFHM is proposed to make full use of the advantages of both FSK mode and chirp mode, collaboratively resolving each other’s issues. In addition, the high flexibility of SFHM facilitates the implementation of a frequency scanning array, which provides a simple and cost-efficient means for fast beam steering. A prototype of the radar system is implemented, and a new signal separation algorithm was derived based on the SFHM theory. Various types of experiments confirm the ability of the radar to accurately provide the respiration and range information of stationary subjects and trajectory information of moving subjects. [ABSTRACT FROM AUTHOR]

A novel 4-D gesture sensing technique using reconfigurable virtual array method with a 60-GHz frequency-modulated continuous wave (FMCW) radar is presented. The 4-D sensing includes the 3-D spatial positioning and the 1-D motion tracking, which combines detection in both spatial and temporal domains. The proposed technique can be used for gesture sensing for both macro gestures such as handwriting letters and numbers, hand drawing different patterns in space and micro gestures such as the fingers’ actions of virtual slider, finger tap, and finger wave. Moreover, this work presents a method to reconfigure the working modes of different transmitting and receiving channels in the multiple input and multiple output (MIMO) architecture, which effectively increases the sensing range of the radar sensor and the signal-to-noise ratio (SNR) of the beat signal. For various gestures at different distances or in different environments, the proposed technique can adaptively achieve the best detection by reconstructing the virtual array of the MIMO radar. A series of experiments are carried out in both microwave anechoic chamber and office environments to validate the proposed technique. The experimental results show that the proposed technique performs well in sensing a variety of both macro gestures andmillimeter-level micro gestures. Compared with the conventional MIMO method, the proposed technique increases the sensing range by 3.5 times, and the SNR is also greatly improved by 12 dB when the radar performs gesture sensing at the distance of 0.65 m. [ABSTRACT FROM AUTHOR]

The article proposes a method of estimating the dielectric constant or propagation velocity of a cylindrical object. The method is simple but robust, completely noninvasive, and suitable for in situ use. The method employs a set of transmission measurements, which record travel times through the object with various path lengths. The shape of the arrival time curve is evaluated and the dielectric constant that best describes the curve shape is obtained as the estimate. The measurement configuration can be seen similar to that of common shot, common midpoint (CMP), or multioffset measurement in ground-penetrating radar (GPR) measurements. The proposed method was demonstrated using synthetic data and in laboratory experiments using a tree log and cemented sand samples with various water contents. The results indicated that the dielectric constant was reasonably estimated by the proposed technique, with an estimation error at least within 10% for the experiments discussed in this article. [ABSTRACT FROM AUTHOR]

With the rapid increase of the number of autonomous driving vehicles, more and more radars working on a similar frequency band are equipped on vehicles, which incurs risks of automotive radar interference. Therefore, a precise interference recognition method is becoming a compelling task. In this article, a novel interference recognition network, called IRNet, is proposed to recognize eight types of interference signals that include mutual interference, unintended interference, and adverse intended interference. First, autocorrelation features of interference signals are obtained via calculating their autocorrelation functions (ACFs) and converted as two-dimensional feature images. Next, these images are employed as inputs of the IRNet that owns significant representation power and adaptive feature selection ability. Finally, the prediction types of interference will be output via the IRNet directly. The robustness of autocorrelation features is verified via simulations. The simulation results show that the proposed method can achieve 90.85% overall recognition accuracy when the jamming-to-noise ratio (JNR) is −14 dB and nearly 100% when JNR $> -8$ dB. Compared with six state-of-the-art methods, the IRNet achieves much better recognition performance, especially under lower JNR conditions with relatively lower and acceptable computational complexity. Results on measured signals also verify the powerful generalization ability of the proposed method. [ABSTRACT FROM AUTHOR]

The frequency scaling algorithm (FSA) is a popular imaging algorithm for dechirped SAR data. To obtain a large azimuth detection area, the miniature millimeter-wave (mmW) linear-frequency-modulated continuous-wave (LFMCW) surveillance radar requires a wider azimuth beamwidth, which leads to additional range frequency aliasing in FSA. Because of the adoption of the dechirp-on-receive technique, the sampling frequency is much smaller than the range bandwidth during near-field imaging, which further aggravates the aliasing effects. The target cannot be well focused, and it makes the weak targets submerged in the background. To acquire high-quality SAR images, an improved FSA using the local stretch operation is proposed. The aliasing bandwidth properties introduced by the FS operation and the desired objective range cell migration (RCM) factor are used in this proposed local-stretch FSA (LSFSA). The initial RCM factor is adjusted by the stretch operation to eliminate the frequency aliasing to a certain level without increasing the computing load. The LSFSA is suitable for solving the problem of range frequency aliasing in near-field side-looking SAR and high squint SAR with wide azimuth beamwidth. The proposed method is validated using reasonable simulations and convincing experiments. [ABSTRACT FROM AUTHOR]

A collocated phased-subarray multiple-input and multiple-output (MIMO) radar system that reduces the number of MIMO channels to implement a large antenna array is proposed. Both the transmitter (TX) and receiver (RX) arrays are divided into phased subarrays, which consist of several RF beamforming antenna elements. Each phased subarray is exploited as an MIMO channel. To estimate the angular information of targets, a hybrid beamforming technique that incorporates RF beamforming of the phased subarrays and digital beamforming of the MIMO virtual array is used. Antenna configurations of the phased-subarray MIMO radar and the corresponding virtual array are also presented. A space between the TX phased subarrays larger than one TX subarray aperture is introduced to facilitate the larger antenna aperture. Because this involves unwanted overall grating lobes, a grating lobe cancellation method is proposed using sum and difference RF subarray beams. This provides a higher angular resolution with the same number of antenna elements. The proposed phased-subarray MIMO radar concept with the corresponding grating lobe cancellation method is demonstrated by implementing a 60-GHz 16-element phased-subarray 2 ${\times }$ 2 MIMO frequency-modulated continuous-wave (FMCW) radar system. [ABSTRACT FROM AUTHOR]

In continuous-wave (CW) radar systems, such as frequency-modulated (FMCW), frequency-stepped (FSCW), or orthogonal frequency-division multiplexing (OFDM) radar systems, the range and velocity uncertainty are significantly impaired by phase noise decorrelation. Therefore, radar designers require accurate knowledge of their synthesizers’ phase noise profiles to assess and predict radar performance. However, commercial phase noise analyzers cannot determine phase noise during modulation, and this may differ notably from phase noise in the pure CW mode. Recent methods for FMCW phase noise analysis usually require comprehensive ${a}$ priori knowledge of modulation parameter and are prone to systematic deviations. To overcome these issues, we propose a new approach based on differential analysis of subsequent time-domain measurements. This method retains, statistical phase noise information while reducing systematic influences. For the first time, less ${a}$ priori signal knowledge is required, and the method works for nearly any kind of broadband signal modulation. The concept requires only a digitizer (e.g., an oscilloscope) and some digital signal processing. The proposed method is first experimentally tested with different phase-locked-loop (PLL)-based synthesizer phase noise profiles. The obtained phase noise profiles agree perfectly with the results of an established measurement system. After this proof of basic functionality, the unique phase noise analysis capability for BB modulated signals is demonstrated with PLL-generated FMCW signals. The results reveal a significant phase noise difference between the different setups and clearly show the capability and benefit of the novel phase noise spectral density measurement concept. [ABSTRACT FROM AUTHOR]

Radar offers a promising modality for enabling gesture recognition, which is a simple and intuitive alternative to click and touch-based human–computer interface. In this article, we propose a spiking neural network (SNN)-based hand gesture recognition with frequency-modulated continuous-wave 60-GHz radar. As preprocessing, the 2-D fast Fourier transform (FFT) is performed across fast time and slow time to generate a video of range–Doppler maps, which are then processed to generate range spectrograms, Doppler spectrograms, and angle spectrograms. The spike trains are fed into an SNN to classify the gesture that has been performed. We demonstrate that with few neurons, SNNs can achieve recognition accuracies close to 99.50% comparable to their deep learning counterparts for eight dynamic gestures. Moreover, the proposed model size is 75 kB, which is substantially smaller compared to the state-of-the-art models making it memory efficient. We also demonstrate using tSNE plots that SNNs can operate with lower embedding dimensions, implying that we can realize SNN with a small compute and memory footprint. [ABSTRACT FROM AUTHOR]

A novel type of photonic background-free multiband arbitrarily phase-coded microwave signal generator with power fading elimination capability is reported. An $x$ -polarized phase modulated optical signal and a $y$ -polarized radio frequency (RF) modulated harmonic single-sideband (HSSB) optical signal are produced based on a dual-polarization quadrature phase shift-keying modulator (DP-QPSKM). After polarization modulation to intensity modulation conversion, a microwave signal with arbitrarily phase encoding in multiple frequency bands is generated. Benefiting from the phase modulation state of the driven electrical coded signal, the generated arbitrarily phase-coded signal has no baseband components. Moreover, the equivalent HSSB modulation ensures the system can realize antidispersion transmission of one-to-multi base stations (BSs). The main distinct highlights of our generator are multifunction. The proposed single-modulator-based photonic scheme can achieve phase encoding in arbitrary format over multiple frequency bands and transmit over long-distance single-mode fiber with the elimination of power fading simultaneously. This work is pretty promising in multiband radar systems for one-to-multi BSs transmission and can increase the detection range, range resolution, Doppler tolerance, and sensitivity of objective recognition of radars. [ABSTRACT FROM AUTHOR]

For highly automated driving functions, up to ten radar sensors must be installed without affecting the vehicle design. This is only possible if they are placed behind painted bumpers. In order to understand the effects of automotive coatings on radar, it is crucial to determine the relative permittivity of each coating layer. A holistic approach to achieve high precision when determining the relative permittivities of multilayer automotive coatings for radars operating at 76–77 GHz is presented. The method is applied to two different types of measurement setups utilizing a vector network analyzer (VNA) with corrugated horn antennas and an all-in-one quasi-optical free-space measurement solution. [ABSTRACT FROM AUTHOR]

General theory of holographic inversion with linear frequency modulation (GHI-LFM) has been proposed recently, providing the framework for further advances in the holographic methods for image reconstruction with millimeter-wave linear frequency modulation (LFM) radar. Here, accelerated holographic imaging (AHI)-LFM, an AHI method for LFM radar that exploits range stacking, is proposed. The method is developed and validated for the purpose of whole-body security screening. The image quality and the computational efficiency are compared with the original GHI-LFM algorithm. It is demonstrated that the AHI-LFM algorithm improves the reconstruction speed by at least an order of magnitude while preserving the same image quality for the image sizes arising in practical whole-body security screening. [ABSTRACT FROM AUTHOR]

This article presents a novel monopulse radar that combines high-sensitivity continuous-wave (CW) and self-injection-locking (SIL) receivers to detect and localize the movements in a human body. The proposed radar utilizes a CW sum pattern and an SIL difference pattern to process the echo signal from the target, so it can produce a monopulse ratio to estimate the angle of arrival (AoA) of the echo signal. With this capability, the radar can localize the movements on the target’s chest that are caused by vital signs such as respiration and heartbeat for posture classification. In addition, the radar can be used in a fall alarm as it can detect a change of posture during a fall. As a proof of concept, a 2.4-GHz prototype radar was experimentally implemented to validate the robustness of detecting falls regardless of their direction. [ABSTRACT FROM AUTHOR]

A novel millimeter-Wave (mm-Wave) joint radar and communication (JRC) system based on photonic spectrum-spreading phase-coding is proposed. The key to the proposed system is the convergence of photonic microwave phase-coding and spectrum-spreading multiplexing techniques. Phase-coding enables the generation of wideband mm-Wave JRC signal, leading to both high range resolution (< 3.5 cm) for radar detection and high capacity (>1 Gb/s) for wireless communication. The spectrum-spreading multiplexing orthogonalizes the radar signal and communication data, highly reducing mutual interferences. In addition, the spectrum-spreading multiplexing is able to improve both peak sidelobe ratio (PSR) for radar and anti-jamming/anti-noise performance for communication. In the proof-of-concept experiments, a JRC phase-coding signal at 35 GHz is generated. For a 5-Gb/s coding rate, the signal-to-noise ratio (SNR) margin is improved by around 13.8 dB for wireless communication below the pre-forward error correction (FEC) limit, while the PSR reaches ~12 dB for radar. Moreover, the impact of spreading gain on the communication capacity has been discussed, revealing that an optimized spreading gain should be set to balance the radar and communication performances. [ABSTRACT FROM AUTHOR]

In this work, we derive the exact response of an interferometric correlation radar to an arbitrary scene containing $N$ independent point scatterers. The response of an interferometric radar to multiple targets can be complicated by the nonlinear processing, which generates intermodulation responses in addition to the desired fundamental frequency responses. An accurate signal model is critical for predicting and mitigating these intermodulation products and allows for model-based parameter estimation methods to be used to estimate target angular velocity. We derive a general response to an arbitrary number of independent targets and validate both the exact model and a simpler approximate model via simulation and experimental measurement with a 38-GHz continuous-wave interferometric radar. The experiment contains two targets traveling perpendicular to the radar’s line-of-sight on linear stages at speeds of 0.36 and 0.5 m/s. We use an error metric to describe the similarity between the measured or simulated time–frequency response and the time–frequency response of a signal generated using the frequency estimates of either the exact or approximate models and show that in regimes where the small-angle approximation holds, both models provide an accurate representation of the measured or simulated interferometric response, demonstrating the feasibility of these models. [ABSTRACT FROM AUTHOR]

A high-resolution vector-sum phase shifter fabricated using a 28 nm CMOS was developed for a 79 GHz imaging radar. The phase shifter incorporates a process and temperature (P/T) stable in-phase (I)/quadrature-phase (Q) signal generator with a robust matching network and highly linear variable gain amplifiers (VGAs) with a crossing metal-line layout. These techniques contribute to 0.5° phase-setting resolution and a 0.9° root-mean-square (rms) phase error with no calibration process. The developed phase shifters were applied to a 79 GHz imaging radar prototype that consists of eight-channel transmitters and eight-channel receivers. The measurement results show that our prototype can recognize human posture, recognize multiple people, and monitor vital signs. [ABSTRACT FROM AUTHOR]

For noncontact vital sign monitoring by using a continuous-wave (CW) radar, the quadrature cosine transform (QCT) with varying window length (VWL) technique is proposed in this article for the first time. The novel algorithm can directly yield the vibration frequency of the radar’s output IQ signals with multiple advantages, including the elimination of dc offset calibration and mitigation of nonlinear interferences caused by harmonic and intermodulation terms, and there is a 50% reduction in frequency resolution of the conventional Fourier transform (FT) that is commonly utilized in existing articles. Thus, it can strike a balance between accuracy and computational efficiency with a short window length. The excellent performance was demonstrated by both theoretical predictions and simulation results. Experiments involving a participant seated 1 m away from the 2.4-GHz ISM band radar prototype demonstrated that the proposed algorithm measures the respiratory rate variability (RRV) and short-time heart rate (HR) with respective errors of less than 1% and 3%. Moreover, the proposed algorithm was more accurate than conventional methods with various window lengths (3–27 s) in 10-min noncontact experiments to monitor the vital signs of ten participants. [ABSTRACT FROM AUTHOR]

Transient radar method (TRM) is introduced as a novel non-destructive testing (NDT) technique that is capable of analyzing fully blindly and simultaneously the electromagnetic (EM) properties as well as geometric parameters of deep sub-wavelength thin single layer slabs. This study focuses on the minimum detectable layer thickness by means of TRM, which mainly depends on the experimental setup configuration. In this article, the complex permittivity and thickness of three polyvinyl chloride (PVC) sheets are extracted by means of a differential TRM set-up. The thickness of these PVC sheets was 1 mm, $500 ~\mu \text{m}$ , and $300 ~\mu \text{m}$ that corresponded to $\lambda $ /30, $\lambda $ /60, and $\lambda $ /100, respectively ($\lambda $ is the wavelength in free space). The carrier frequency was 10 GHz and the experiments were done in a bistatic radar setup. A differential TRM structure was used in this experiment. Some error sources, such as switch leakage and non-perpendicular illumination as well as systematic errors are considered as well. The experimentally obtained results are as follows: the thickness of these samples were 1033 ± 12, 535 ± 11, and 302 ± $9 ~\mu \text{m}$ with 1.18%, 0.94%, and 2.89% relative error, respectively. Additionally, the complex permittivity of these samples was found as (2.73 ± 0.02)–(0.23 ± 0.01)j, (2.70 ± 0.02)–(0.20 ± 0.02)j, and (2.65 ± 0.02)–(0.37 ± 0.01)j, respectively. This novel technique has the potential for deployment in a wide range of applications ranging from the piping, wind energy industry, and automotive to biotechnology, food industry, clinical monitoring, and pharmacy. [ABSTRACT FROM AUTHOR]

High-performance millimeter-wave (mm-wave) multiple-in-multiple-out (MIMO) radars have been using efficient multiplexing with increasingly complicated radar waveforms, where conventional hardware architectures suffer from inevitably high design complexity and cost. This article presents a new software-defined mm-wave multistatic imaging system which provides great efficiency and flexibility to generate and process complicated radar waveforms. A general system block diagram and its signal model are proposed to use space-time-coded orthogonal frequency-division multiplexing (OFDM) for simultaneous MIMO transmission at the same time and frequency. The space-time coding (STC) is designed based on the Hadamard matrix which allows simple decoupling and decoding for imaging processing. A radar prototype is designed to validate the proposed system architecture, which operates at 83.5 GHz with a frequency bandwidth of 4.8 GHz. The mm-wave front-end consists of a metal-printed 8-by-8 waveguide array with a small element-separation of 9 mm to form 64 virtual channels for three-dimensional imaging. Experimental results show good imaging performance, giving great potential to design future cost-effective high-performance mm-wave imaging with efficient multiplexing. [ABSTRACT FROM AUTHOR]

Aiming at realizing on-chip real-time human activity recognition based on the miniaturized and integrated radar with limited computational resources, hyperdimensional computing (HDC) is a promising method due to its unique advantages including high energy efficiency, excellent robustness, lightweight model, and superfast learning process. This article reports on the first use of HDC in the radar system to recognize human activities. First, we design an image mask method to minimize the impact of interference in original radar micro-Doppler spectrograms and apply a fast envelope extraction method to fully reflect features of different human activities. Subsequently, we select the most applicable representation methods for HDC to encode and recognize these features. To better accelerate the convergence speed, enable subtle adjustments of the HDC model, and improve the recognition accuracy, we propose a new adaptive retraining method, Mask-Retraining. Finally, the accuracy of recognizing six human activities using HDC with Mask-Retraining reaches 92.93%. Experimental results and comparisons between HDC and ten recognition algorithms demonstrate the validity of our methods. In most cases, HDC outperforms other algorithms being compared both in recognition accuracy and computational cost. Especially, HDC becomes the prime and irreplaceable candidate when only small datasets or finite data points are available. [ABSTRACT FROM AUTHOR]

The joint radar-communication (RadCom) concept has been continuously gaining interest due to the possibility of integrating radar sensing and communication functionalities in the same radio frequency hardware platform. Besides a number of challenges in terms of hardware design and signal processing, the choice of suitable modulation schemes plays a significant role in driving the performance of RadCom systems. In this sense, this article presents an overview of state-of-the-art modulation schemes for RadCom systems, namely, chirp sequence, phase-modulated continuous wave, orthogonal frequency-division multiplexing, and orthogonal chirp-division multiplexing. For each of them, a detailed system model is outlined, and parameters for quantifying both radar and communication performances are presented. Finally, a comparative analysis of the aforementioned RadCom modulation schemes is carried out to illustrate the presented discussion. [ABSTRACT FROM AUTHOR]

Automotive radars, along with optical sensors such as cameras or lidars, offer a reliable way of obtaining the 3-D information about the environment. Of particular interest in autonomous driving (AD) is the reliable detection of particularly vulnerable road users (VRUs). Modern radar sensors are able to detect, distinguish, and track targets with high resolution. Relying on that, a backscattering model of complex traffic targets can be generated from the reflected signals of their scattering points (SPs). These models can be employed in the radar channel simulations for verification methods of advanced driver assistance systems. Therefore, in this work, different persons as the most vital VRUs are measured with high radial and high angular resolution. The necessary signal processing steps are explained in detail for the determination of the relevant SPs. Thus, the corresponding radar cross section (RCS) values can be assigned to certain body regions. In addition to real persons, further measurements are compared with a dummy of the corresponding size. Based on the measurement results, not only accurate models of road users can be derived, but also the measurement results can be employed for calculating wave propagation in traffic scenarios. From the measured SPs, the classification of the persons by size and stature is derived. [ABSTRACT FROM AUTHOR]

In this work, a method for directly measuring target velocity in three dimensions using a dual axis correlation interferometric radar is presented. Recent advances have shown that the measurement of a target’s angular velocity is possible by correlating the signals measured at spatially diverse aperture locations. By utilizing multiple orthogonal baselines and using conventional Doppler velocity methods to obtain radial velocity, a full 3-D velocity vector can be obtained using only three receive antennas and a single transmitter, without the need for tracking. A 41.8-GHz dual axis interferometric radar with a ${7.26\lambda }$ antenna baseline is presented along with measurements of a target moving parallel to the plane of the radar array, and of a target moving with components of both radial and tangential velocity. These experiments achieved total velocity root-mean-square errors (RMSEs) of 41.01 mm $\cdot \,\,\text{s}^{-1}$ (10.5%) for a target moving along a plane parallel to the array, and 45.07 mm $\cdot \,\,\text{s}^{-1}$ (13.5%) for a target moving with components of radial and tangential motion relative to the array; estimated trajectory angle RMSEs of 10.42° and 5.11° were achieved for each experiment. [ABSTRACT FROM AUTHOR]

Radar-based near-field 3-D imaging technology has recently attracted increasing attention in the field of security systems. This article presents a novel multiple-input–multiple-output (MIMO) synthetic aperture radar imaging algorithm for security checkpoints attached to a moving walkway. The proposed algorithm is characterized by transmitting-signal multiplexing on the Doppler frequency domain, which allows for a reduced data acquisition time compared with that of conventional time-division multiplexed MIMO systems and therefore achieves the image reconstruction of dangerous objects with smaller motion errors. This algorithm can be applied to 1-D antenna array systems, and image reconstruction is based on a back-projection algorithm with some modifications. The mathematical derivation of the algorithm and its advantages and disadvantages in comparison with those of a conventional system are detailed in this article. Details of numerical simulation of a point target as well as the experimental results of image reconstruction of a pinball and toy gun, using cascaded millimeter-wave sensors, are also presented for verifying the performance of the algorithm. [ABSTRACT FROM AUTHOR]

The article presents a monostatic $D$ -band frequency-modulated continuous-wave (FMCW) radar based on a fully integrated monostatic single-channel silicon-germanium (SiGe) transceiver (TRX) chip. The chip is fabricated in Infineon’s bipolar-complementary metal–oxide–semiconductor (BiCMOS) production technology B11HFC which offers heterojunction bipolar transistors (HBTs) with an $f_{\mathrm {T}}/f_{\mathrm {max}}$ of 250 GHz/370 GHz. The monolithic microwave integrated circuits (MMICs) output signal is coupled by a fully differential substrate integrated waveguide (SIW) based coupling network. The output power at the WR-6.5 antenna flange is more than −10 dBm over a bandwidth of 37.5 GHz. For a sweep within a single-loop phase-locked loop (PLL) circuit from 174.5 to 121.5 GHz, a spatial resolution of almost 3 mm with a metallic plate as the target is achieved. The radar provides a small form factor of $2 \times 4 \times 5$ cm3 and low power consumption of 2.2 W at 5 V. Finally, the capabilities of the sensor for non-destructive testing (NDT) are demonstrated using a millimeter scanner. With radar imaging, it was possible to measure the orientation of the fiber layers up to a depth of 7.03 mm. [ABSTRACT FROM AUTHOR]

In short-range sensing, the frequency-modulated continuous-wave (FMCW) radar is subject to the leakage between the transmitter (Tx) and the receiver (Rx) and the stationary clutter reflections, which are difficult to deal with due to the proximity to the target. The proximity ghost image may not only interfere with the target but also pose limitations on the radar performance, such as the degradation of the signal-to-noise ratio (SNR). This article proposes a novel hybrid analog and digital compensation techniques, which mitigates the leakage and the stationary clutters by compensating with the prestored anti-interference signals in both analog and digital domains at the intermediate-frequency (IF) stage. A novel modulation signal-based synchronization (MBS) technique is developed to align the real-time IF signal with the anti-interference signal during the compensation process. By significantly suppressing both the Tx–Rx leakage and the stationary clutters, the proposed technique greatly improves the signal-to-interference ratio (SIR) of the IF beat signals and makes possible the detection of targets with weak reflections. Moreover, the analog compensation enables the full use of the dynamic range of the analog-to-digital converter (ADC), which will reduce the impact of quantization noise and, thus, improve the SNR. Experiments have been carried out to validate the performance of the proposed technique in leakage compensation, weak target detection, stationary clutter compensation, and gesture sensing. The experimental results show that the SIR and the SNR have been improved by around 38 and 10 dB, respectively. [ABSTRACT FROM AUTHOR]

Automotive radar sensors play a key role in the current development of autonomous driving. Their ability to detect objects even under adverse conditions makes them indispensable for environment-sensing tasks in autonomous vehicles. The thorough and in-place validation of radar sensors demands an integrative test system. Radar target simulators (RTSs) are capable of performing over-the-air validation tests by creating artificial radar echoes that are perceived as targets by the radar under test (RuT). Since the authenticity and credibility of these targets are based on the accuracy with which they are generated, their simulated position must be arbitrarily adjustable. In this article, a new approach to synthesize virtual radar targets at an arbitrary angle of arrival (AoA) is presented. The concept is based on the superposition of the returning signals of two adjacent RTS channels. A theoretical model describing the basic principle and its constraints is developed. Additionally, a measurement campaign is conducted that verifies the practical functionality of the proposed scheme. [ABSTRACT FROM AUTHOR]

Recent advances in radar systems have demonstrated the possibility of noncontact human vital signs detection. Most prior research has focused on vital sign detection with specific subjects’ orientations. So far, very few reported studies have been carried out on vital sign detection in any orientation, which is necessary to be applicable in various scenarios, e.g., assisting in the daily life of elderly persons living alone. To tackle this problem, this article presents a scheme that uses a distributed radar network, which transmits stepped frequency continuous-wave (SFCW) signals, then collecting the vital sign data returned from different directions of the subject and subsequently obtaining the respiratory and heartbeat rates from these collected data. A new respiratory and heartbeat model is proposed here for the theoretical analysis and simulation of vital sign detection for any orientation utilizing a distributed radar network. A modified independent component analysis (ICA) method noted as derivative independent component analysis (DICA) is proposed here to estimate the respiratory and heartbeat rates from multiple channels of the distributed radar network. Use of the ICA method was theoretically validated first to prove that the problem formulation satisfies the three conditions required for its implementation. Vital signs of a stationary subject were detected in simulation and measurement using multiple receiving antennas that are fan-shaped distributed around the subject from different directions. In this scenario, both the heartbeat and respiratory rates can be accurately estimated using the proposed DICA algorithm. Moreover, we also experimentally investigated the performance of the DICA method with different combinations of channels as input signals to the DICA algorithm. Both the simulated and experimental results have demonstrated that, by using a distributed radar network and the DICA method, a successful and accurate respiratory and heartbeat rate detection of a subject regardless of subject’s orientation can be achieved due to the independence of their non-Gaussian sources. [ABSTRACT FROM AUTHOR]

Most conventional vital-sign radars cannot easily detect human vital sign signals under nonperiodic body movement. This article presents a novel frequency-locked loop (FLL) radar that can track the phase changes that are caused by nonperiodic body movement. A gain/phase detector and a cross correlation function (CCF) in the FLL radar greatly reduce the second harmonic, the intermodulation terms between vital sign signals and nonperiodic body movement noise, enhancing both the signal-to-noise ratio and the accuracy of detection of the vital signs. Measurements indicated that the implemented 2.4-GHz FLL radar with a gain/phase detector and CCF can effectively detect the human respiration rate (RR) and heart rate (HR) under nonperiodic body movement. Using a chest belt as the measurement reference, the standard deviation (SD) of RR and HR measurements were 1.27 and 5.69 beats/min, respectively, when the seated subject under test (SUT) swung nonperiodically his upper body. When the SUT walked away from the radar naturally at 2.6 km/h, the implemented FLL radar measured RR and HR with SDs of 2.67 and 8.28 beats/min, respectively. [ABSTRACT FROM AUTHOR]

Millimeter-wave radar interferometry is superior in detecting small displacement motions owing to its short wavelength. However, it is subject to phase ambiguity as the target displacement may often exceed a quarter wavelength. In this article, a modified differentiate and cross-multiply (MDACM) technique is proposed to tackle the phase ambiguity issue for accurate reconstruction of the phase history in millimeter-wave interferometry. In addition, to resolve the imperfections of the interferometric radar system, an MDACM-based integral phase reconstruction approach is presented, which seamlessly integrates alternating current (ac)-coupling-induced distortion correction, $I/Q$ mismatch correction, and direct current (dc) offsets’ calibration. Without causing any phase ambiguity, the proposed technique acts as a black box to take in the raw $I/Q$ signals and correct all the hardware imperfections, and it outputs the desired displacement motions with micrometer accuracy. The simulation results show that the proposed technique can not only linearly recover the displacement motions across a wide range in different noise conditions without any phase ambiguity but also improve the stability by 11 times under ac-coupling-induced distortion. With a custom-designed 120-GHz interferometric radar sensor, experiments were carried out to validate various scenarios including mechanical vibrations and gesture sensing. The experimental results show that the proposed technique can accurately track not only deep subwavelength motion of only $1~\mu \text{m}$ but also multiwavelength displacement of >40 times of the wavelength at 120 GHz. [ABSTRACT FROM AUTHOR]

This article proposes a method to detect vocal signals and the corresponding locations of multiple humans using a multiple-input and multiple-output (MIMO) frequency-modulated continuous-wave (FMCW) radar system. The signals of multiple humans are extracted with digital beamforming by the virtual array generated by MIMO radar processing. To remove body motion artifacts that distort the speech information detected by the radar, a body motion effect cancellation method is proposed. The technique allows recovering vocal signals from detected distorted signals by estimating phase variations due to body motions. A combination of the proposed vocal signal detection algorithm with a human localization one enables to detect speaking humans by means of the MIMO radar. Experiments verify that the proposed method can accurately locate and detect speaking humans based on their vocal vibration signals. [ABSTRACT FROM AUTHOR]

Thermal modeling of different transmission lines (TLs) based on resonant scatterers is presented. The coplanar strip (CPS) and microstrip (MS) TLs are used to model resonators and to introduce the thermal dependence. A reflectometry approach is employed to validate the model by detecting the scatterers’ resonance frequency and comparing it with analytical expressions. The observable shift in the resonance frequency of the scatterers with temperature variations is due to the thermal expansion of metals and temperature dependence of the substrate permittivity. Since all the measurements are done remotely with no direct line of sight, it is shown how such a reflectometry approach can be used for remote temperature sensing using a passive label composed of resonators. Unlike previous works in this domain where the thermal dependence is considered empirically, the introduced model is used to take into account all thermal effects affecting the resonant scatterers allowing to link rigorously the variations of the measured resonance frequency with the temperature without any lookup table. Temperature sensing using very simple TLs based on resonant scatterers was demonstrated in a real environment. A temperature error of less than 3 °C is obtained. Once the temperature has been determined, it is possible to go back to the TL parameters, such as the effective permittivity and the physical length. [ABSTRACT FROM AUTHOR]

In this article, a channel micro-Doppler ($\mu \text{D}$) signatures’ quantitative evaluation method for multiple-input–multiple-output (MIMO) radar system, named relative signal–noise ratio in the time–frequency domain and denoted as RSNRtf, is introduced. The impact on RSNRtf by some key dominant factors in real practical and diverse detection environments was theoretically analyzed first. Then, this proposed method is exploited to conduct effective and superior channel selection for improved human activity classification at random human target positions. Based on numerous MIMO stepped-frequency continuous wave (SFCW) radar data from eight subjects with seven activities at nine positions in a through-wall within a view angle of ±20° and up to 6-m distance away, the influence of various primary factors on the proposed method is investigated. Investigative experiments showed that the proposed method has a wide range of applicability and a high interference tolerance even for different detection distances, angles, activities, and subjects. Classification experimental results based on typical classifiers also showed that the proposed method could effectively improve human activity classification. Moreover, we can claim that the proposed method can achieve a higher outstanding performance in the channel $\mu \text{D}$ capacity evaluation and enhanced classification for the MIMO-radar-based human activity classification in free space or with a wider detection field with large angle range. [ABSTRACT FROM AUTHOR]

Simultaneous multitarget vital signs measurement has become a hot issue for noncontact vital signs perception. However, there is still challenge in the multitarget heartbeat measurement due to the weakness of heartbeat signal and interference from complex environment. In this article, a new multiple-input–multiple-output (MIMO) continuous-wave (CW) radar system equipped with 2-D digital beamforming (DBF) is presented to measure the respiration and heartbeat of multiple human subjects at unknown positions simultaneously. Through 2-D beam scanning of the whole scene, a 2-D radar image is generated. From the image, the chest motion of multiple targets is accurately located. Then, the vital signs of targets are obtained through forming individual beams focusing on the chests of targets. Moreover, the low intermediate frequency (low-IF) architecture is adopted to minimize the impact of flicker noise in low-frequency amplifier stages. The experimental results demonstrate that the proposed MIMO 2-D imaging radar system can locate chest areas of multiple targets, suppress the clutters, and make vital signs measurement, heartbeat measurement in particular, more robust compared with single-input–multiple-output (SIMO) radar system in complex environment. [ABSTRACT FROM AUTHOR]

In a conventional frequency-modulated continuous-wave (FMCW) radar, the target distance is estimated by the beat frequency, which is obtained from dechirping the received signal with the transmitted one. The challenge to achieve fine-range sensing is limited by the inaccuracy of beat frequency caused by the nonlinearity of sweeping chirps. In this work, instead of determining the accurate beat frequency, a novel dual-phase-term tracking (DPTT) method is introduced for high-accuracy range sensing even in a severe nonlinear situation. By tracking the phase of the beat signal and observing the phase difference over the up or down period of a triangular chirp, two distinct featured phase terms $\phi _{o}$ and $\Phi _{B}$ are extracted. The phase $\phi _{o}$ represents the carrier round-trip phase delay at $f_{\mathrm {o}}$. Although $\phi _{o}$ is free of the nonlinear chirping effect, the range estimation based on $\phi _{o}$ suffers from the range ambiguity problem. The phase term $\Phi _{B}$ represents the phase change over the first half chirp period and it is monotonically increased across the range ambiguity zones of $\phi _{o}$. Therefore, by combining these phase terms to determine the target range, both the frequency chirping nonlinearity and the range ambiguity can be effectively eliminated such that the range accuracy of tens of micrometers can be achieved even with an extremely narrow chirp bandwidth. To validate the proposed method, a 24-GHz FMCW radar with a 400-MHz chirp bandwidth and a 10-ms chirp period has been designed and implemented for demonstration. At a distance of 0.6 m, the measured range accuracy is $40.1~\mu \text{m}$ for the weak nonlinearity factor of 0.3%. For the severe nonlinear chirp case with a 25.3% nonlinearity factor, the range accuracy of $137.5~\mu \text{m}$ is also successfully obtained, validating the robustness of this proposed DPTT method. [ABSTRACT FROM AUTHOR]

We propose a millimeter-wave (mmWave) sensor to monitor gases and aerosols based on time-of-flight (ToF), thus, on the real refractive index. It utilizes an ultrawideband frequency-modulated continuous-wave (FMCW) radar operating from 72 to 92 GHz at a sampling rate of 500 Hz. Also, we introduce a model for simulation of the refractive index of arbitrary gases at mmWave frequencies using molecular spectroscopic data. Simulations then allow the identification of the respective gas under test. We characterized the performance of the sensor regarding the refractive index within various experiments. The precision is 0.027 ppm, and the 20-h long-term stability is better than 0.2 ppm. The linearity is at least 1.5 ppm. Due to sophisticated temperature compensation, the temperature drift is less than 10 ppm for 30 K. Since the sensor is accurate, precise, and robust, it is perfect for in-process real-time monitoring and classification of gases or aerosols in the industry. [ABSTRACT FROM AUTHOR]

A novel matrix-pencil (MP)-based interference mitigation approach for frequency-modulated continuous-wave (FMCW) radars is proposed in this article. The interference-contaminated segment of the beat signal is first cut out, and then, the signal samples in the cutout region are reconstructed by modeling the beat signal as a sum of complex exponentials and using the MP method to estimate their parameters. The efficiency of the proposed approach for the interference with different parameters (i.e., interference duration, signal-to-noise ratio (SNR), and different target scenarios) is investigated by means of numerical simulations. The proposed interference mitigation approach is intensively verified on experimental data. Comparisons of the proposed approach with the zeroing and other beat-frequency interpolation techniques are presented. The results indicate the broad applicability and superiority of the proposed approach, especially in low SNR and long interference duration situations. [ABSTRACT FROM AUTHOR]

This article presents a novel spoofing device capable of injecting false target information into a frequency-modulated continuous-wave (FMCW) radar. The spoofing device uses a radio frequency (RF) single-sideband (SSB) mixer to introduce a frequency shift to the incoming RF signal transmitted by the victim radar and retransmits the modulated RF signal. The modulated RF signal resembles a false target. Upon down-conversion on the receiver chain of the victim radar, the modulated RF signal creates an illusion of a real target in the radar signal processing system. The frequency shift can be adjusted to vary the range of the spoofed target. The theory of the spoofing mechanism was developed, and a 5.8 GHz prototype was built for experimental validation. Experimental results demonstrate the ability of the proposed spoofing device to inject a false target at any arbitrary range. A hybrid-chirp FMCW approach was proposed and verified as a countermeasure to distinguish a real target from a spoofed target to mitigate the RF-spoofing attack. [ABSTRACT FROM AUTHOR]

As the electromagnetic environment in battlefields is more and more complex, automatic modulation recognition for radar signals is becoming vital and challenging. Traditional methods are more likely to cause lower recognition accuracy with higher computational complexity in low signal-to-noise ratio (SNR). Feature redundancy especially for handcrafted features is one of the shortcomings of deep-learning-based methods. In this article, a novel end-to-end sequence-based network that consists of a shallow convolutional neural network, a bidirectional long short-term memory (Bi-LSTM) network strengthening with a self-attention mechanism, and a dense neural network is constructed to recognize eight kinds of intrapulse modulations of radar signals. The autocorrelation functions of received radar signals are first calculated as autocorrelation features. Then, these features are employed as inputs of the proposed network which owns significant sequence processing advantages and adaptive selection ability of features. Finally, the proposed network outputs prediction modulations directly. The simulation results verify the robustness and effectiveness of autocorrelation features. And the proposed network achieves about 61.25% accuracy at −20 dB and more than 95% accuracy at −10 dB. Compared with four state-of-the-art networks, the proposed network has better recognition performance especially at low SNRs with much lower computational complexity. Results on measured signals also demonstrate that the proposed network outperforms these four networks. [ABSTRACT FROM AUTHOR]

Radar imaging using the synthetic aperture radar (SAR) principle is a common method to obtain information about e.g., the surface of a target. However, most image formation algorithms for such systems assume (quasi-)static measurements. This may lead to errors in the processed images if the sensor is moving during the measurement process. This is especially the case for frequency-modulated continuous-wave (FMCW)-based sensors since the signal duration is longer than in a pulsed system and the achievable bandwidth is much larger and introduces additional challenges. Motion compensation in the context of radar imaging is usually related to the correction of deviations from an ideal trajectory. In contrast, this article presents a method to take the sensor movement during a single FMCW ramp into account and therefore addresses the effects caused by a continuous path during the transmit/receive process. Hence, faster movement can be achieved during the scanning of the synthetic aperture without being bound by stop-and-go approximations. In addition, it will be shown that the algorithm is suitable to reduce systematic errors due to aliasing caused by spatial sampling below the Nyquist rate. For this purpose, this article presents simulations and measurement results, obtained by an ultrawideband $D$ -band FMCW radar operating between 122 and 170 GHz. [ABSTRACT FROM AUTHOR]

We report on the realization of a multichannel imaging radar that achieves uniform 2-D cross-range resolution by means of a linear array of a special form of leaky-wave antennas. The presented aperture concept enables a tradeoff between the available range resolution and a reduction in the number of channels required for a given angular resolution. The antenna front end is integrated within a multichannel radar based on stepped-carrier orthogonal frequency-division modulation, and the advantages and challenges specific to this combination are analyzed with respect to signal processing and a newly developed calibration routine. The system concept is fully implemented and verified in the form of a mobile demonstrator capable of soft real-time 3-D processing. By combining radio frequency (RF) components operating in the $W$ -band (85–105 GHz) with the presented aperture, a 3-D resolution of less than ${1.5}^\circ \times {1.5}^\circ \times $ 15 cm is demonstrated using only eight transmitters and eight receivers. [ABSTRACT FROM AUTHOR]