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Cross-eye jamming is an effective angular deception jamming technique used for countering monopulse radars. With the need of countermeasure against active radar seekers, the research on cross-eye jamming becomes a hot research topic in electronic war. This study overviews the cross-eye jamming with regard to jamming theories, equipment, application problems, and current research trends to offer comprehensive knowledge and future research ideas.

Broadband near-infrared (NIR) phosphors have received increasing attention for fabricating NIR light sources. In this article, based on our predictions of heavy Mn-doped models obtained using DFT calculations, we successfully synthesize and characterize manganese-based magnetoplumbite-type La(Zn,Mn)Al11O19 phosphors, which crystallize into a hexagonal structure with space-group P63/mmc. Under excitation at 450 nm, it was found that LaZn0.7Mn0.3Al11O19 and LaZn0.2Mn0.8Al11O19 had the optimal emission intensity and the maximum quantum efficiencies were 99% and 55%, respectively. An anomalous near-infrared (NIR) emission band at ∼730 nm is observed for the LaZnAl11O19 host with heavy Mn2+ doping. The density functional theory calculations and transient and steady-state luminescence investigation suggest that this unusual NIR emission band comes from the Mn2+–Mn2+ dimers. Moreover, the as-prepared phosphor, being integrated into high-powered photonic devices, could operate at high temperature without degeneration, due to the great advantage of the phosphor-in-glass (PiG) approach. Consequently, our study not only develops a viable strategy for synthesising innovative NIR phosphors, but also sheds light on the development of high-power photonic devices and procedures. [ABSTRACT FROM AUTHOR]

Developing chemically and thermally stable, highly efficient green-emitting inorganic phosphors is a significant research field in solid-state lighting. In this work, we successfully tailor the properties of an yttrium silicate based Na3(Y,Sc)Si3O9:Eu2+ phosphor as a highly efficient green phosphor via crystal field engineering. The quantum efficiency (QE) and thermal stability of Na3(Y,Sc)Si3O9:Eu2+ were increased by 33% and 35%, respectively, via the combination of structure and bandgap engineering. Meanwhile, persistent luminescence (PersL) was observed, followed by a more thorough investigation of the relationship between the intensity of afterglow and Sc3+ concentration. Accordingly, the excitation temperature-dependent and fading thermoluminescence experiments are conducted, and the trap properties are deeply studied by the initial rising method. The results reveal the PersL mechanism and the significant role of Sc3+ as substitute ions. These results clearly indicate that our proposed designing concept of PersL materials are indeed effective and feasible, and the as-prepared Na3Y0.5Sc0.5Si3O9:Eu2+ phosphors are certainly promising for multifunctional applications. [ABSTRACT FROM AUTHOR]

Transparent glass-ceramics are a highly attractive class of materials for photonic applications. Transition metal ions are promising candidates for luminescence centers thanks to the sensitivity of the ligand ions to d–d electron transition. Here, broadband second near-infrared (NIR-II) photoluminescence was achieved via precipitation of ZnGa2O4:Ni2+ nanocrystals within a zinc gallium–silicate glass matrix by a crystallization process. Excited by 260 nm UV photons, ZnGa2O4:Ni2+ GC displays NIR-II emission peaking at 1240 nm and has a full width at half maximum wider than 288 nm, attributed to 3T2g(3F) → 3A2g(3F) electronic transition of octahedrally coordinated Ni2+ ions. Moreover, broad persistent luminescence of Ni2+ ions can be effectively obtained after irradiation in UV light. Based on the electron paramagnetic resonance spectra and a thermoluminescence method, a physical model was constructed to demonstrate the mechanism of persistent luminescence. This developed afterglow luminescent glass-ceramic exhibits potential applications in biological imaging. [ABSTRACT FROM AUTHOR]

Transparent glass-ceramics are a highly attractive class of materials for photonic applications. Transition metal ions are promising candidates for luminescence centers thanks to the sensitivity of the ligand ions to d–d electron transition. Here, broadband second near-infrared (NIR-II) photoluminescence was achieved via precipitation of ZnGa2O4:Ni2+ nanocrystals within a zinc gallium–silicate glass matrix by a crystallization process. Excited by 260 nm UV photons, ZnGa2O4:Ni2+ GC displays NIR-II emission peaking at 1240 nm and has a full width at half maximum wider than 288 nm, attributed to 3T2g(3F) → 3A2g(3F) electronic transition of octahedrally coordinated Ni2+ ions. Moreover, broad persistent luminescence of Ni2+ ions can be effectively obtained after irradiation in UV light. Based on the electron paramagnetic resonance spectra and a thermoluminescence method, a physical model was constructed to demonstrate the mechanism of persistent luminescence. This developed afterglow luminescent glass-ceramic exhibits potential applications in biological imaging. [ABSTRACT FROM AUTHOR]

Coprime arrays (CPAs) have been found to be an effective configuration for adaptive beamforming (ABF). However, most ABF methods for CPAs are embedded with the spatial spectrum estimation technique, and therefore they usually deteriorate in the case of low signal‐to‐noise ratio (SNR), especially without prior information of interferences. To address this issue, a robust ABF method for CPAs via atomic‐norm‐based sparse recovery is proposed. This method begins with initialised virtual array interpolation to avoid aperture loss caused by 'holes', which is subsequently transformed to a matrix completion and denoising issue via a Toeplitz step. With the matrix's Hermitian Toeplitz structure and the intrinsic sparsity of interferences, sparse recovery for the interference covariance matrix is introduced by subtracting the target signal and noise from the received signal and implemented by atomic‐norm minimisation. Concretely, this non‐convex process is decomposed into two convex steps and solved iteratively. Unlike previous methods, this method can interpolate the virtual array and estimate the steering vector of the target and the noise power simultaneously; consequently, the interference‐plus‐noise covariance matrix is reconstructed with merely some trivial entry selections without the need for the spatial spectrum. Furthermore, the optimality conditions and boundedness in this method are proven theoretically. Simulation results demonstrate the effectiveness of the proposed method and its advantages over previous methods under those non‐ideal conditions. [ABSTRACT FROM AUTHOR]

By introducing halogens to the A/Ga/Q (A = Na, K; Q = S, Se) system, one new chalcohalide namely Na2GaS2Cl was successfully obtained. It crystallizes in the orthorhombic space group Cmcm (63). Na2GaS2Cl has a layered structure consisting of two dimensional [GaS2]∞ layers which are stacked in "face to face" and "back to back" arrays and separated by Na+ and Cl− ions. Interestingly, supertetrahedral building units [Ga4S10] (T2) which are rarely found in metal chalcogenides and metal chalcohalides are formed in this structure. Moreover, the distances of two adjacent layers are around four times larger than the ionic radius of the Na+ ion, which is very likely to provide a perfect environment for the storage and migration of Na+ ions. In particular, the volume concentration of the Na+ cations in this compound is as high as 1.54 × 1022 cm−3. The UV-vis-NIR spectroscopy measurement reveals that the optical band gap of this title compound is 3.06 eV. The electronic structural calculations on Na2GaS2Cl show that the band gap is mainly determined by the [GaS4] groups and Na–Cl ionic bonding. [ABSTRACT FROM AUTHOR]

In this paper, the convolution neural networks (CNN) are developed for the classification and localization of mixed near-field and far-field sources by using the geometry of symmetric nested array. We first transform the received data into frequency domain. Then, we preprocess the phase difference matrix to decouple mixed sources. Considering that the counter-diagonal elements in the phase difference matrix only contain the direction of arrival (DOA) parameter of each mixed source, we utilize the upper right elements as the input of CNN to estimate the DOA of each mixed source. In order to avoid the influence of noise, we construct a particular range vector without the estimated DOA and employ the output of autoencoder to classify the mixed sources. Finally, we further exploit the output of autoencoder and apply the CNN without bias vectors to estimate the range of near-field sources. In contrast to the traditional learning-based approaches regarding the parameter estimation as a classification problem, the proposed approach considers the parameter estimation as a regression problem and can significantly reduce the complexity of networks. Simulation results demonstrate that the proposed learning-based method can improve the precision for the mixed source localization. Moreover, the proposed method is robust to the off-grid parameters and the different numbers of mixed sources. [ABSTRACT FROM AUTHOR]

This article addresses the problem of joint direction of departure (DOD) and direction of arrival (DOA) estimation with nested bistatic multiple input multiple output (MIMO) radar using tensor decomposition. We first employ the two-level nested transmit and receive arrays to develop the sum-difference coarray for constructing the Toeplitz and spatial smoothing matrices. We then generalize the three-way tensor model from DOD and DOA dimensions, and derive the optimized tensor by maximizing the number of detectable targets, where the existing COMFAC technique is exploited for angle estimation. We show that the proposed method can identify more targets and achieve better performance by enforcing the three-way structure information compared with the subspace-based algorithms. We also show that the conventional tensor model is just a special case. Finally, we derive the coarray Cramér–Rao Bound (CRB) for the nested MIMO radar, and also conduct a study for the conditions under which the CRB exists. Numerical simulations are provided to validate the theoretical analysis and demonstrate the performance improvement. [ABSTRACT FROM AUTHOR]

In recent years, with the popularity of mobile devices and mobile Internet, more and more social media sites are growing in an explosive way. Therefore, the social hot event will be rapidly fermented by the interaction of a large number of network users, and a large amount of multimedia data (such as texts, images and videos) will be generated. Therefore, it is important and necessary to conduct the research of multimedia social event analysis to know the evolutionary trend of social event over time automatically. This paper provides a survey and summarizes major progresses in multimedia social event analysis. We focus on four areas: (1) multimedia social event representation; (2) multimedia social event detection and tracking; (3) multimedia social event evolutionary analysis; and (4) multimedia social event topic mining. [ABSTRACT FROM AUTHOR]

Recent research treats radar emitter classification (REC) problems as typical closed-set classification problems, i.e., assuming all radar emitters are cooperative and their pulses can be pre-obtained for training the classifiers. However, such overly ideal assumptions have made it difficult to fit real-world REC problems into such restricted models. In this paper, to achieve online REC in a more realistic way, we convert the online REC problem into dynamically performing subspace clustering on pulse streams. Meanwhile, the pulse streams have evolving and imbalanced properties which are mainly caused by the existence of the non-cooperative emitters. Specifically, a novel data stream clustering (DSC) algorithm, called dynamic improved exemplar-based subspace clustering (DI-ESC), is proposed, which consists of two phases, i.e., initialization and online clustering. First, to achieve subspace clustering on subspace-imbalanced data, a static clustering approach called the improved ESC algorithm (I-ESC) is proposed. Second, based on the subspace clustering results obtained, DI-ESC can process the pulse stream in real-time and can further detect the emitter evolution by the proposed evolution detection strategy. The typically dynamic behavior of emitters such as appearing, disappearing and recurring can be detected and adapted by the DI-ESC. Extinct experiments on real-world emitter data show the sensitivity, effectiveness, and superiority of the proposed I-ESC and DI-ESC algorithms. [ABSTRACT FROM AUTHOR]

As one of the most important features for human perception, contours are widely applied in graphics and mapping applications. However, it is considerably challenging to extract contours from large-scale point clouds due to the irregular distribution of point clouds. In this letter, we propose a 3-D-guided multiconditional residual generative adversarial network (3-D-GMRGAN), the first deep-learning framework to generate contours for large-scale outdoor point clouds. To make the network handle huge amounts of points, we operate contours in the parametric space rather than raw point space, associated with a parametric chamfer distance. Then, to gather contour features from potential positions and avoid the huge solution space, we propose a guided residual generative adversarial framework, by utilizing a simple feature-based method to get the “over extraction” potential contour distribution. Experiments demonstrate that the proposed method is able to generate contours efficiently for large-scale point clouds, with fewer outliers and pseudo contours compared with state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

Due to the maternal inheritance of cytoplasm, using foxtail millet [ Setaria italica (L.) P. Beauv.] male sterile lines with a single cytoplasmic source as the female parent will inevitably lead to a narrow source of cytoplasm in hybrids, which may make them vulnerable to infection by cytoplasm-specific pathogens, ultimately leading to destructive yield losses. To assess cytoplasmic genetic diversity in plants, molecular markers derived from chloroplast DNA (cpDNA) have been used. However, such markers have not yet been applied to foxtail millet. In this study, we designed and screened nine pairs of polymorphic foxtail millet-specific primers based on its completely sequenced cpDNA. Using these primers, we analyzed the genetic diversity and cytoplasmic types of 130 elite foxtail millet parental lines collected in China. Our results revealed that the cytoplasmic genetic diversity of these accessions was low and needs to be increased. The parental lines were divided into four cytoplasmic types according to population structure analysis and a female parent-derivative evolutionary graph, indicating that the cytoplasmic types of elite foxtail millet lines were rather limited. A principal component analysis (PCA) plot was linked with the geographic and ecological distribution of accessions for each cytoplasmic type, as well as their basal maternal parents. Collectively, our results suggest that enriching cytoplasmic sources through the use of accessions from diverse ecological regions and other countries as the female parent may improve foxtail millet breeding programs, and prevent infection by cytoplasm-specific pathogens. [ABSTRACT FROM AUTHOR]

Coherent source localization is a common problem in signal processing. In this paper, a sparse representation method is considered to deal with two-dimensional (2D) direction of arrival (DOA) estimation for coherent sources with a uniform circular array (UCA). Considering that objective function requires sparsity in the spatial dimension but does not require sparsity in time, singular value decomposition (SVD) is employed to reduce computational complexity and ℓ2 norm is utilized to renew objective function. After the new objective function is constructed to evaluate residual and sparsity, a second-order cone (SOC) programming is employed to solve convex optimization problem and obtain 2D spatial spectrum. Simulations show that the proposed method can deal with the case of coherent source localization, which has higher resolution than 2D MUSIC method and does not need to estimate the number of coherent sources in advance. [ABSTRACT FROM AUTHOR]

Under uniform circular array, by employing some algebraic schemes to exploit the phase information of receiving data and further estimate the source's three-dimensional (3D) parameters (azimuth angle, elevation angle, and range), a series of novel phase-based algorithms with low computational complexity have been proposed recently. However, when the array diameter is larger than source's half-wavelength, these algorithms would suffer from phase ambiguity problem. Even so, there always exist certain positions, where the source's parameters can still be determined with nonambiguity. Therefore, this paper first investigates the zone of ambiguity-free source 3D localization using phase-based algorithms. For the ambiguous zone, a novel ambiguity resolution algorithm named ambiguity traversing and cosine matching (ATCM) is presented. In ATCM, the phase differences of centrosymmetric sensors under different ambiguities are utilized to match a cosine function with sensor number-varying, and the source's unambiguous rough angles can be derived from amplitude and initial phase of the cosine function. Then, the unambiguous angles are employed to resolve the phase ambiguity of the phase-based 3D parameter estimation algorithm, and the source's range as well as more precise angles can be achieved. Theoretical analyses and numerical examples show that, apart from array diameter and source's frequency, the sensor number and spacing of employed sensors are two key factors determining the unambiguous zone. Moreover, simulation results demonstrate the effectiveness and satisfactory performance of our proposed ambiguity resolution algorithm. [ABSTRACT FROM AUTHOR]

The effect of platform skin return on multiple-element retrodirective cross-eye jamming (MRCJ) system is investigated, allowing the differences between multiple jammer loops to be considered. The jammer antennas employ a linear array with a common center. The median value of the total cross-eye gain and the jamming-to-signal ratio (JSR) are derived to explore their relationship. Simulation results demonstrate the performance of MRCJ in the presence of platform skin return. [ABSTRACT FROM PUBLISHER]

Due to the additional degrees of freedom, multiple-element cross-eye jamming (MCJ) can reduce tolerance sensitivity and increase the effective sector angle. In this paper, we investigate multiple-element retrodirective cross-eye jamming (MRCJ) based on the retrodirective linear array. The monopulse error and cross-eye gain are derived via trigonometric approximations. Moreover, excellent performances of MRCJ in terms of induced angular error and tolerance requirements are demonstrated in simulation results. [ABSTRACT FROM PUBLISHER]

Cross-eye jamming is an angular deception jamming technique against monopulse radar. Multiple-element retrodirective cross-eye jamming (MRCJ) as an improved method, uses a retrodirective antenna array with multiple antenna elements in a cross-eye jammer and can obtain better jamming performance. However, the practical MRCJ system employing a linear antenna array becomes ineffective when the threat radar appears in the antenna array's end-fire direction. To meet multiple threats from different directions and provide continuous jamming, MRCJ employing a circular antenna array (C-MRCJ) is proposed after defining the modulation direction of system parameters. Optimal configuration of C-MRCJ providing stable jamming performance is discussed. The number of the jammer loops is analyzed under considerable jamming performance and moderate hardware cost. [ABSTRACT FROM AUTHOR]

Climate change has caused severe drought, affecting global crop production. Broomcorn millet is a drought-tolerant crop preferred for water-saving agriculture because of its short life cycle and high water use efficiency. This study evaluated the drought tolerance of 300 broomcorn millet varieties from 21 sources under well-watered, semi-arid conditions (Yulin, Shaanxi, China) and unwatered, arid conditions (Dunhuang, Gansu, China). Two broomcorn millet varieties with contrasting drought tolerance attributes, DT 43 (drought-tolerant) and DS 190 (drought-sensitive), were selected for comparative physiological and transcriptional assessment under the two drought stress conditions (polyethylene glycol 6000 [PEG-6000] and soil drought) and corresponding melatonin treatments. The two forms of drought stress decreased photosynthetic capacity and triggered transcriptome reprogramming in both broomcorn millet cultivars. However, PEG induced a more 'severe' and 'rapid' drought stress than the 'milder' and 'slower' soil moisture drought stress. Moreover, PEG stress caused severe growth arrest and photosynthesis inhibition, especially for DS190. About 61.38% and 48.78% differentially expressed genes (DEGs) were up-regulated in DT 43 under PEG and soil drought stresses, respectively. Moreover, 74.31% and 54.59% DEGs were up-regulated in DS 190 under PEG and soil drought stresses, respectively. Most DEGs in DT 43 were significantly enriched in hormone signal transduction, mitogen-activated protein kinase (MAPK) signaling, and carbon metabolism pathways. However, most DEGs in DS 190 were enriched in plant photosynthesis, chlorophyll metabolism, and nitrogen metabolism pathways. Moreover, melatonin enhanced the drought resistance of the two genotypes, increasing photosynthetic and antioxidant enzyme activity and thus mitigating transcription response. Therefore, these unique mechanisms of enhancing drought resistance can improve bioenergy crops, especially for the cultivation of drought-tolerant varieties. [Display omitted] • Drought-tolerant broomcorn millet is a suitable crop model for drought tolerance simulation. • Drought-tolerant broomcorn millet adapts to drought by regulating plant hormone signal transduction and mitogen-activated protein kinase signaling. • Polyethylene glycol induces a more 'severe and 'rapid' drought stress than 'milder' and 'slower' soil drought stress. • Melatonin enhances drought resistance by increasing photosynthetic and antioxidant capacities. [ABSTRACT FROM AUTHOR]