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Radar coincidence imaging (RCI) is a high‐resolution radar imaging mode which constructs a temporal spatial stochastic radiation field (TSSRF) and uses the correlation between reference signal and echoes for imaging. The correlation between the reference matrix and the echoes is the main factor affecting the imaging performance. In fact, radar target characteristics cause fluctuations in the radar cross section and variations in the scattering intensity of each resolution element. The latter degrades the correlation between the reference matrix and the echoes, seriously affecting the image reconstruction. This paper designs the waveform based on image entropy under fixed transmitting and receiving arrays. The targets with fluctuating scattering intensity at each resolution element are statistically modelled. Simulation results show this approach can improve the imaging performance and reduce the energy dissipation degree of the target grid. [ABSTRACT FROM AUTHOR]

Detection of space objects is a key component of space situational awareness, which could help prevent and minimise space collisions. While there have been lots of radar systems designed to detect space objects, few of them have dealt with long baseline distributed bistatic pairs. The authors focus on the feasibility of long baseline bistatic radars, which can be extended for the multistatic case; and the performance of the multistatic system for a target at different altitudes assuming one transmitter over three different scenarios: a cluster of receivers, receivers spread throughout the world and the combination of the two previous cases. To analyse the performance the multiple‐input‐multiple‐output (MIMO) ambiguity function (AF) will be employed. The results of the MIMO AF show how the fusion of different bistatic pairs improves the detection capabilities. Moreover, when the different radar measurements are coherently summed in the MIMO AF, the uncertainty on the location of the target is reduced. [ABSTRACT FROM AUTHOR]

The Integrated Side Lobe Ratio (ISLR) problem the authors consider here consists in finding optimal sequences of phase shifts in order to minimise the mean squared cross‐correlation side lobes of a transmitted radar signal and a mismatched replica. Currently, ISLR does not seem to be easier than the general polynomial unconstrained binary problem, which is NP‐hard. In their work, the authors aim to take advantage of the scalability of quantum computing to find new optima, by solving the ISLR problem on a quantum annealer. This quantum device is designed to solve quadratic optimisation problems with binary variables (QUBO). After proposing suitable formulation for different instances of the ISLR, the authors discuss the performances and the scalability of their approach on the D‐Wave quantum computer. More broadly, their work enlightens the limits and potential of the adiabatic quantum computation for the solving of large instances of combinatorial optimisation problems. [ABSTRACT FROM AUTHOR]

Millimetre‐wave radar has been widely used in health monitoring and human activity recognition owing to its improved range resolution and operation in a variety of environmental conditions. With the MIMO antenna array, 4D radar is increasingly employed in autonomous driving, while its application in assisted living is recent and therefore the value added compared to the increase in signal processing and hardware requirements is still an open question. A model for 4D Time‐division multiplexing (TDM) multiple‐input‐multiple‐output (MIMO) frequency‐modulated Continuous wave radar is established using the human activities from the HDM05 motion capture dataset. The simulator produces an end‐to‐end simulation, including four human motions (jumping Jack, kick, punch, and walk), signal time of flight, noise, MIMO signal processing, and classification. Different pre‐processing and point cloud‐based methods are compared to obtain an average classification accuracy of 90% with PointNet. This study simulates a specific 4D TDM MIMO radar configuration to benchmark signal pre‐processing algorithms, which can also assist other researchers to generate range‐Doppler‐time (range‐Doppler time) point cloud data sets for human activities testing different radar configurations, array configurations, and activities saving valuable time in human resources and hardware development before prototyping to assess expected performances. [ABSTRACT FROM AUTHOR]

The marginal Fisher information (MFI) metric is used to design waveforms for the sake of informationally optimal adaptive‐on‐transmit radar operation. A framework for MFI waveform design is developed and the Polyphase‐Coded FM (PCFM) waveform model is utilised to produce a constant‐modulus, spectrally contained signal amenable to transmission with high‐power amplifiers. The efficacy of the MFI waveform design and minimum mean square error (MMSE) estimation is experimentally demonstrated and extended into an adaptive and dynamic sensing paradigm. The radar transmit waveform is optimised to maximise the Fisher information with respect to the range profile. Upon observing new information from radar echoes, the iterative MMSE (iMMSE) estimator then minimises the estimation error variance according to prior observations. Sequential information maximisation (via waveform design) and error minimisation (via iMMSE) tends towards the Cramér–Rao lower bound (CRLB) with additional measurements improving radar resolution and accuracy. These concepts maximise the information extracted by a radar operating in a congested spectrum where the available bandwidth is limited. [ABSTRACT FROM AUTHOR]

The transmit waveform with ambiguity function specifications in the range‐Doppler plane has been of great interest in traditional single antenna radar systems in recent years. This paper considers the design of waveform sets with a desired slow‐time ambiguity function for multiple‐input multiple‐output radar. Specifically, it is desirable that the ambiguity function has low sidelobes where clutter occurs, as this reduces the impact of the clutter on target detection. Instead of unimodular waveforms, the authors consider amplitude modulation signals and introduce the bound constraint on signal amplitudes into the optimisation for the consideration of transmitter efficiency. The design problem is formulated as minimising the weighted integrated sidelobes level of the ambiguity function over the range‐Doppler plane under bound constraints. The resulting problem has a highly non‐linear objective function and is constrained by bound constraints and quadratic equality (constant energy) constraints, making it difficult to solve. The authors develop an efficient algorithm based on the sequential quadratic programming technique and non‐linear conjugate gradient method to solve it. Simulation results show that the proposed algorithm is superior to the existing methods. [ABSTRACT FROM AUTHOR]

Due to the controllable degrees of freedom of frequency diverse array in the distance dimension, the frequency diverse multiple‐input multiple‐output (FDA‐MIMO) radar can easily deal with mainlobe interference, which is often difficult to solve in traditional phased arrays. Nevertheless, the performance of FDA‐MIMO radar will suffer from degradation in the scenario where spectrum interferences and signal‐dependent interferences coexist. In order to solve this problem, a novel FDA‐MIMO radar framework via antenna switching is proposed. Based on this framework, an effective method for jointly optimising antenna selection and beamforming against spectrum interferences and signal‐dependent interferences is developed. The resulting optimization problem is nonconvex and NP‐hard owing to the integer constraints caused by antenna selection. By relaxing the integer constraints, the original problem can be transformed into a convex optimization form and an iterative reweighting strategy is used to force the obtained solution to satisfy the integer constraints. Simulation examples show that the proposed algorithm has better performance in output signal‐to‐interference‐plus‐noise ratio (SINR) and beampattern radiation performance than the existing competitive methods. [ABSTRACT FROM AUTHOR]

To address the problems of traditional two‐level nested arrays (TTNA) with low degrees of freedom and high mutual coupling, a generalised two‐level nested MIMO radar array with high degrees of freedom and low mutual coupling for the direction of arrival (DOA) estimation is proposed. First, two coprime expansion factors are introduced in the TTNA to mitigate mutual coupling among array elements and enhance its degrees of freedom. Secondly, the range of consecutive lags and the total number of virtual array elements are derived in closed form under the structures of 'sum–difference co‐array'. Finally, utilising the atomic norm minimisation theory, the authors address the issue of discrete holes caused by different coprime expansion factors through filling in virtual arrays at discontinuities. Furthermore, a convex optimisation model to recover equivalent received signals from these filled virtual arrays is established, which is combined with a multiple signal classification algorithm for DOA estimation. Simulation results validate the rationality of the array structure and demonstrate the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

The Gaussian noise model and estimators based on least squares (LS) are widely used in target localisation with distributed multiple‐input multiple‐output (MIMO) radar because of their computational efficiency. However, the accuracy of existing LS‐based target localisation algorithms deteriorates sharply in the presence of outliers in the measurements. Thus, a robust solution is developed based on the lp ${l}_{p}$‐norm minimisation criterion and iteratively reweighted least squares (IRLS) for locating a moving target with impulse noise using the angle of arrival (AOA), time delay (TD), and Doppler shift (DS) measurements. First, the AOA, TD, and DS measurement noise models are developed based on the α‐stable distribution. Then, the localisation problem is transformed into an lp ${l}_{p}$‐norm minimisation problem by linearising the AOA, TD, and DS measurement equations. Finally, the lp ${l}_{p}$‐norm minimisation problem is solved using an IRLS method to obtain the target position and estimate the velocity. Moreover, the optimum of the norm order (p) and the Cramér–Rao lower bound for the target position and velocity estimation are derived under α‐stable distributed measurement noise. The simulation results demonstrate that the developed algorithm offers higher accurascy and robustness than the existing ones in the presence of measurement outliers. [ABSTRACT FROM AUTHOR]

Multiple‐Input‐Multiple‐Output (MIMO) radar has the characteristic of multiple antenna channels, bringing on a big data volume for signal processing. Therefore, the trade‐off between detection ability and computational efficiency is always considered. In this article, an optimisation system is proposed to enhance the real‐time performance of frequency division MIMO radar without compromising accuracy. For the scenario of low‐altitude small target detection, a signal processing acceleration method is proposed and a MIMO radar optimisation system based on graphics processing unit (GPU) architecture is built. The signal model of frequency division MIMO radar is first established, improving the classical signal processing flow efficiency from the perspective of reducing fast Fourier transform (FFT) times and windowing operation times. To achieve an advanced acceleration, the parallel architecture of ArrayFire‐library in GPU is then employed. Distinct minimum parallel units are extracted by analysing the principle of digital beamforming (DBF), pulse compression, moving target detection (MTD), and constant false‐alarm rate (CFAR) algorithms. And the corresponding parallel algorithms are designed to constitute a parallel acceleration system of frequency division MIMO. Simulation results indicate that the proposed method significantly improves the efficiency of MIMO system with a maximum acceleration ratio of 65 times, meeting the real‐time processing requirements. [ABSTRACT FROM AUTHOR]

In this letter, a dilating and embedding scheme for constructing sparse multiple-input and multiple-output radar arrays is addressed, which seeks to increase the uniform degrees of freedom (uDOFs) and reduce the mutual coupling effects for a given number of transmitters and receivers (Tx/Rx). According to this scheme, a dilated maximum interelement spacing constraint (MISC) array with an embedded thinned coprime array in the collocated MIMO radar for DOA estimation is proposed. Theoretical analysis shows that the proposed array can provide higher uDOFs and is robust in a scenario with heavy levels of mutual coupling. Numerical simulations are conducted to validate its aforementioned advantages in line with the design scheme. [ABSTRACT FROM AUTHOR]

This study considers designing constant‐modulus waveforms for multiple‐input‐multiple‐output radar in spectrally crowded environment. The mutual information is used as the waveform design metric. A constant‐modulus constraint is imposed on the waveforms to improve the hardware efficiency. To enhance the spectral compatibility of the transmit waveforms, a precise control on the interference energy produced on each reserved bandwidth is considered. To tackle the multi‐spectrally constrained waveform design problem, a minorisation‐maximisation based method is developed, and a quadratic function to minorise the objective function is derived. Then an alternating direction method of multipliers is used to tackle the quadratically constrained quadratic programming problem at each iteration. The effectiveness of the presented algorithm is demonstrated via simulation results. [ABSTRACT FROM AUTHOR]

Multicarrier technology is widely used for improving the performance of beampattern synthesis in frequency diverse array multiple‐input and multiple‐output (FDA‐MIMO) Radar. However, how to use multicarrier technology to achieve highly focussed beampattern synthesis is still an open problem. To this end, the authors first establish the system model of FDA‐MIMO radar with multicarrier transmission and analyse the parameters influencing beampattern synthesis by Cramér–Rao lower bound derivation. It can be recognised that frequency increments and multicarrier distribution are key parameters hindering highly focussed beampattern synthesis. On top of the investigation, a simple yet effective Multidimensional Non‐linear Frequency Component, named multidimensional frequency components (MNFC), is proposed for forming a highly focussed beam. Specifically, MNFC is a two‐dimension frequency component for FDA‐MIMO radar. The first dimension is the frequency increment weighted by the Dynamic Taylor Window Function that effectively decouples the joint‐range‐angle beampattern. The second dimension is a non‐linear multicarrier weighted by Log with a Linear Coefficient for further optimising dot‐shaped beampatterns for target indication with high precision. Finally, numerical simulations and comparative experiments are performed to validate the superiority of the MNFC in beampattern synthesis. [ABSTRACT FROM AUTHOR]

Small‐array high‐frequency surface wave radar (HFSWR) is widely used to monitor maritime targets as it can be used to save on‐land resources. In small‐array HFSWR systems, the main lobe of the receiving angle spectrum is significantly broadened. In complex clutter backgrounds, an extremely wide beam severely influences clutter suppression performance; consequently, targets with a low signal‐to‐clutter ratio (SCR) may be eliminated, or the angle may be barely estimated. This study proposes a space‐time adaptive processing (STAP) algorithm based on hyper beamforming (HBF) to improve the clutter suppression performance of small‐array HFSWR. In addition, HBF can obtain more independent identical distributed training samples than the conventional beamforming; thus, the STAP algorithm can extract the clutter information with high accuracy in the covariance matrix estimation. Moreover, this study combines an efficient STAP algorithm with a joint domain localised (JDL) algorithm to improve clutter suppression. Based on the experimental results, the proposed HBF‐JDL algorithm performs satisfactorily and significantly improves the SCR. Moreover, HBF‐JDL is still applicable at lower SCRs of the target compared with JDL. [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 radome can protect the enclosed antenna from harsh weather and environmental conditions; however, it will cause a non‐negligible effect particularly transmission loss on the wideband signal which has been widely used in electronic systems. For this, a novel transmission loss compensation method for radome based on non‐linear frequency modulation (NLFM) waveform design is proposed. First, the transmission coefficient calculation process is given, Then, the detailed NLFM waveform design method is described in detail. Finally, the simulation experiments are demonstrated to verify the effectiveness of the proposed compensation method. Based on the designed NLFM waveform, the transmission loss can be compensated and a flat frequency response can be obtained, which can achieve excellent performance of pulse compression in the range direction. The proposed NLFM design method has great potential application value in the electronic system. [ABSTRACT FROM AUTHOR]

Radar waveform design is facing severe challenges with the development of radar countermeasure technology, such as easy access to intra‐pulse modulation property and poor anti‐recognition capabilities. Both frequency modulation and phase modulation can improve the waveform countermeasure performance in existing research. Amplitude modulation can also improve the anti‐identification ability of the waveform by increasing the signal complexity in the time domain, which is a newly developing modulation method. A joint amplitude‐frequency‐phase modulation (JAFPM) signal is proposed in this study, which has good waveform confrontation potential due to high waveform complexity and randomness. Besides, an echo processing method which combines matched filtering and compressed sensing reconstruction is further proposed based on sparse sampling characteristics of signal. Simulation results show that more accurate target information can be obtained compared with matched filtering processing under the condition of a low signal‐to‐noise ratio, which demonstrates the effectiveness of the proposed JAFPM radar waveform design and processing method. [ABSTRACT FROM AUTHOR]

The number of antennas in automotive frequency‐modulated continuous wave (FMCW) multiple‐input multiple‐output (MIMO) radar systems is increasing. Existing greedy or subspace‐based methods cannot quickly and accurately estimate the direction of arrival (DoA) of the target. Therefore, we propose a fast and accurate DoA estimation algorithm for the automotive FMCW MIMO radar. To achieve both fastness and accuracy, we exploit the group sparsity in DoA estimation by defining the problem as a multiple measurement vector (MMV) compressive sensing and extend the step‐learnt iterative soft‐thresholding algorithm (SLISTA) to the MMV problem. To apply the extended SLISTA, we train the network in an unsupervised manner and normalise the input. We conduct experiments to evaluate the performance of the proposed method. Compared to the algorithms such as ISTA/FISTA/MFOCUSS that solve the same optimisation problem, the extended SLISTA exhibits the most accurate DoA estimation results for actual targets, with less execution time than a subspace‐based method. Moreover, the results show that the extended SLISTA prevents false detections, whereas greedy and subspace‐based methods do not. [ABSTRACT FROM AUTHOR]

Frequency diversity array (FDA) radar provides more degrees of freedom and can generate range‐angle‐time‐dependent beampattern. Furthermore, based on the receiver's multi‐input multi‐output (MIMO) scheme, the frequency diversity array‐multi‐input multi‐output (FDA‐MIMO) radar can develop a range‐dependent but time‐independent beampattern. Taking advantage of this feature, this article improves the signal‐to‐interference‐plus‐noise ratio and the effective suppression of interference by jointly optimising the transmit beamspace and the receive filter. Since the optimisation problem is a non‐convex problem with constant energy constraints, we transform it into two convex subproblems with restrictions. The whole algorithm follows the alternate optimisation over receive filter and transmit beamspace. By simulating challenging scenarios, we confirmed the effectiveness and superiority of the method. [ABSTRACT FROM AUTHOR]

Randomized stepped‐frequency (RSF) radar has the potential of realizing joint high‐resolution range‐Doppler estimation. However, estimating multiple targets' two‐dimensional parameters at high efficiency based on RSF waveforms is still a difficult issue. In this study, a novel algorithm, which estimates multiple targets' velocities by using different frequencies pulses and then generates their high‐range‐resolution profiles (HRRPs), is proposed for RSF radar. In the velocities estimation, by setting a certain difference‐frequency parameter, a set of signals with constant range‐phase terms and changing velocity‐phase terms is constructed and then used to generate a new generalized Doppler spectrum called the difference‐frequency Doppler spectrum (DFDS). To suppress rising noise floors caused by sidelobes and cross‐terms in the DFDS, DFDSs corresponding to different difference‐frequency parameters are non‐coherently integrated to obtain a so‐called accumulated DFDS. From the accumulated DFDS, targets are detected and their velocities are estimated. In the HRRPs generation, a special dictionary matrix is structured by using the estimated velocities, and each target HRRP, without interference from other targets, is generated via the compressed sensing (CS) technique. The proposed algorithm avoids huge computation burden by separately performing Doppler and range process, and guarantees the performance in a multi‐target scenario via the noise floors suppression and CS. [ABSTRACT FROM AUTHOR]

This letter considers the problem of beamforming in multiple‐input multiple‐output (MIMO) radar. The mismatch phenomenon of MIMO radar virtual array steering vector is addressed, which can better describe the mismatch characteristics of not only one‐way transmitting or receiving path but also the whole transmit‐receive path for a collocated MIMO radar. Then, a new robust beamforming method for MIMO radar against virtual array steering vector mismatch is proposed. The object function of this robust MIMO radar beamformer is constructed from an infinite norm of the output data, which is solved by linear programming. The performance of the proposed beamformer is verified by simulation results. Numerical results illustrate that proposed beamformer exhibits good performance improvement in virtual array steering vector mismatch compared to conventional methods. [ABSTRACT FROM AUTHOR]

This letter formulates a high‐dimensional multi‐objective optimization model to minimize all correlation function values for multiple input multiple output (MIMO) radar waveforms. Then, to solve this problem, this letter proposes an adaptive weighted cyclic algorithm‐new (CAN), named p‐norm weighted cyclic algorithm‐new (p‐WeCAN). Specifically, the adaptive weight updating function is constructed using p‐norm to minimize peak side‐lobe level (PSL) and integrated side‐lobe level (ISL) simultaneously. Numerical results show that the p‐norm weighted cyclic algorithm‐new obtains similar PSL values as the best PSL minimization algorithm and low integrated side‐lobe level values close to its lower bound at the same time. [ABSTRACT FROM AUTHOR]

Frequency diverse array‐multiple input multiple output (FDA‐MIMO) radar not only has the advantage of waveform diversity but also can realise azimuth‐range correlation map, so it can realise high precision azimuth‐range joint estimation and has the ability to distinguish different range unit targets in the same azimuth. However, the existing research mainly adopts uniform linear array (ULA) model and mainly focusses on incoherent targets. At present, the elevation‐range joint estimation algorithm of metre wave FDA‐MIMO radar based on ULA has the problems of sharp decline in angle‐range measurement accuracy of ultra‐low altitude targets and large fluctuation of elevation‐range measurement accuracy with changing elevation. In order to solve the above difficult problems, starting from the perspective of reducing the influence of multipath effect by array structure, this paper innovatively combines sparse array with FDA‐MIMO radar, establishes the low elevation‐range joint estimation model of metre wave FDA‐MIMO radar based on sparse array, and puts forward the low elevation‐range joint estimation method suitable for this model, and it fills the gap of low elevation‐range measurement method based on sparse array metre wave FDA‐MIMO radar. Simulation experiments compare two typical sparse arrays with ULA of equal array elements, which verify the superiority of low elevation‐range measurement performance of monostatic metre wave FDA‐MIMO radar based on sparse array and the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, the waveform design for Rician target detection with multiple‐input‐multiple‐output radar is addressed. The relative entropy between the distributions of the observations under two hypotheses is employed as the design metric. Due to the difficulty of tackling the non‐convex waveform design problem, a novel algorithm based on minorisation‐maximisation is developed. Since a simple quadratic function is established to minorise the objective function, the presented algorithm has lower computational complexity than its counterparts. Moreover, it can be extended to design waveforms under many practical constraints, including the constant‐envelope constraint, the similarity constraint, and the constant‐envelope and similarity constraints. Numerical results are provided to show the effectiveness of the proposed algorithm for detecting Rician targets. Moreover, the designed waveforms can be used to enhance the detection performance of a Swerling 0 target in the presence of angle mismatch. [ABSTRACT FROM AUTHOR]

Compared with traditional approaches that used vision sensors which can provide a high‐resolution representation of targets, millimetre‐wave radar is robust to scene lighting and weather conditions, and has more applications. Current methods of human skeletal pose estimation can reconstruct targets, but they lose the spatial information or don't take the density of point cloud into consideration. We propose a skeletal pose estimation method that combines point convolution to extract features from the point cloud. By extracting the local information and density of each point in the point cloud of the target, the spatial location and structure information of the target can be obtained, and the accuracy of the pose estimation is increased. The extraction of point cloud features is based on point‐by‐point convolution, that is, different weights are applied to different features of each point, which also increases the nonlinear expression ability of the model. Experiments show that the proposed approach is effective. We offer more distinct skeletal joints and a lower mean absolute error, average localisation errors of 6.1 cm in X, 3.5 cm in Y and 3.3 cm in Z, respectively. [ABSTRACT FROM AUTHOR]

Sparse frequency agile linear frequency modulation-orthogonal frequency division multiplexing (LFM-OFDM) radar can improve anti-interference ability as well as reduce the sampling rate of the radar system. However, the frequency agility makes it difficult to realize coherent processing by using the fast Fourier transform. To overcome this problem, a signal processing scheme for the sparse frequency agile LFM-OFDM radar is proposed to obtain the high range and Doppler resolution in this study. The subcarriers are synthesised to an LFM signal in the time domain at first. Then, within the framework of the compressed sensing theory, an improved orthogonal matching pursuit algorithm is proposed to obtain the high-resolution range-velocity profile while reducing the computation complexity. Finally, several numerical simulations are provided to verify the effectiveness of the proposed method for moving targets. [ABSTRACT FROM AUTHOR]

The integrated radar and communications (IRC) waveform can simultaneously estimate the range and velocity of other targets while communicating with other facilities. In high‐speed scenarios, the IRC echo signal based on orthogonal frequency division multiplexing (OFDM) needs to consider the intra‐symbol and inter‐subcarrier Doppler effects. This paper first builds a receiving model of the integrated echo signal by including the intra‐symbol and inter‐subcarrier Doppler effects. On this basis, we propose a two‐step joint range and velocity estimation method, where rough estimation is performed by an improved estimating the signal parameters via the rotational invariance technique (ESPRIT), and a least‐square weighted (LSW) method is applied for fine estimation. The Cramer‐Rao lower bound (CRLB) of the receiving model is also provided, and the computational complexity of the proposed method is analyzed. Simulation results demonstrate the superiority of the proposed method. [ABSTRACT FROM AUTHOR]

The purpose of operating a radar system multistatically is to acquire information about targets of interest more quickly and reliably than would be possible using disparate radars, which fuse data and track post‐detection. This paper identifies and addresses the critical issues for designing a coherent multistatic radar system using conventional coherent radars and proposes a set of design principles for configuring a coherent multistatic radar network with the aim of maximising the utility of information while constraining system cost and complexity. The issues discussed are as follows: the localisation of targets in three dimensions; eliminating the inevitable spatial ambiguities arising from sparse spatial sampling while exploiting the large aperture for high resolution; the achievement of spatial coherent processing gain for target detection; the effect of phase centre localisation, phase and frequency errors on synchronisation; the incorporation of three‐dimensional Doppler estimation for slow‐time coherent integration. The arguments presented are physically‐based and complemented by mathematical analysis and numerical experimentation using non‐linear sparse estimation, the sparse algorithm being critically important for resolving spatial ambiguities. An optimal configuration is identified, which has sufficiently many nodes to overcome spatial ambiguities and achieves significant spatial coherent processing gain, while simultaneously constraining the overheads of inter‐node synchronisation and communication. [ABSTRACT FROM AUTHOR]

A multiplatform radar network (MRN) composed of multiple transmitting and receiving facilities is advantageous over monostatic radar in moving target detection (MTD) and tracking due to the diversity gain. Within the framework of the Internet of Battlefield Things (IoBT), the authors propose that the airborne platforms equipped with the cognitive multimodal radar (CMR), the subarray‐based MIMO radar (SMR), the active electronically scanned array (AESA) radar, and the adaptive radar countermeasures (ARC) should team up in target detection and tracking. To obtain better target detection and tracking performance, the probing signals from the CMR, the SMR, and the AESA radar are adaptively optimised based on the scenario under consideration. The ARC consists of two parts: 1) RF signal sensing and recognition with deep neural network (DNN), that is, to detect, identify, and localise multiple radio frequency emitters; 2) intelligent fake return creation and jamming to confuse the enemy radars in real time in the field. This work aims to serve as a good reference for future researchers interested in developing MRN with diverse nodes and the general teaming of radars on the battlefield. [ABSTRACT FROM AUTHOR]

As one of the key technologies of electromagnetic spectrum operations, radar waveform recognition is an important basis for judging the threat degree of enemy's weapons. At present, it is difficult to recognize the waveform at low signal‐to‐noise ratio (SNR), and the theoretical simulation is used in most research studies, which leads to the problem that the engineering practicality of the algorithm is poor. In this paper, a two‐stream convolutional network radar waveform recognition (TCNRWR) algorithm that fuses the original time–frequency image and the continuous frames autocorrelation time–frequency image is proposed, and an experimental platform is built by using software defined radio technology. Compared with traditional theoretical simulations, this paper focusses on the influence of spatial background interference and signal incompleteness on the recognition of intra‐pulse signals, and proposes an automatic removal method of invalid signal in the time–frequency domain. In order to further improve the recognition rate at low SNR, a deeper feature of short‐time autocorrelation flow is excavated, and a two‐stream time–frequency images fusion convolutional network (TTIFCNet) is constructed. The network effectively fuses the pre‐classification results of the two streams through Softmax layer and different weights. Finally, the hardware platform HackRF is used to realize the communication and processing of signals in real space, which proves the effectiveness of the TCNRWR algorithm. [ABSTRACT FROM AUTHOR]

Since cables are the critical structural components for ensuring the overall structural integrity and safety of cable‐stayed bridges, the portable and rapid cable force measurement has a very important practical significance in the bridge health monitoring. In this paper, a method of simultaneous and continuous estimation of the forces of multiple cables using a self‐developed microwave interferometric radar was proposed. In the proposed approach, first, the time‐varying modal frequencies are identified by the Hilbert transform algorithm from the displacements of multiple cables, which are monitored by the self‐developed radar, and then, the time‐varying cable forces are obtained by the vibration method. In addition, for the problem of multiple cables located in the same range bin when distance test or the test angle is nonideal, a single‐channel blind source separation algorithm based on vibrational mode decomposition (VMD) and time‐frequency analysis was proposed to separate the cable signals. Furthermore, a method based on the spectrum correlation coefficients was proposed to determine the number of decomposition layers in VMD. The "Nanjing Eye" cable‐stayed footbridge was used to conduct field measurement to validate the proposed method. Field measurement results show a good agreement with reference measurements, which demonstrate that the proposed method can perform well in an actual project for portable and rapid cable force estimation. [ABSTRACT FROM AUTHOR]

In order to solve the problems of slow imaging speed and poor reconstruction accuracy of wall parameters under the condition of wall parameter fuzziness, an improved limited Broyden-Fletcher-Goldfarb-Shanno-particle swarm optimisation (LBFGS-PSO) algorithm was proposed. The LBFGS-PSO algorithm model solves the problems of slow calculation speed and large errors of the traditional quasi-Newton algorithm and particle swarm algorithm. The algorithm combined with block orthogonal matching pursuit algorithm can not only accurately reconstruct the position of the sidewall, but also can use the multi-path information to accurately reconstruct the moving target and the stationary target. Compared with the traditional BFGS algorithm and PSO algorithm, the proposed algorithm can reduce the calculation time and provide more accurate estimation results. Simulation results and data analysis verify the performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

When driving on an iron-bridge, stationary iron-clutters cause disturbances in the detection of a moving target in an automotive radar system. In this Letter, the authors propose a moving target detection method that utilises phase similarity of the spatial domain on an iron-bridge. To analyse the spatial domain via the array antenna signal of the up- and down-chirp beat-frequencies, the frequency-modulated continuous wave (FMCW)-phased array radar signal was used. It is possible to match the up- and down-chirp beat- frequencies of each object, moving target, and stationary iron-clutters, by using the proposed method. Not only the moving target but also the ego-vehicle and moving target velocity are detected through this matching. The suitability of the proposed method is verified by on-road measurement data using a 77 GHz FMCW-phased array radar. [ABSTRACT FROM AUTHOR]

Multiple-input multiple-output (MIMO) radar has many advantages over the phased-array radar due to the waveform diversity, one of which is the greater flexibility to design the transmit beampattern. In this Letter, a low-complexity transmit beampattern design method, considering constant envelope (CE) waveforms, is proposed for the uniform linear array MIMO radar. First, the authors parameterise the waveform covariance matrix as the integral form of continuous spatial variable, by exploiting the beamforming weight vector in the main lobe region, to derive the closed-form solution of the waveform covariance matrix that fulfils positive semi-definiteness and uniform elemental power constraints. The transmit beampattern designed by the proposed method has the spatial characteristics of low main lobe fluctuation and peak-to-sidelobe level, and further mathematical explanation is illuminated. Next, they directly use the parameterised expression of waveform covariance matrix, approximately transformed into a discrete form of the spatial variable based on the Riemann integral definition, to efficiently synthesise correlated CE waveforms. The proposed method can provide transmit beampattern performance comparable to existing methods with a lower computational cost and ensure the CE property of the waveforms. The performance of the proposed method is verified and analysed via numerical examples. [ABSTRACT FROM AUTHOR]

In this Letter, the problem of waveform design for MIMO radar with good transmit beampattern performance is investigated. The binary transmit waveforms are designed via minimising the beampattern integrated sidelobe to mainlobe ratio. Since the resulting binary combination optimisation problem is NP-hard, a generalised likelihood ascent search algorithm is proposed to deal with it. Besides, the effectiveness of the proposed algorithm is demonstrated via simulation results. [ABSTRACT FROM AUTHOR]

The frequency-modulated continuous wave (FMCW) radar will play a more important role in future intelligent traffic systems due to low cost and high adaptability to complex environments. Generally, a 2D array is utilised to measure range, speed and azimuth and elevation angles (4D) for multiple vehicles simultaneously. However, a traffic radar utilising a 2D array will enhance its system complexity; therefore, the increased cost would make it less superior to LiDAR. In this Letter, an azimuth and elevation angles estimation method of FMCW radar utilising only 1D array is proposed. Thus, it can provide 4D parameters to multiple vehicles simultaneously. The feasibility of the proposed approach is verified by on-road measurement data. [ABSTRACT FROM AUTHOR]

The beam system of multiple input and multiple output (MIMO) radar needs lower peak sidelobe level for reducing interference, in addition, broad nulls placed at undesired directions are also an alternative method. A hybrid method based on the whale optimisation algorithm is proposed to implement sidelobe suppression and broad nulls. To the best of the authors' knowledge, relative works based on the whale optimisation algorithm applied to MIMO radar are not reported so far. By introducing chaotic optimisation into the whale optimisation algorithm scheme, performance of origin algorithm is improved substantially in suppressing peak sidelobe level with constraint of broad nulls. Furthermore, it is found in the experiment that the proposed algorithm can avoid the premature of origin algorithm effectively, and only takes a short time during the optimum accomplishment. Finally, simulation results demonstrate the good performance of the proposed method. [ABSTRACT FROM AUTHOR]