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In this article, a joint node selection and power allocation (JNSPA) strategy based on low probability of intercept (LPI) is proposed in a phased array radar network (PARN) for multitarget tracking (MTT). The joint optimization problem is formulated with a minimization of the total interference energy from a PARN to communication devices under constraints of the tracking level of each target and an LPI value of the system. To solve the proposed nonconvex problem, a two-stage optimization strategy is exploited. Specifically, a heuristic algorithm is first used to determine the target set that needs to be tracked at the current time, and a particle swarm optimization (PSO) with a compression factor is then adopted to solve the subsequent problem. Numerical simulations show that compared with traditional algorithms, the proposed algorithm can effectively improve the spectrum compatibility capability and the LPI performance of the system.

Structural motifs containing nitrogen–nitrogen (N–N) bonds are prevalent in a large number of clinical drugs and bioactive natural products. Hydrazine (N2H4) serves as a widely utilized building block for the preparation of these N–N-containing molecules in organic synthesis. Despite its common use in chemical processes, no enzyme has been identified to catalyze the incorporation of free hydrazine in natural product biosynthesis. Here, we report that a hydrazine transferase catalyzes the condensation of N2H4and an aromatic polyketide pathway intermediate, leading to the formation of a rare N-aminolactam pharmacophore in the biosynthesis of broad-spectrum antibiotic albofungin. These results expand the current knowledge on the biosynthetic mechanism for natural products with N–N units and should facilitate future development of biocatalysts for the production of N–N-containing chemicals.

This paper investigates dynamic hybrid beamforming (HBF) for a dual-function radar-communication (DFRC) system, where the DFRC base station (BS) simultaneously serves multiple single-antenna users and senses a target in the presence of multiple clutters. Particularly, we apply a HBF architecture with dynamic subarrays and double phase shifters in the DFRC BS. Aiming at maximizing the radar mutual information, we consider jointly designing the dynamic HBF of the DFRC system, subject to the constraints of communication quality of service (QoS), transmit power, and analog beamformer. To solve the complicated non-convex optimization, an efficient alternating optimization algorithm based on the majorization-minimization methods is developed. Simulation results verify the advancement of the considered HBF architecture and the effectiveness of the proposed design method.

Measuring accurate force/torque is a key factor for the cooperative robot to realize human–robot collaboration tasks. However, integrating torque sensors into robot joints is still a challenge due to limitations including size, cost, and mismatched communication protocol. Moreover, the crosstalk errors from undetermined external forces and the sinusoidal effect from the harmonic drive (HD) make it difficult to measure torque accurately. This article proposed ultracompact joint torque sensor (JTS) units, addressing the contradiction of the cooperative robot to realize high-resolution force sensing while ensuring proper stiffness. To achieve these goals, a novel spoked structure with double holes is proposed to increase strains and improve stress concentration. Meanwhile, an optimization model is formulated to enhance the resolution with the desired stiffness. In addition, the torque ripple elimination method is introduced, which can properly handle the crosstalk suffered from the HD and thus accurately measure the interest torque. Finally, three sizes of JTS with different loads were implemented with the feature of modularization, lightweight, low cost, and easy to manufacture. Dynamic calibration was applied to a proposed JTS and the performance was also experimentally evaluated. Experimental results showed that the prototype can accurately measure the torque of interest in the range of 170 $\text{N}\cdot \text{m}$ while eliminating crosstalk, and the torque resolution of the small, medium, and large JTS is 0.02, 0.05, and 0.1 $\text{N}\cdot \text{m}$ , respectively, under the premise of ensuring the stiffness. These results and economic costs can promote the application of JTSs in collaborative robots.

Adaptive monopulse algorithm always faces low angle measurement performance in multi-interference environments with low signal-to-noise ratio. To clarify the impact factors, we analyze the performance of monopulse ratio estimation and further derive the Cramer-Rao bound (CRB) for angle estimation. Based on the analysis, a constraint-relaxed adaptive monopulse (RCAM) optimization problem is proposed, and the closed-form solution of the problem is obtained by alternative-direction-method-of-multipliers (ADMM) with fast convergence. Numerical simulations have been provided to demonstrate the effectiveness of the proposed algorithm in improving beamforming and angle estimation.

In this letter, we investigate enhancing the physical layer security (PLS) for the dual-function radar-communication (DFRC) system with hybrid beamforming (HBF) architecture. To enhance PLS in the considered DFRC system, we propose a novel HBF architecture, which introduces a new integrated sensing and security (I2S) symbol. The secure HBF design problem for DFRC is formulated by maximizing the minimum legitimate user communication rate subject to radar signal-to-interference-plus-noise ratio, eavesdropping rate, hardware and power constraints. To solve this non-convex problem, we propose an alternating optimization based method to jointly optimize transmit and receive beamformers. Numerical simulation results validate the effectiveness of the proposed algorithm and show the superiority of the proposed I2S-aided HBF architecture for achieving DFRC and enhancing PLS.

This article addresses the problem of subspace detection in the compound Gaussian (CG) sea clutter with lognormal (LN) texture and structured interference. We proposed three novel subspace detectors by two-step maximum a posteriori (MAP) generalized likelihood ratio test (GLRT), the Rao test, and the Wald test. In the first step, we assume that the texture component and the speckle covariance matrix (CM) are known, and we derive the test statistics of the proposed detectors. Then, in the second step, we substitute the estimated texture component and speckle CM to obtain the adaptive detectors. Furthermore, we exploit the persymmetric property of the speckle CM to improve the detection performance of the proposed detectors. Moreover, we prove the constant false alarm rate (CFAR) properties of the novel subspace detectors with respect to the speckle CM and the scale parameter of the texture component of the non-Gaussian sea clutter. Besides, we verify the detection performance of the proposed subspace detectors by numerical experiments in both simulated and measured sea clutter. The simulation results show that the novel subspace detectors perform better than the comparison detectors in the case of limited training data, mismatched signals, and structured interference.

Hybrid digital/analog architecture and low-resolution analog-to-digital/digital-to-analog converters (ADCs /DACs) are two low-cost implementations for large-scale millimeter wave (mmWave) systems. In this paper, we investigate the problem of constant-envelope transmit beamforming for large-scale multiple-input multiple-output (MIMO) radar system, where the transmit array adopts a hybrid digital/analog architecture with a small number of RF chains and the receive array adopts a fully digital architecture with low-resolution ADCs. We derive the relative entropy between the probability density functions associated with the two test hypotheses under low-resolution ADCs. We formulate our optimization problem by maximizing the relative entropy, subject to the constant envelope and orthogonality constraints. To suboptimally solve the resultant problem, a two-stage framework is developed. In the first stage, we optimize the transmit power at the directions of the target and clutter. In the second stage, an efficient iterative algorithm based on majorization-minimization is presented to obtain the constant-envelope beamformer according to the attained transmit power. Specifically, we apply a quadratic function as the minorizer, leading to a low-complexity solution at each iteration. In addition, to further facilitate low-cost implementation of the constant-envelope beamformer, we consider the problem of one-bit beamforming design and propose an efficient iterative method based on the Nesterov-like gradient method to solve it. Numerical simulations are provided to demonstrate the effectiveness of the proposed schemes.

To enhance the coexistence performance of multiple-input multiple-output (MIMO) radar system and multiuser MIMO communication system with hybrid beamforming architecture, this work proposes a codesign problem regarding the digital and analog beamformers of communication base station, the receive beamformers of downlink users, and the transmit waveform of radar. An information-theoretic criterion is adopted to improve the radar detection performance, while the signal-to-interference-plus-noise ratio requirement is imposed on each downlink user to ensure communication quality. In addition, similarity restriction is also involved to manage some significant radar waveform characteristics. An iterative algorithm is introduced to tackle the resulted nonconvex and NP-hard problem. In each iteration, several subproblems are developed to decompose the original problem and are solved by the lower bound maximization and the alternating direction method of multiplier algorithm. Numerical simulations show that the proposed algorithm allows the objective function to increase monotonically and finally converge to a finite value. It also shows that the codesign scheme can effectively optimize the radar detection performance while ensuring the achievable sum rate and the bit error rate of the communication system.

In millimeter-wave (mmWave) dual-function radar-communication (DFRC) systems, hybrid beamforming (HBF) is recognized as a promising technique utilizing a limited number of radio frequency chains. In this work, in the presence of extended target and clutters, a HBF design based on the subarray connection architecture is proposed for a multiple-input multiple-output (MIMO) DFRC system. In this HBF, the double-phase-shifter (DPS) structure is embedded to further increase the design flexibility. We derive the communication spectral efficiency (SE) and radar signal-to-interference-plus-noise-ratio (SINR) with respect to the transmit HBF and radar receiver, and formulate the HBF design problem as the SE maximization subjecting to the radar SINR and power constraints. To solve the formulated nonconvex problem, the joinT Hybrid bEamforming and Radar rEceiver OptimizatioN (THEREON) is proposed, in which the radar receiver is optimized via the generalized eigenvalue decomposition, and the transmit HBF is updated with low complexity in a parallel manner using the consensus alternating direction method of multipliers (consensus-ADMM). Furthermore, we extend the proposed method to the multi-user multiple-input single-output (MU-MISO) scenario. Numerical simulations demonstrate the efficacy of the proposed algorithm and show that the solution provides a good trade-off between number of phase shifters and performance gain of the DPS HBF.

Recently, deep document clustering has been increasingly attracting interest. However, the design of existing deep document clustering methods is limited to processing only static document datasets because applying these methods to dynamic text documents is challenging as the underlying topics of document datasets are not static but evolve. Deep models must learn the cluster-level representations that are inherited. Thus, methods must be explored to implement the inheritance of cluster-level representations. In this study, we overcome the aforementioned challenges and propose a deep evolutionary document clustering model with an inherited mixed autoencoder (DEDC-IMAE), to discover evolutionary document structures with evolutionary topics in dynamic document datasets. An inherited mixed autoencoder (IMAE) is designed to learn an evolutionary semantic representation of each document considering both the inherited historical topic semantics and the document's own characteristics, to reflect the evolved topic semantics. Using the document evolutionary semantics, a deep evolutionary document clustering (DEDC) module is then investigated to learn a clustering partition that reflects the characteristics of document datasets. Experimental results on a real evolutionary text document dataset showed that DEDC-IMAE achieves better evolutionary clustering results than a variety of baseline models. [ABSTRACT FROM AUTHOR]

As renewable energy penetration grows, traditional power systems face significant challenges due to their intermittency and volatility. Pumped thermal energy storage (PTES) is a potential energy storage technology that has a low specific cost and geographical restriction. In this paper, a PTES system which is coupled with solar photovoltaic thermal (PVT) collectors is proposed to satisfy the demand for cooling, heating and electricity supply, and achieve energy cascade utilization. An ejector refrigeration cycle and the turbine extraction heating are accompanied with a PTES system. Thermodynamic analysis of the system is performed by evaluating the influence of key parameters on system performances for 1 MW power output. The economic analysis adopted levelized cost of energy storage (LCOS), which mainly includes investment costs, operation and maintenance costs and system depreciation. The results show that the maximum amplification of roundtrip efficiency with PVT is 12.04 % compared to the system without PVT. Moreover, the maximum average power generation benefit of PVT is 4.85 %. The increase in cold energy storage tank temperature can effectively improve the roundtrip efficiency of the system. The lower cold energy storage tank temperature and higher hot energy storage tank temperature have a negative impact on system thermal efficiency (ηthermal) but benefits for LCOS. Multi-objective optimization is carried out to obtain the optimal design performance that ηthermaland LCOSare 51.06 % and 0.533$/kWh respectively.

In this letter, we study the Hybrid Beamforming (HBF) design for a Dual-Function Radar-Communication (DFRC) system, which serves Multiple Users (MUs) and detects a target in the presence of signal-dependent clutters, simultaneously. Unlike conventional beamforming strategies, we propose a novel one on the symbol level, which exploits Constructive Interference (CI) to achieve a trade-off between radar and communication using one platform. To implement this novel strategy, we jointly design the DFRC transmit HBF and radar receive beamforming by maximizing the radar Signal to Interference plus Noise Ratio (SINR) while ensuring the Quality of Service (QoS) of downlink communication. To tackle the formulated non-convex problem, we propose an iterative algorithm, which combines the Majorization-Minimization (MM) and Alternating Direction Method of Multipliers (ADMM) judiciously. The numerical experiments indicate that our algorithm yields the CI properly for robust communications and achieves better performance than the conventional HBF benchmarks in both communication bit error rate and radar SINR.

This paper investigates the classification and localization of the mixed far-field sources (FFSs) and near-field sources (NFSs) on a symmetrical uniform linear array and proposes a new mixed source localization algorithm. Firstly, we analyze the persymmetric structure property of the far-field (FF) steering vector in matrix differencing. Based on that, we implement the matrix auto-differencing operation on the fourth-order cumulant (FOC) matrix, which eliminates the contribution of the FF signals from the mixed signals. Based on the reserved near-field (NF) parts, an effective subspace-based is performed to estimate NF parameters. Secondly, to reconstruct the NF FOC matrix, we propose a new method to estimate the NF kurtosis from the non-Hermitian statistics matrix. Then, the related NF components can be removed from the mixed signals to avoid interfering with FF direction-of-arrival (DOA) estimations. Based on the subspace technique, the FF DOAs can be determined by the one-dimensional spectrum search. The proposed algorithm does not require additional classification operations, even when NFSs have the same DOAs as FFSs. Finally, several simulations demonstrate the better estimation performance of the proposed algorithm than existing localization algorithms. [ABSTRACT FROM AUTHOR]

The interrupted sampling repeater jamming (ISRJ) is a coherent interference, and it will result in a large amount of intra-pulse false targets in pulse compression (PC) radar. If the intercepted slices of the ISRJ, named as the screening waveform (SW), are orthogonal to the un-intercepted transmit waveform, named as the detection waveform (DW), the ISRJ can be suppressed by filtering with DW. In this paper, we investigate the problem of ISRJ suppression by jointly designing the DW and SW. Based on the inaccuracy of ISRJ parameter estimation, the joint design problem is formulated by minimizing the integrated sidelobe level (ISL) of the cross-correlation between the ISRJ and DW. The resulting design problem, which involves constraints of constant modulus and orthogonality, is NP-hard, and an alternating optimization like (AltOpt-like) algorithm is developed. Concretely, the SW is first obtained with the aid of the block coordinate descent (BCD) method, then the DW is optimized based on the alternating direction method of multipliers (ADMM) framework. Moreover, in the ADMM framework, low complexity algorithms are devised to solve the subproblems of the primal variables. Numerical simulations are provided to demonstrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In a synthetic aperture radar system, long-time coherent integration for ground moving targets suffers from the complex range migrations (RMs) and Doppler frequency migration (DFM), which lead to a serious degradation of the target detection. To address these problems and obtain the motion parameters of the moving target, a new algorithm based on modified location rotation transform (MLRT) and improved discrete chirp Fourier transform (IDCFT), i.e., MLRT-IDCFT, is proposed in this paper. More concretely, the matched filtering function is first utilized to remove the range curvature (RC) for improving the computational efficiency. After that, the MLRT-IDCFT corrects the residual linear range migration (LRM) through rotating coordinate locations of the echo trajectory and achieves the coherent integration as well as the motion parameter estimation via the IDCFT. The IDCFT exploits the prior information to adaptively adjust the parameter estimation range, which not only improves the parameter resolution but also guarantees the validity of the parameter estimation. Due to the linear transform property, the proposed method can work well under the low signal-to-noise ratio (SNR) environment. Additionally, it has a relatively low computational complexity since the exhaustive searching for acceleration is avoided. Several simulations are provided to demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

It is a common requirement for over-the-horizon (OTH) radar to detect the sea and airborne targets in the same direction simultaneously. The long coherent integration time (CIT) is needed to detect the sea target and the weak moving target such as aircraft. However, the range walk effect (RWE) will occur within the long integration time, leading to a serious degradation of the airborne target detection and tracking. To settle this problem, a new approach based on the multi-channel track-before-detect (MC-TBD) is proposed in this paper. More specifically, to improve the detection performance of the airborne target with unknown speed, multiple processing channels corresponding to different speed ranges are set under the MC-TBD framework. The received data are processed in each channel in parallel. In each channel, the constraints of the speed range are utilized to determine the number of pulses in the CIT of the airborne target. Then, coherent and noncoherent integration processing are performed sequentially based on the moving target detection (MTD) and track-before-detect (TBD). Finally, the detection results and trajectories of all channels are fused to achieve the final detection and tracking of the airborne target. Simulation results show the superiority of the proposed MC-TBD approach over the existing methods in terms of the performance of detection and tracking for airborne target with OTH radar under the background of simultaneous detection of airborne and sea targets in the same direction. [ABSTRACT FROM AUTHOR]

This paper design waveform for high frequency radar to optimize its performances in co-channel interference/colored noise environment. Considering that radar applies the optimal filter for range processing, a novel objective function accounting for both Signal to Interference plus Noise Ratio (SINR) and Integrated Sidelobes Level (ISL) is introduced and the constant modulus constraint on the probing waveform is forced. To resolve the resulting non-convex quartic optimization problem, an efficient iterative algorithm based on Majorization-Minimization (MM) and Pattern Search (PS) is proposed. In each iteration, the proposed algorithm produces a multi-dimension quadratic majorized problem and then splits it into multiple one-dimension problems with closed-form solutions. Simulation results show that the SINR and ISL performances of designed waveform can be flexibly adjusted. Besides, the convergence speed and stability of the proposed algorithm are more satisfactory than the other methods. [ABSTRACT FROM AUTHOR]

Compared with the traditional frost space-time beamformer (STB) with a pre-steering delay processing (PSDP), the method without the PSDP is able to provide a more intuitive observation of the space-frequency response (SFR) for both the desired signal and interference in the beam pattern. In this paper, a new SFR constraint is proposed to guarantee the same time delay for all different frequency components in the desired signal by analyzing the desired signal process of the digital STB. Specifically, in order to make all frequencies in the desired bandwidth meet the SFR constraint, we propose a method to obtain the number of the sample frequency points of the new constraint. After that, the equivalent beamformer with lower complexity is acquired via transforming the SFR constraints into a part of the optimization objectives. On this basis, a robust wideband beamformer against the direction of arrival (DOA) mismatch of the desired signal is established. To be more concretely, in the proposed robust beamformer, the covariance matrix of the interference plus noise and the covariance matrix of the desired signal are reconstructed with the observed data containing the desired signal. Additionally, the reconstructed two matrices are used to estimate the actual desired signal steering vector by considering a maximization of the desired signal output power. Numerical results verify the effectiveness of those proposed algorithms. [ABSTRACT FROM AUTHOR]