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Detecting respiration and heartbeat information from human chest movement is crucial for non‐contact vital sign detection. Due to the small frequency difference between respiration and heartbeat signals and the relatively low amplitude of the heartbeat signal, it is challenging to separate and extract them completely. This letter proposes a successive variational mode extraction method based on spectrum trend for the extraction of respiration and heartbeat signals. The proposed method adaptively determines the initial centre frequency and extraction order of the desired signal modes by analyzing the spectrum trend of the signal to be decomposed. Additionally, a recursive framework is introduced to sequentially extract the desired signal modes. Both simulation and practical experiment results show that the method is effective in extracting respiration and heartbeat signals, significantly improving the accuracy of estimating respiration and heartbeat frequencies. [ABSTRACT FROM AUTHOR]

In this letter, a novel algorithm is proposed to design symbol‐level waveform for dual‐functional radar‐communication (DFRC) systems with low range sidelobe. Different from current schemes design waveform at the block level, a phase response constraint is introduced at the symbol level to provide an additional degree of freedom to decrease the range sidelobe in the pulse compression procedure, which is highly desired in radar systems. In particular, the phase response at the target direction is constrained to be similar to the given reference phase, and the matching error between the designed beampattern and the desired one is minimized subject to the constant modulus constraint. Furthermore, to guarantee the quality of service for communication, constructive interference is exploited at the symbol level for each communication user. An alternating direction method of multipliers algorithm is also proposed to solve the resulting nonconvex optimization problem with tractable subproblems solved sufficiently by the manifold optimization and standard quadratic problem. Numerical simulation results demonstrate the performance of the proposed method. [ABSTRACT FROM AUTHOR]

The type parameter helps in scattering mechanism analysis and scattering centre identification. However, current approximate solution methods based on spectral estimation are noise‐sensitive and exhibit low accuracy. In this letter, a high‐precision approach for the type parameter based on the alternating direction method of multipliers (ADMM) is proposed. Logarithmic transformation is used to separate the type parameter and the amplitude from the coupling term, and initially obtain the closed‐form solution of the type parameter. Then, the regularization term of l2‐norm is used for denoising. Finally, a joint optimization model based on ADMM is constructed to effectively estimate the type parameter. Simulation results confirm the high accuracy of the proposed approach. [ABSTRACT FROM AUTHOR]

Two‐dimensional (2D) direction‐of‐arrival (DOA) estimation is crucial in array signal processing. Compressed sensing (CS) provides a superior alternative to spatial spectrum estimation algorithms by enabling 2D DOA estimation of correlated sources from single snapshot data. However, the grid mismatch effect inherent in grid‐based CS algorithms impacts estimation accuracy. Despite recent advancements, the state‐of‐the‐art gridless CS algorithm, decoupled atomic norm minimization, is limited to specific 2D array geometries, such as uniform rectangular arrays. This letter presents an efficient gridless 2D DOA estimation algorithm for generalized rectangular arrays, including both uniform and sparse arrays. The proposed algorithm achieves high accuracy through a novel approach called generalized matrix‐form atomic norm minimization and provides a fast solution using the alternating direction method of multipliers. Validation through computer simulations and practical experiments underscores its efficacy. [ABSTRACT FROM AUTHOR]

In scenarios with constrained physical aperture sizes, aiming to enhance the resolution and accuracy of Direction of Arrival (DOA) estimation, this paper proposes a novel approach that integrates a moving synthetic virtual array with Sparse Bayesian Learning (SBL) for DOA estimation. Initially, a virtual array is constructed based on the motion characteristics of the target. Subsequently, the SBL method is employed to estimate the DOA of the target. Simulation experiments validate the effectiveness of this approach, demonstrating comparable DOA estimation performance to synthetic aperture methods with larger aperture sizes, even in situations with limited aperture expansion. Furthermore, under constant virtual aperture expansion, this method surpasses non‐SBL methods regarding DOA resolution. We explore the construction of a virtual array through the relative displacement induced by target motion. It further investigates the performance improvement of Direction of Arrival (DOA) estimation resolution using sparse Bayesian learning within the context of a virtual array. [ABSTRACT FROM AUTHOR]

Effective compression of point clouds is essential for implementing virtual and mixed reality applications, which require encoding millions or even tens of millions of points. This paper offers a new geometric compression for point clouds based on sparse cascaded residuals and sparse attention. A sparse cascaded residual module is posited to connect multiple residual modules through shortcuts, thereby augmenting the network's learning capacity and compression efficacy. The authors developed a sparse attention module to acquire global features by computing interdependencies among points, enhancing compression performance to a greater extent. Trade‐off parameters are employed to optimize the rate and distortion. The authors' method outperforms the state‐of‐the‐art open‐source method regarding rate‐distortion on the ShapeNet, ModelNet, and Microsoft Voxelized Upper Bodies datasets, with average bjøntegaard‐delta (BD)‐rate gains of −14.44% and −15.38%. [ABSTRACT FROM AUTHOR]

Targets with rotating components generate micro‐motion (MM) modulation effect in addition to the main body. Extracting MM parameters is challenging due to interference from the target's main body, necessitating the separation of modulation signals. This letter proposes a robust complex local mean decomposition (RCLMD) method with self‐adaptive sifting stopping, aiming at the problem of component redundancy due to multiple iterations during break and the loss of modulation components during the separation process. The proposed method sets the objective function and self‐adaptive stopping criterion, combined with the modulation signal characteristics, enhancing the accuracy and efficiency of MM component extraction. Simulation experiments show that compared with the complex local mean decomposition method, the complex empirical mode decomposition method, and its improved method, the RCLMD method can achieve the highest decomposition effect of 96.57%, and the separation time consumed has a significant advantage over the above methods, performance is less fluctuating by the change of signal‐to‐noise ratio with good robustness. The measured data in real scenarios also verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Passive localization using time difference of arrival (TDOA) is one of the common methods for radiated source target localization, and its localization performance depends on the accuracy of TDOA estimation. In many localization scenarios, the signals of target are intricate and often contain multiple ones, so how to effectively extract the time difference parameters from them becomes a difficult problem. This letter proposes a signal‐level fusion method for TDOA estimation to address this problem. At the receiver terminal, multiple signals are fused to obtain their cross‐ambiguity function, so as to estimate the TDOA value for target localization. The effect of fused signals on the accuracy of TDOA estimation is analyzed and the concept of frequency depression is proposed. Simulation experiments verify that the estimation method with signal‐level fusion gets a higher accuracy of the TDOA value and a smaller position error in target localization. [ABSTRACT FROM AUTHOR]

This letter presents a method to optimize the estimation of direction of arrival (DOA) using the uniform linear array (ULA) with one‐bit signals in the presence of non‐uniform noise. With the Toeplitz properties and the rank characteristics of the signal subspace matrix formed by the ULA, the alternating minimization (AM) method is employed to optimize the estimation problem. To address this challenge further, we utilize the singular value thresholding (SVT) method and the approximate projection method. The angle deviations caused by non‐uniform noise can be effectively corrected and a significant improvement in the estimation performance can be achieved. The feasibility and effectiveness of the proposed method are demonstrated through simulation results. [ABSTRACT FROM AUTHOR]

Although radar sensors have been known for their robustness in challenging environmental conditions, they face difficulties in distinguishing between upper structure (US), such as road signs, traffic lights, overpasses, and pedestrian bridges, and forward vehicle (FV). This misclassification can lead to false alarms and unwanted braking events. In this paper, the authors propose a method distinguishing between US and FV at different distances based on change in radar cross section (RCS). The study collects real‐world RCS data from various objects identified as US and FV during road driving scenarios. [ABSTRACT FROM AUTHOR]

Hand gesture recognition based on micro‐Doppler (MD) radar has garnered considerable attention from researchers as a potential method for human–computer interaction (HCI). However, two significant challenges, that is, obvious differences in MD map size and lots of redundant information contained in the MD maps, are encountered. Here, a multi‐scale graph‐based hand gesture recognition framework is proposed. First, a MD graph representation method is developed, which is adapted to arbitrary‐sized frames and enables to map the key features in a sparse manner. Then, the multi‐scale information from MD graph is fully extracted for hand gesture recognition. Experimental results show that the proposed framework achieves a state‐of‐the‐art accuracy of 96.73% on the four‐class radar hand gesture dataset, while reducing up to 99% of the redundant information in the MD maps. This framework requires only a little amount of memory storage with good hand gesture recognition capability, demonstrating its high potential in the HCI field. [ABSTRACT FROM AUTHOR]

Specifying parameters of high‐speed targets as range and velocity in radar systems operating with phase‐modulated signals is a problematic process because of the serious effect of high Doppler frequency on these types of waveforms. In the existence of a high‐speed target, its Doppler frequency will be very high such that it totally changes the phase sequence of the received signal. As a result, the matched filter output will be distorted. Therefore, estimating target parameters will be impossible. In this letter, a new method is proposed for detecting and estimating velocity of high speed targets using phase‐modulated signals. The suggested technique methodology depends on compensating the target high‐Doppler frequency for signal recovery using a customized waveform shape. Moreover, the Doppler frequency value is estimated without ambiguity from one pulse, and without the need for a range‐Doppler module. As such, the implementation of the proposed method is simple and inexpensive. The performance evaluation of the new method shows its superiority in compensation and estimation compared to other techniques when examined under higher Doppler frequency and noise compared to the conventional radar.The paper presents a new method for detecting high‐speed targets, and super‐sonic vehicles using phase‐modulated waveforms. The proposed technique depends on a customized waveform shape for compensating the target high‐Doppler frequency when received in the Doppler compensation module. Moreover, the Doppler frequency information is estimated from one pulse for determining the target velocity in the Doppler estimation module. [ABSTRACT FROM AUTHOR]

This letter proposes a data‐driven method to simulate random sea clutter amplitude sequence with distribution and correlation characteristics directly inherited from the measured clutter. First, a generation model is developed to simulate clutter amplitude sequence with desired distribution. By multiplying the measured amplitudes with random disturbance coefficients, the model introduces sample diversity between the simulated and measured sequences. Meanwhile, to quantitatively control the difference of the distribution tails between the simulated and measured sequences (i.e. to ensure their distributions are similar), the threshold error metric is introduced to set the disturbance variance. Second, a scheme combining the generation model with the correlation transfer technique is presented, which allows to simulate clutter amplitude sequence with both desired distribution and correlation for engineering purpose. Experiments based on different measured clutter sets indicate the proposed method works very well. [ABSTRACT FROM AUTHOR]

Due to the aircraft targets' uncooperative character, acquiring the complete scattering characteristics of enemy aircraft is challenging. An effective reconstruction method of target scattering centres based on characteristics analysis of inverse synthetic aperture radar (ISAR) images is proposed in this letter. First, a positive definite manifold characterizing ISAR images of different attitudes is constructed. Then, Kullback–Leibler divergence is used as a measure of the variability between ISAR images. Finally, an ISAR image interpolation method based on the characteristics analysis of ISAR images is proposed to obtain the scattering characteristics with more attitudes. Furthermore, simulation results confirm that the proposed method is effective. [ABSTRACT FROM AUTHOR]

In this letter, a computationally efficient multiple signal classification (MUSIC)‐based evolutionary algorithm for angle estimation of bistatic multiple‐input multiple‐output (MIMO) radar is proposed. The existing MUSIC algorithms require a computationally cumbersome two‐dimensional (2D) peak searching and the performance is highly related to the grid that set, which leads to a conflict between the computational efficiency and estimation performance. To address this difficulty, a multimodal quantum‐inspired salp swarm algorithm, integrating kmeans clustering technique, is proposed to substitute the 2D peak searching to obtain multiple maxima of the MUSIC algorithm. The resulting computationally efficient algorithm obviously reduces the computational complexity of the MUSIC algorithm, avoids grid errors, and further exploits the potential of the MUSIC algorithm. Numerical simulations in various scenarios are carried out to verify the superiority of the method. [ABSTRACT FROM AUTHOR]

This letter proposes an efficient tensor model for Direction of Departure (DOD) and Direction of Arrival (DOA) estimation based on bistatic nested Multiple‐Input Multiple‐Output (MIMO) radar. Tensor offers a robust solution in characterizing multi‐dimensional data structures, ensuring data integrity, and has demonstrated remarkable effectiveness in the realm of multi‐dimensional parameter estimation. However, the complexity of traditional methods for constructing tensors is a major obstacle to practical applications. In response, this research introduces a novel approach that utilizes an iterative two‐dimensional Toeplitz matrix reconstruction method to rapidly derive expanded virtual covariance matrices prior to tensor construction. This streamlines the algorithm and improves efficiency. Numerical simulations have verified the superiority of this algorithm. [ABSTRACT FROM AUTHOR]

The automatic modulation recognition (AMR) of radar signals has become a popular research topic in recent years. However, most algorithms focus on the type of signal modulation and lack further understanding of the signal. To address this gap, a network architecture for multi‐tasking intra‐pulse description words (MIDW‐Net) is proposed herein. In this framework, the denoising algorithm employs a convolutional denoising autoencoder, which is an effective method for suppressing noise interference and preserving signal information. The multiscale feature‐extraction capability of a feature pyramid network (FPN) is utilized to expand the perceptual domain without losing the high‐frequency features of the image. Finally, AMR and modulation parameter estimation are accomplished via multitask learning. Experiments performed on simulated radar signals using four intra‐pulse descriptors verified the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Radar forward‐looking imaging is gaining significance in various applications like battlefield reconnaissance, target surveillance, and precision guidance. Although synthetic aperture radar techniques provide high azimuth resolution but faced limitations in forward‐looking area due to the poor Doppler resolution and the "left‐right" ambiguity problem. Recently, generative adversarial networks have been extensively used for image motion blur removal. This letter proposes an end‐to‐end forward‐looking image enhancing network using generative adversarial network to produce high‐resolution images, improving the efficiency, and quality of imaging. Compared to conventional methods such as the deconvolution‐based methods, this algorithm eliminates the need for design and iterative processes of the observation matrix. Simulated and real radar data validate that this approach offers robust recovery and better performance. [ABSTRACT FROM AUTHOR]

Synthetic Aperture Radar (SAR) renderings in 3D provide additional target information when compared to 2D by separating out features overlaid in height. However, the required 2D SAR aperture, when Nyquist sampled, necessitates large scanning times that would be impractical for most realistic collections. This research has developed a novel volumetric approach to sparse aperture 3D SAR imaging, which is applicable to bistatic SAR near‐field geometries, a generalization of far‐field cases. This approach is first demonstrated in simulation and then applied to a measured scene containing a model vehicle target, producing sub‐Nyquist sampled 3D SAR renderings. [ABSTRACT FROM AUTHOR]

The micro‐Doppler (m‐D) effect caused by the rotational parts of the targets influences the quality of inverse synthetic aperture radar (ISAR) imaging. In this letter, a novel deep network‐assisted method is proposed to reduce the m‐D effect in ISAR imaging. The training data, including ISAR images with m‐D effect and ISAR images without m‐D effect, help the network establish non‐linear mapping relationships. The simulated and measured data results show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Interrupted sampling repeater jamming (ISRJ) is a novel intra‐pulse coherent jamming based on digital radio frequency memory (DRFM). By repeatedly sampling and retransmitting the radar transmitting signal fragments, a series of false targets can be formed after pulse compression (PC), posing a severe threat to modern radar systems. Inspired by the energy function method and histogram analysis in image processing, an adaptive time‐frequency (TF) filtering method is proposed in this letter. The ISRJ‐contaminated regions can be accurately determined in the TF image after histogram analysis and subsequent energy accumulation. Guided by the energy function, the proposed method can automatically adjust the intensity threshold in TF image histogram analysis and therefore reveals better robustness compared with other competing methods. Simulations have verified the effectiveness and robustness of the proposed method against ISRJ under various circumstances. [ABSTRACT FROM AUTHOR]

This letter addresses the coherent integration problem for detecting high‐speed target. A fast coherent integration method based on the short‐time Fourier transform (STFT) and sequence reversing transform (SRT), that is, STFT‐SRT, is proposed. In this method, STFT is first employed to obtain the velocity and improve the SNR without additional calculation. After that, SRT is presented to remove range migration (RM). Finally, the Fourier transform (FT) is conducted to achieve the coherent integration. The proposed algorithm can be easily implemented by using complex multiplications and the fast FT (FFT). Both simulated and real data results demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This study has been made to improve the detection capacity of radar using phase coded waveforms especially the Golay set sequence while keeping the sidelobe ambiguity function to the possible minimum. This Letter begins with a description of Golay complementary sets construction from a graph and a determination of the parameters on which they depend to be optimised after. Then, the simulated annealing (SA) algorithm has been proposed to deal with low ambiguity problem of the Golay set, due to its simplicity and also to its effectiveness to solve this kind of problem. Simulation results show that the optimisation with SA has impressively improved the sidelobe rejection of Golay set sequences with a gain of up to 20 dB. [ABSTRACT FROM AUTHOR]

This Letter describes a pulsed waveform which exhibits extreme Doppler tolerance, enabling large time‐bandwidth‐product observations of high‐velocity targets with low computational complexity. The waveform, which supports pulsewidth, pulse repetition interval, and frequency agility, utilises hyperbolic frequency‐modulated pulses with modulation parameters constrained to suppress range migration. [ABSTRACT FROM AUTHOR]

Fractional-N phase locked loops (PLLs) offer a low-cost solution to the precision frequency ramp requirements of frequency-modulated continuous-wave (FMCW) radar. In this application, however, the infamous spurious signals generated by these PLLs have not received adequate analysis. In this Letter, the authors investigate the impact of integer boundary spurs on FMCW radar performance. They show that the offset of these spurs is swept during the course of waveform generation, and that undesirable spur chirps manifest in the beat signal as a result. These spur chirps span the radar's intermediate frequency bandwidth and produce Fresnel ripples in the range profile which reduce spurious-free dynamic range. They present simulations and measurements that demonstrate how reduction of PLL bandwidth can be used to suppress these spurii. [ABSTRACT FROM AUTHOR]

Pulse‐agile radar systems are becoming more prevalent as the demand for adaptive and cognitive systems increases. This focus is motivated by the need for interference avoidance and spectrum sharing. Pulse agility within a coherent processing interval (CPI) or intra‐CPI adaption has been shown to cause distortion, which will negatively impact the radar's performance. This problem can be framed in the context of image processing such that an ideal range–Doppler image is corrupted by some point spread function. Deconvolution is then applied to remove this distortion and improve radar performance while maintaining the ability to use computationally efficient fast Fourier transform‐based processing. [ABSTRACT FROM AUTHOR]

An iterative adaptive approach (IAA) based algorithm is presented to realise coherent integration for the random pulse repetition interval radar. The proposed method firstly removes the effect of Doppler ambiguity via phase compensation, and then accomplishes target focusing via conducting the azimuth IAA and range inverse fast Fourier transform. Theoretical analysis and numerical experiments have verified the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

As a typical signal processing problem, direction-of-arrival (DOA) estimation has been adapted to a wide range of applications in radar-based systems. A high DOA resolution requires a large number of antenna elements which increases the overall cost. To minimise the cost, it is desirable to choose an optimum sub-array from a full array. To enable cognition, the subarrays are selected based on the present target scenario. By using deep learning (DL) based techniques, the authors show a cognitive sparse array selection technique. By using hardware simulations, they demonstrate the applicability of the deep learning (DL)-based sparse antenna selection network in direction-of-arrival (DOA) estimation problems. They show that the DL-based sub-arrays lead to a higher direction-of-arrival (DOA) estimation accuracy by 6 dB over random array selection. [ABSTRACT FROM AUTHOR]

In this Letter, the authors report on a 26 GHz joint communication–radar system. By exploiting the beam steering features of leaky‐wave antennas, angle‐of‐arrival estimation and multi‐user transmission are achieved. Furthermore, the Zadoff–Chu preamble of the OFDM waveform is used to provide a frequency‐modulated continuous‐wave radar signal. This way, the wide operational bandwidth is used for both, communications and radar, yielding high data throughput and precise user localisation. Experimentally, spectral‐efficient 16‐QAM multi‐user 5 × 4 Gbit/s communications and user localisation with an accuracy of about 2 cm and ±1.5° is demonstrated. [ABSTRACT FROM AUTHOR]

In this Letter, the authors propose a face identification method using radar sensor data. They use a frequency‐modulated continuous wave radar sensor that utilises a centre frequency of 61 GHz and a bandwidth of 6 GHz. Then, they accumulate radar data by transmitting and receiving radar signals on human faces. Finally, they use a convolutional neural network (CNN) to distinguish radar signals reflected from different human faces. In this network, signals received from multiple antenna elements are synthesised in parallel to make the radar signals into an image that is the input form of the CNN. The accuracy of face recognition through the CNN is >98%. In addition, they also collect radar data when the same subjects wear cotton masks. Within their entire dataset, wearing a mask does not significantly affect the accuracy of the radar‐based face recognition method. [ABSTRACT FROM AUTHOR]

This Letter demonstrates the technical capability of millimetre wave pulse-Doppler radar to identify safety-critical operating status information for parked cars. A simple 94-GHz pulsed linear frequency modulated radar with stretch processing on receive provides range-selective detection of small-scale vibration along the length of a parked car. The resulting range-Doppler signature clearly differentiates whether the car's engine is running or not as well as whether the car's transmission is shifting between 'park' and 'drive'. The rotational motion of an opening car door also produces a distinct signature in range-Doppler space. Incorporating this knowledge into future automotive sensors can alert oncoming vehicles to unanticipated actions of parked cars to avert potential damage or injury. [ABSTRACT FROM AUTHOR]

Radar sensors have a new growing application area of dynamic hand gesture recognition. Traditionally radar systems are considered to be very large, complex and focused on detecting targets at long ranges. With modern electronics and signal processing it is now possible to create small compact RF sensors that can sense subtle movements over short ranges. For such applications, access to comprehensive databases of signatures is critical to enable the effective training of classification algorithms and to provide a common baseline for benchmarking purposes. This Letter introduces the Dop‐NET radar micro‐Doppler database and data challenge to the radar and machine learning communities. Dop‐NET is a database of radar micro‐Doppler signatures that are shareable and distributed with the purpose of improving micro‐Doppler classification techniques. A continuous wave 24 GHz radar module is used to capture the first contributions to the Dop‐NET database and classification results based on discriminating these hand gestures as shown. [ABSTRACT FROM AUTHOR]

The future L‐band geosynchronous synthetic aperture radar (GEO SAR) system will be inevitably affected by ionospheric scintillation. Due to the lack of the real system, it is necessary to achieve the scintillation‐affected GEO SAR raw data for the research of influential mechanism and correction strategies. A method for the generation of scintillation‐affected GEO SAR raw data is proposed that utilises the reverse backprojection (ReBP) to efficiently and accurately modulate the scintillation transfer function on GEO SAR signals. A simulation experiment for a real SAR scene from one of the ALOS‐PALSAR observation is operated in case of the current inclined L‐band GEO SAR system configuration. The simulation takes less time by using the ReBP, compared with the existent method, and shows the speckle‐like phase error similar to the injected scintillation phase error, which validates the nice efficiency and accuracy of the proposed methodology. [ABSTRACT FROM AUTHOR]

The vital signal extraction remains an on‐going challenge due to the low signal‐to‐noise ratio (SNR) of vital signals in real tests. In this Letter, the authors propose a novel vital signal enhancement method using spectral gain instead of the traditional singular value decomposition (SVD) method, which shows excellent performance in the elimination of noise that is in the same frequency band as the vital signal and reducing calculation time. The simulation and experiment have been conducted, and the results indicate that the proposed extraction method outperforms the traditional SVD in output SNR and processing time. [ABSTRACT FROM AUTHOR]

This Letter addresses the coherent integration problem for the moving target detection in a pulse repetition interval (PRI)‐staggered radar system. Due to the random sampling, the complex coupling effects between range and azimuth will severely degrade the target parameter estimation and coherent integration performance. To deal with this issue, a fast coherent integration detection method with random azimuth sampling is proposed, where range migration is firstly compensated by applying the range‐frequency reversal transform. Then, the random phase fluctuation caused by the staggered PRI can be efficiently removed by applying the non‐uniform FFT technique. Finally, a moving target can be well focused. Simulated results are provided to validate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The performance of high‐frequency hybrid sky‐surface wave radar (HFSSWR) is known to suffer from the spread Doppler clutter (SDC). As a major source of the SDC, ionospheric clutter generally possesses high directivity within the main detection range. Classical coherent sidelobe cancellation method provides an efficient way to suppress the highly directional clutter. However, it performs poorly when the directions of a target and the clutter are both in the main lobe. To address this problem, a novel clutter suppression method using oblique projection is proposed, which does not require priori knowledge of the targets, such as directions, Doppler frequencies, strength etc. By combining training data selection based on oblique projection with SDC suppression in the Doppler domain, this method is implemented in the interested range cell for all target directions. Experimental results indicate that the proposed method can achieve better clutter suppression performance based on real data. [ABSTRACT FROM AUTHOR]

For the synthesised aperture radar, the radar signal with a zero autocorrelation zone (ZACZ) is synthesised, which represents a sequence from two phase‐code shift keying (PCSK) pulses coded by adjacent pairs of the D‐code with additional linear frequency shift‐keying (LFSK) of the train pulse discrete value. A comparative analysis is performed of correlation characteristics of the synthesised signal with the signal without discrete modulation and the truncated M‐sequence. Total correlation characteristics of the ensemble from four signals are also analysed. It is shown that in ZACZ, the level of all side lobes of the autocorrelation function (ACF) of the synthesised signal is less than the level of the ACF side lobes of the M‐sequence. The total ACF of the ensemble of four signals both with modulation and without the discrete modulation has zero side lobes along with the whole time axis τ, and at mismatch in frequency in ZACZ, it has the side lobe level <−40 dB. [ABSTRACT FROM AUTHOR]

When multiple ground‐based differential interferometric radar (GB‐DInRad) systems are utilised together to resolve three‐dimensional (3D) deformation, the resolving accuracy is related with the measurement geometry of these radar systems. This Letter focuses on how to determine an optimal geometry. Based on the resolving equation of the 3D deformation, the Geometric Dilution of Precision (GDOP) is defined. Then the minimum value of the GDOP is calculated and a detailed geometrical analysis is made to determine the geometrical conditions of the minimum GDOP. The results prove that the optimal geometry could be obtained when the unit measurement vectors of these radar systems construct a regular pyramid with a specific structure. A numerical simulation is utilised to validate the analysis conclusion. [ABSTRACT FROM AUTHOR]

The detection performance of high‐frequency surface wave radar (HFSWR) is significantly impacted by ionospheric clutter and sea clutter. In order to suppress the ionospheric clutter, a new method based on the largest Lyapunov exponent prediction algorithm is proposed in this Letter. Firstly, it is demonstrated, for the first time, that the ionospheric clutter from HFSWR is a chaotic dynamical process, and then the largest Lyapunov exponent is estimated using the Wolf algorithm. After verifying the actual data, this suppression algorithm can decrease the amplitude of the ionospheric clutter by at least 30 dB. [ABSTRACT FROM AUTHOR]

Automotive radar (AR) plays a key role in autonomous vehicles. A modern‐day AR requires cognition to adapt to its dynamically changing environment. In an automotive environment, the number of ARs needed to operate simultaneously varies rapidly and these ARs should transceive without mutual interference. Most widely used AR systems use frequency‐modulated continuous‐wave radar due to their smaller bandwidth and cost compared with pulse Doppler radar (PDR). By using sub‐Nyquist based techniques, such as Xampling, the authors show here that the targets could be estimated from low rate samples even with a PDR. In this study, they demonstrate a hardware prototype demonstrating the applicability of sub‐Nyquist PDR as a cognitive AR. They consider a scenario where a number of ARs are mounted on a vehicle and need to look simultaneously into different directions without interfering with each other. The available bandwidth is divided into several non‐overlapping subbands, which depend on the number of ARs required. Each AR is assigned a set of randomly spaced subbands for its transceiver to operate. Through simulations, they show that the ARs could detect targets simultaneously without interference. Furthermore, the noise robustness of their sub‐Nyquist reconstruction method is better than the standard matched‐filtering approach. [ABSTRACT FROM AUTHOR]

The micro‐motion feature extraction of precession target is an effective way for discriminating warhead from decoy in missile ballistic defence. Generally, traditional methods based on high‐resolution range profile (HRRP) sequences put forward high requirements on modulation bandwidth for the system, increasing the complexity of the system significantly. Utilising single‐frequency ladar without modulation, the authors proposed a precession parameter extraction algorithm of precession target based on high‐resolution Doppler profile (HRDP) sequences. Firstly, they model the Doppler bandwidth of the cone‐shaped precession target with the observation angle. Under the assuming that the measurement error obeys zero‐mean Gaussian distribution, the probability density function of Doppler bandwidth is established. Then, the precession parameters are estimated with measured Doppler profile sequences through maximum likelihood estimation method. Compared with the methods based on HRRPs, the proposed method based on the Doppler profile has lower requirements on the system and easier to implement. Laboratorial data has been used to validate the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

Through‐the‐wall radar is widely used in civil and military applications. However, the echo from the target behind the wall is often buried in the wall reflections and other clutter waves. An effective subspace selection method based on singular value decomposition for wall clutter mitigation is presented. Furthermore, the Akaike information criterion method is employed for noise clutter mitigation. Experimental results with real data demonstrate the correctness and effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Radar observation and signature identification of human motions have a variety of applications in social security and rescue operations. Both simulation and real radar experiment are conducted to investigate the polarimetric micro‐Doppler signatures (MDSs) of a pedestrian. In the simulation, the motion‐captured dataset developed by Carnegie Mellon University motion graphic laboratory is first used, then both Feldberechnung bei Korpern mit beliebiger Oberflache (FEKO) and MATLAB are used to calculate the radar scattering of pedestrian' arms, based on which, horizontal‐horizontal (HH) and horizontal‐vertical (HV) polarimetric MDSs are analysed. Simulation results clearly show that in the time–frequency diagram, HH micro‐Doppler (m‐D) of arms is rising, whereas HV m‐D is falling, which is verified by practical Ka‐band radar experiment on a pedestrian. The work shows that by using polarimetric radar the m‐D signature of human motion can be much well detected and identified which can be further explored for classification of different people. [ABSTRACT FROM AUTHOR]

A novel method to estimate the object velocity for random stepped frequency radar by the waveform design is proposed. The method utilises a so‐called 'complementary random code' to modulate the transmitted waveform. Theoretical analyses show that the proposed method achieves a high precision in velocity estimation, which could meet the requirements of motion compensation. Moreover, its computational complexity can be significantly reduced, compared with the classical estimation methods. Finally, the simulations validate the effectiveness of the present method. [ABSTRACT FROM AUTHOR]

The feasibility of measuring heart rate using radar echoes from a human head is demonstrated. Non‐contact measurement of vital signs using radar has been attracting much attention because such technologies can breakthrough benefits for monitoring health conditions without electrodes or wearable devices. Most existing studies have measured echoes from the torso, particularly the chest wall. However, this is difficult because of multiple interfering reflections from the complex shape of the torso and other body parts, such as limbs. The current study is the first demonstration that non‐contact heart rate measurement can be easily achieved using echoes from the human head. There are two important advantages of measurement from the human head: (i) the simple shape of the head makes an ideal radar target with only a single reflection, and (ii) the other undesired echoes can be removed using time‐gating when an ultra‐wideband radar is used. Nonetheless, because the displacement of the human head due to heart rate is small, a millimetre‐wave ultra‐wideband array radar system is developed, which is installed on the ceiling and used in the proposed measurements with participants. [ABSTRACT FROM AUTHOR]

A novel coherent high‐speed manoeuvering target detection method based on the parameterised autocorrelation function and three‐dimensional integration is presented. The parameterised autocorrelation function realises the searching parameters replacement and reduces the noise correlation without the signal energy loss. Consequently, compared to two representative detection methods, the proposed method can strike a balance between the computational cost and detection performance without the blind speed sidelobe. [ABSTRACT FROM AUTHOR]

This Letter addresses the coherent integration problem for air and space moving target detection in a staggered pulse repetition interval (PRI) radar system. In this algorithm, a range‐compressed signal is firstly transformed into the one in the range frequency domain, and then the authors resample the non‐uniformly sampled signal into a uniform grid along azimuth direction. Subsequently, the well‐known Keystone transform is applied to compensate the range cell migration caused by target motion. Finally, a moving target can be well focused in the range‐Doppler domain after motion compensation. Simulated results are provided to validate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The radar cross‐section (RCS) measurements for cylinders with different surface roughness have performed in the terahertz bands. The terahertz radar system has 220 and 440 GHz carrier frequencies. It is a solid‐state system whose base band signal is generated by a phasor network analyser. The original recorded data are calibrated by the results of the smooth surface cylinder. These calibrated RCS results are compared with calculated results. The experiments suggested that targets with the rough surface will provide complicated scattering in terahertz. The results of this experiment can prove that the surface roughness of the target has a certain impact on RCS measurement results in the terahertz band. [ABSTRACT FROM AUTHOR]

Many studies have demonstrated the capability of radar micro‐Doppler signature for classifying micro‐drones. However, most existing works on radar classification of drones are based on the assumption that the received signal is only reflected from a single drone. When multiple drones are present simultaneously, the existing methods of drone classification fail due to the superimposition of the micro‐Doppler features of multiple drones. In this Letter, a method for detection of multiple drones is proposed. First the time–frequency spectrogram is converted into the cadence‐velocity diagram (CVD), which expresses how the curves in the time‐frequency‐domain repeat. Then the cadence frequency spectrum (CFS), as the basis vector of the training data from each class, of the CVD is extracted. Finally, the K‐means classifier is used to recognise the component of multiple micro‐drones based on the CFS. The experimental results on real radar data demonstrate that the proposed method is capable of dealing with multiple drones with satisfactory classification accuracy. [ABSTRACT FROM AUTHOR]

The Letter aims to investigate the polarisation diversity for passive radar system. Digital television signal is used as the illuminator of opportunity in this experiment. Dual‐polarised Yagi‐Uda antennas have been independently designed as surveillance array antennas, which can receive horizontal (H) and vertical (V) polarisation simultaneously. The experimental results showed that the detection performance after polarisation processing depends on the difference between target polarisation state and interference polarisation state. The target detection performance will be improved if the technology of polarisation diversity is used. [ABSTRACT FROM AUTHOR]