Distributed multiple-input multiple-output (MIMO) radar networks operating at millimeter-wave frequencies enable high-resolution microwave imaging but face fundamental limitations in antenna array synthesis. Sparse virtual apertures reduce hardware complexity yet introduce severe grating lobes and sidelobe artifacts, which degrade image fidelity via aliasing in the electromagnetic (EM) spatial frequency domain. To address these antenna array synthesis challenges, we propose a noisy tensor completion framework exploiting joint low-rank and sparsity constraints inherent in radar scattering. Our method reorganizes radar echoes into high-dimensional tensors with dispersed missing elements, explicitly modeling the sparse array sampling process. A key innovation is an adaptive singular-value reweighting scheme that preserves dominant EM scattering components while suppressing noise-corrupted interference. The resulting optimization is solved via an alternating direction method of multipliers (ADMM) algorithm. Extensive EM simulations and experimental validation using a prototype W-band (77 GHz) distributed MIMO radar system demonstrate superior artifact suppression and target reconstruction over state-of-the-art methods. This establishes a robust imaging solution for sparse-aperture systems by directly addressing antenna array pattern limitations through tensor-based aperture synthesis.

The rapid advancement of Internet of Things (IoT) technology, particularly in the realm of autonomous driving, has elevated the requirements for automotive radar systems to achieve precise environmental perception. This article delves into the distributed MIMO radar network model and the associated signal processing techniques that enable accurate measurement of range, velocity, and angular positions, culminating in the generation of high-resolution 4-D point clouds. These capabilities are pivotal for intelligent interactions between vehicles and their surroundings within the IoT ecosystem. We introduce a stepped-frequency frequency-modulated continuous wave (SF-FMCW) waveform that incrementally increases the starting frequency of each chirp, leading to a larger bandwidth and finer range resolution without altering the individual chirp bandwidth. Furthermore, we propose a hybrid FDM-DDM scheme to ensure orthogonality among MIMO waveforms. This scheme allows for decoding across various DDM modes through the application of overlapping binary masks, while maintaining unambiguous range-Doppler measurements, which is crucial for real-time data processing and decision-making within IoT. To enhance angular resolution, we optimize the array configuration and develop a low sidelobe direction of arrival (DOA) estimation method using phase coherence factor (PCF) techniques. Extensive simulations and experimental analyses demonstrate the superior performance of the proposed methods in resolving closely spaced targets and generating high-fidelity 4-D point clouds, even in challenging scenarios with limited angular separation. The development of these technologies is significant for intelligent perception and safe navigation of vehicles within the IoT, providing a technological foundation for seamless integration of vehicles with the IoT infrastructure.

Abstract A low probability of intercept (LPI)‐based cooperative node selection and transmit resource allocation (CNS‐TRA) strategy is proposed for multi‐target tracking in multiple radars architecture (MRA). The key idea of the proposed CNS‐TRA strategy is to coordinate the radar node selection and the transmit resource that is, dwell time, transmit power, and effective bandwidth allocation to improve the LPI performance, under the constraints of predefined target tracking accuracy requirement and several resource budgets. By incorporating the above controllable parameters, the Bayesian Cramér‐Rao lower bound is calculated and used as the accuracy metric for target tracking. Subsequently, this paper develops a fast and effective two‐stage‐based solution methodology to solve the resulting non‐convex and non‐linear optimisation problem. Specifically, the optimisation problem can be decomposed into two sub‐problems, that is, the radar node selection sub‐problem and the transmit resource allocation sub‐problem. The active‐set method and the interior point approach are utilised to solve those two sub‐problems, respectively. Simulation results demonstrate that the CNS‐TRA strategy has superiority over other existing algorithms and can achieve better LPI performance for MRA.

Simultaneous feature selection and clustering is a major challenge in unsupervised learning. In particular, there has been significant research into saliency measures for features that result in good clustering. However, as datasets become larger and more complex, there is a need to adopt a finer-grained approach to saliency by measuring it in relation to a part of a model. Another issue is learning the feature saliency and advanced model parameters. We address the first by presenting a novel Gaussian mixture model, which explicitly models the dependency of individual mixture components on each feature giving a new component-based feature saliency measure. For the second, we use Markov Chain Monte Carlo sampling to estimate the model and hidden variables. Using a synthetic dataset, we demonstrate the superiority of our approach, in terms of clustering accuracy and model parameter estimation, over an approach using a model-based feature saliency with expectation maximisation. We performed an evaluation of our approach with six synthetic trajectory datasets obtaining an average clustering accuracy of 97 percent. To demonstrate the generality of our approach, we applied it to a network traffic flow dataset obtaining an accuracy of 93 percent for intrusion detection. Finally, we performed a comparison with state-of-the-art clustering techniques using three real-world trajectory datasets of vehicle traffic. Our approach achieved an average clustering accuracy of 96 percent compared to 77-95 percent for the other techniques. In conclusion, for the datasets considered, component based feature saliency measures gave improved clustering over those based on whole models.

Effective resource utilization is an important problem in the application of array, especially for the new time modulated array. Considering the problem of full utilization of array elements in time modulated array, a sparse optimization algorithm based on discrete variable convex optimization is proposed in this paper. The pattern optimization of equal excitation time modulation array is realized in two stages: In the first stage, the number of working array elements is as low as possible under the condition of suppressing the sidelobe of the central frequency. In the second stage, the sideband is suppressed by iterative convex optimization. The numerical simulation results are compared with other methods to verify the effectiveness of the proposed method in pattern optimization of equal excitation time modulation array. Finally, the optimization performance of the algorithm with different array parameters is verified.

This paper studies the problem of Stackelberg game based distributed power allocation for spectral coexisting multistatic radar and communication systems. The strategy aims to minimize the radiated power of each radar by optimizing transmit power allocation for a desired signal-to-interference-plus-noise ratio (SINR) meanwhile the communication base station (CBS) is protected from the interference of radar transmissions. We formulate this distributed power allocation process as a Stackelberg game, where the CBS is a leader and the radars are the followers. The Nash equilibrium (NE) for the formulated game is derived. Then, the existence of the NE and uniqueness of the solution are analytically proved. Moreover, an iterative algorithm is developed to solve the resulting problem. Finally, numerical results verify that the proposed scheme is effective on power allocation and CBS protection with reduced signaling overhead.

Helicobacter pylori (H. pylori) infection remains a cause of significant morbidity and mortality worldwide. Comprehensive understanding of the pathogenic mechanism of H. pylori and its interaction with host will contribute to developing novel prophylactical and therapeutical strategies. Here, we first determined microRNA (miRNA) levels in H. pylori-infected patients with gastritis, duodenal ulcer, gastric cancer or mucosa-associated lymphoid tissue lymphoma using miRNA data sets. Thirty-four differentially expressed miRNAs were identified and functional enrichment analysis of those miRNA target genes revealed that H. pylori infection were strongly associated with pathway in cancer and regulation of mRNA synthesis. Using disease connectivity analysis of 28 hub genes, we found that H. pylori may increase the risk of many extragastric diseases (e.g. cardiovascular disease, hemic and lymphatic diseases and nervous system disease). Altogether, our integrated analysis provided a new method to predict pathogen-human disease connectivity based on miRNA-mRNA interaction network and indicated anti-H. pylori therapy as an effective means of human diseases prevention.

In this study, the authors investigate the security and reliability trade‐off (SRT) performance of a multiuser wireless network, where an eavesdropper attempts to overhear the confidential transmissions between a base station and multiple users under the impact of co‐channel interference. To enhance the SRT performance of the network, the authors propose two joint user and jammer selection schemes, namely the joint optimal user and random jammer selection (JOU‐RJS) scheme and the joint optimal user and optimal jammer selection (JOU‐OJS) scheme. For SRT performance comparison purposes, the traditional multiuser scheduling (TMUS) scheme is also considered. The authors derive closed‐form outage and intercept probability expressions for the JOU‐RJS and JOUOJS schemes. Simulation results show that the SRTs of both JOU‐RJS and JOU‐OJS schemes are better than that of the TMUS scheme, where JOU‐OJS achieves the best SRT performance. Additionally, this study also shows that an expected outage or intercept probability of the TMUS, JOU‐RJS, and JOU‐OJS schemes can be achieved by giving an appropriate overall rate. Finally, the sum of the outage and intercept probability can be minimised through an optimal power allocation between the selected user and friendly jammer for the proposed JOU‐RJS and JOU‐OJS.

This study investigates the problem of low probability of intercept (LPI)‐based distributed multiple‐input multiple‐output (MIMO) radar waveform design against barrage jamming in signal‐dependent clutter and coloured noise. Given the priori knowledge of the extended target impulse response, signal‐dependent clutter, barrage jamming signals and coloured noise, the LPI‐based scheme for optimal radar waveform design is proposed to minimise the total power consumption of the MIMO radar system by optimising the transmitted waveforms of different transmitters with a predetermined mutual information (MI) constraint for target characterisation performance. Firstly, the MI between the received echoes from the target at each receiver and the target impulse response is derived as a practical metric to characterise the parameter estimation performance of a target. Then, the LPI‐based distributed MIMO radar waveform design strategy is developed. The resulting radar waveform optimisation problem is convex and solved analytically, whose solutions represent the optimum power allocation for each transmitter in the MIMO radar system. With the aid of numerical simulations, it is illustrated that to minimise the total transmission power, the optimal waveform should match with the target, clutter, jamming and coloured noise. In addition, it is also demonstrated that the LPI performance of the MIMO radar system can be significantly improved by employing the proposed radar waveform design scheme.

In this paper, we analyze the secrecy outage probability and computation overhead of a multi-user multi-eavesdropper wireless system which is composed of one cluster head (CH) transmitting to multiple users, while multiple eavesdroppers attempt to tap the transmission from CH to multiple users in the presence of co-channel interference (CCI). To achieve high security and low computation overhead, we present two multi-user scheduling schemes, namely, the switch-and-examine combining with post-selection user scheduling (SECpsUS) scheme and the selection combining-based user scheduling (SCbUS) scheme. For the purpose of comparison, the conventional round-robin scheduling (RRS) is also considered as a benchmark scheme. Furthermore, we derive closed-form secrecy outage probability expressions and analyze computation overheads for the conventional RRS, SCbUS, and SECpsUS schemes. Numerical results and Monte Carlo simulations are provided to verify the correctness of our theoretical secrecy outage analysis and to demonstrate the effect of CCI on the system performance. It is shown that the SECpsUS and SCbUS schemes outperform the conventional RRS scheme in terms of their secrecy outage probabilities, where SCbUS achieves the best secrecy outage performance but at cost of the highest computation overhead, while the conventional RRS scheme has no computation overhead with the worst secrecy performance. Moreover, a flexible tradeoff between the secrecy outage performance and computation overhead can be achieved by the proposed SECpsUS scheme by adjusting a so-called switching threshold. In addition, as the number of users increases, the secrecy outage performance of the SECpsUS and SCbUS is improved significantly, whereas no secrecy benefit is achieved by the conventional RRS scheme.

In this paper, we study a multiuser uplink network consisting of one base station (BS), multiple users and one eavesdropper (E), where the users are intended to transmit their confidential messages to BS, while the eavesdropper attempts to tap their transmissions. To improve the transmission secrecy, we propose two friendly jammer selection-aided multiuser scheduling schemes, namely, the random jammer selection-aided multiuser scheduling (RJS-MUS) without knowing the eavesdropper's channel state information (CSI) and the optimal jammer selection-aided multiuser scheduling (OJS-MUS), where the CSIs of eavesdropper are available. For comparison purposes, the conventional non-jammer selection-aided multiuser scheduling (NJS-MUS) scheme is considered as a benchmark. We derive exact and asymptotic closed-form secrecy outage probability expressions for the conventional NJS-MUS as well as proposed RJS-MUS and OJS-MUS schemes. The numerical results show that the proposed RJS-MUS and OJS-MUS schemes with equal power allocation between the selected friendly jammer and scheduled user perform worse than the conventional NJS-MUS approach in terms of the secrecy outage probability in the low signal-to-noise ratio (SNR) region. As the SNR increases, the secrecy outage performance of RJS-MUS and OJS-MUS schemes substantially improves, which is, in turn, better than that of conventional NJS-MUS approach. Moreover, the secrecy advantage of RJS-MUS and OJS-MUS over NJS-MUS becomes more significant with an increasing SNR. Also, it is shown that for both the RJS-MUS and OJS-MUS schemes, a better secrecy performance can be achieved through an optimal power allocation (OPA) between the scheduled user and friendly jammer. In addition, the proposed RJS-MUS and OJS-MUS schemes with OPA strictly outperform the conventional NJS-MUS approach in terms of the secrecy outage probability.

Here, the problem of non‐cooperative game‐theoretic distributed power control is studied in a radar network system based on low probability of intercept (LPI) subject to the signal‐to‐interference‐plus‐noise ratio (SINR) constraint and the transmit power constraint of each radar, where all the radars in the network share the same frequency band. The objective is to improve the LPI performance by reducing the transmit power caused by some radars' SINRs over the specified threshold. First, a novel LPI performance‐oriented utility function is defined as a metric to evaluate power control. Then, consider that radars in the network are self‐interested to maximise their own utilities, the distributed power control problem is formulated as a non‐cooperative game, and an iterative power control algorithm is proposed that converges quickly to the Nash equilibrium (NE) of the non‐cooperative game. Finally, the existence and uniqueness of NE are proved analytically. Numerical simulation results are provided to demonstrate that, compared with other methods, the presented algorithm not only guarantees the minimum SINR requirements of all radars but also improves the LPI performance for radar network.

In this paper, a new method is proposed to refocus a ground moving target in synthetic aperture radar imagery. In this method, range migration is compensated in the 2-D frequency domain, which can easily be implemented by using the complex multiplications, the fast Fourier transform (FFT), and the inverse FFT operations. Then, the received target signal in a range gate is characterized as a quadratic frequency-modulated (QFM) signal. Finally, a novel parameter estimation method, i.e., scaled generalized high-order ambiguity function (HAF), is proposed to transform the target signal into a signal on 2-D time-frequency plane and realize the 2-D coherent integration, where the peak position accurately determines the second- and third-order parameters of a QFM signal. Compared with our previously proposed generalized Hough-HAF method, the proposed method can obtain a better target focusing performance, since it can eliminate the incoherent operations in both range and azimuth directions. In addition, the proposed method is computationally efficient, since it is free of searching in the whole target focusing procedure. Both simulated and real data processing results are provided to validate the effectiveness of the proposed algorithm.

This paper analyzes the secrecy outage probability of a cellular downlink system which consists of multiple users, one base station (BS), and one eavesdropper in the presence of co-channel interferers, where the BS transmits its signals to users which are distributed according to a Poisson point process with a fixed density, while the eavesdropper attempts to tap the transmission from the BS to the users. To enhance the transmission security against eavesdropping, we propose two multiuser scheduling schemes, namely, the partial channel state information (CSI) aided user scheduling (PCSI-US) scheme where only the CSIs of users are available without knowing the co-channel interferers' CSIs and the full CSI aided user scheduling (FCSI-US) scheme which requires the CSIs of both users and interferers. For comparison purposes, the conventional round-robin scheduling scheme is also considered as a baseline. We derive closed-form expressions of the secrecy outage probability for the proposed PCSI-US and FCSI-US as well as conventional round-robin scheduling schemes in co-channel interference (CCI) environments. Numerical results show that the proposed FCSI-US and PCSI-US schemes outperform the conventional round-robin scheduling in terms of their secrecy outage probabilities, where FCSI-US achieves the best secrecy outage performance in CCI environments. It is also demonstrated that increasing the mean number of users has a marginal effect on the secrecy performance of conventional round-robin scheduling, which can significantly decrease the secrecy outage probabilities of PCSI-US and FCSI-US schemes. This further validates the secrecy effectiveness of the proposed user scheduling methods in terms of combating the CCI.

With the wide spread availability and the favourable Doppler resolution, the frequency modulation (FM) commercial radio signals have become attractive for passive radar applications. Passive radar networks using multiple illuminators of opportunity and multichannel receivers have been shown to offer significant performance improvement owing to their advantage of signal and spatial diversities. In this study, the authors compute the joint Cramér–Rao lower bound (CRLB) for the target parameter (delay and Doppler) estimation error utilising FM commercial radio signals as illuminators of opportunity for passive radar network systems, where the non‐coherent and coherent processing scenarios are considered. The numerical simulations are provided to show that the joint CRLB is not only a function of the transmitted waveforms but also of the relative geometry between the target and the passive radar networks for both non‐coherent and coherent cases. The expressions for joint CRLB are an important performance metric for target parameter estimation in FM‐based passive radar networks.

In this study, the problem of low probability of identification (LPID) performance improvement for distributed multiple-radar system (DMRS) is addressed. Firstly, we propose security information factor originating from secrecy capacity to evaluate the LPID performance for DMRS, and derive an explicit closed-form expression of security information factor. Then, a novel LPID enhancement scheme based on security information factor is presented, whose purpose is to maximize the achievable security information factor by optimizing the transmission waveforms and the cooperative jamming spectra with the predefined total transmission energy and cooperative jamming power constraints. Numerical simulations demonstrate that the proposed strategy can effectively achieve the optimal solutions and bring remarkable improvement on the LPID performance for DMRS.

This paper presents an effective metric to evaluate different kinds of low probability of interception (LPI) waveforms. Based on the common view that white noise is the best LPI waveform, the method introduced in this paper first use the asymptotic spectral distribution of Wigner matrix as the property of white noise and use the spectral distribution of the normalized sample covariance matrix as the property of a specific waveform. Then, a numerical approximation of Kullback-Leibler divergence (NA-KLD) is deduced to measure the distance between the two distributions. The NA-KLD is regarded as the metrication to evaluate LPI waveforms. A lower value of NA-KLD represents a better LPI performance. Simulations show that the proposed NA-KLD is effective and robust to evaluate LPI radar waveforms.

This letter studies the mainlobe misorientation problem of the First-Order Steerable Differential Array (FOSDA) in the presence of microphone gain and phase errors, whose response is constructed by a linear combination of monopole and two orthogonal dipoles using a four-element square array. It is shown that the mainlobe orientation of the FOSDA will be undesiredly reversed in the presence of microphone phase errors if the array directivity controlling parameter is less than the corresponding lower bound. In contrast, the effect of microphone gain errors makes little difference when the array directivity controlling parameter varies. Some numerical examples are presented to evaluate the theoretical analysis.

Conventional wideband beamformers are known highly sensitive to gain and phase errors in microphone characteristics, especially for small-sized arrays. Recently, a robust design approach for nearfield wideband beamformers using worst case performance optimization has been proposed. However, the worst case performance optimization criterion might be overly conservative in practice, which may lead to undesired low-pass filtered distortion of target signals. In this paper, a robust design approach for nearfield wideband beamformers using the worst case mean performance optimization is proposed, which is less conservative than the existing approach. Unlike the existing robust design approaches which have no control over array response variance, the presented approach further proposes to impose the passband response variance constraint to enhance the stability of passband array response and hence to reduce the target signal distortion. Moreover, some insights into the properties of array response variance are derived, which are helpful to better understand the robustness characteristics of nearfield wideband beamformers. Design examples demonstrate the effectiveness of the proposed robust design approach.

Cognitive Radio (CR) is an intelligent radio system, which is aware of the communication environment and consequently adapts to it. Orthogonal Frequency Division Multiplexing (OFDM) is a proper and efficient modulation scheme for CR. Adaptive beamforming technique improves CR reliable communication by strengthening the desired signals and rejecting interferences. In this paper, two post IFFT/FFT OFDM adaptive beamformers with iterative weights computing are proposed. The first one directly heritages the spectrum masking concept and deactivates the weights for the OFDM CR subcarriers, which hold the same frequency bands with the Licensed Users (LU). Another beamformer adds extra constraints to those weights instead of masking them, directs the main beam towards the CR users and nulls towards the LU and interferences, and consequently shares the same spectrum bands with LU. Simulation results show that both two OFDM adaptive beamformers guarantee that the CR system not to disturb the LU. Furthermore, it is shown that beamforming with constrained weights provides a lower BER, higher bit rate, more efficient spectrum usage, and suffers no side lobe interference from the LU.