Three-dimensional antennas array for the estimation of direction of arrival

Direction of arrival (DOA) estimation of multiple sources using an antenna array becomes very important in wireless communications. It is well known that the quality of the DOA estimation depends on the selected technique and algorithm but it also depends on the geometrical configuration of the antenna array used during the estimation. The authors study the influence of the antenna array configurations on the Cramer?Rao bounds (CRB) of the 2D DOA estimation problem as well as on the performance of the well known MUSIC algorithm. For this we consider the most known planar arrays and we propose a 2-L shaped 3D antennas array. It appears that this 3D antennas array outperforms the other configurations as well as that already proposed in Tayem and Kwon (2005), in terms of both the CRB and the MUSIC root mean square estimation error and also removes ambiguities from the estimation MUSIC pseudo spectrum.     

Neural network method for direction of arrival estimation with uniform cylindrical microstrip patch array

In this study, a new neural network algorithm is proposed for real-time multiple source tracking problem with cylindrical patch antenna array based on a previously reported Modified Neural Multiple Source Tracking (MN-MUST) algorithm. The proposed algorithm, namely cylindrical microstrip patch array modified neural multiple source tracking (CMN-MUST) algorithm implements MN-MUST algorithm on a cylindrical microstrip patch array structure. CMN-MUST algorithm uses the advantage of directive pattern of microstrip patch elements by considering only a part of array elements for a chosen sector. This reduces neural network sizes and also improves the spatial filtering performance. The proposed algorithm improves MN-MUST algorithm in the sense of accuracy and speed while covering the full azimuth range.     

一种适用于低信噪比条件的DOA估计方法

波达方向（Direction of Arrival,DOA）估计技术是信号处理中一个非常活跃的研究领域。但是无论传统的波束形成技术还是现代谱估计技术均适应于高信噪比的环境,当信噪比较低时,这些方法的波达方向（DOA）估计性能急剧下降。根据信号在时间上的强相关性和噪声在时间的弱相关性,提出了一种协方差矩阵的重构方法,该方法能够明显地提高协方差矩阵的信噪比。将新的协方差矩阵应用到最小方差无畸变响应（Minimum Variance Distortionless Re-sponse,MVDR）算法进行DOA估计,改善了传统MVDR算法在低信噪比条件下的DOA估计性能。计算机仿真和定向实验均表明在信噪比较低的环境中可以进行高精度的DOA估计。     

Direction of arrival estimation for uncorrelated and coherent signals with uniform linear array

A novel direction of arrival (DOA) estimation method is proposed with uniform linear array when uncorrelated and coherent signals coexist. The DOAs of uncorrelated signals are first estimated using a new method of modified total least squares estimation of signal parameters via rotation invariance techniques. Afterwards, the contributions of uncorrelated signals are eliminated and a new matrix is constructed based on the spatial difference matrix. Then, the coherent signals can be resolved by performing the forward spatial smoothing scheme on the new matrix. The proposed method can resolve more signals than the array elements with good performance. Simulation results demonstrate the effectiveness and efficiency of the proposed method.     

Classification of brain hemorrhage computed tomography images using OzNet hybrid algorithm

Classification of brain hemorrhage computed tomography (CT) images provides a better diagnostic implementation for emergency patients. Attentively, each brain CT image must be examined by doctors. This situation is time-consuming, exhausting, and sometimes leads to making errors. Hence, we aim to find the best algorithm owing to a requirement for automatic classification of CT images to detect brain hemorrhage. In this study, we developed OzNet hybrid algorithm, which is a novel convolution neural networks (CNN) algorithm. Although OzNet achieves high classification performance, we combine it with Neighborhood Component Analysis (NCA) and many classifiers: Artificial neural networks (ANN), Adaboost, Bagging, Decision Tree, K-Nearest Neighbor (K-NN), Linear Discriminant Analysis (LDA), Naïve Bayes and Support Vector Machines (SVM). In addition, Oznet is utilized for feature extraction, where 4096 features are extracted from the fully connected layer. These features are reduced to have significant and informative features with minimum loss by NCA. Eventually, we use these classifiers to classify these significant features. Finally, experimental results display that OzNet-NCA-ANN excellent classifier model and achieves 100% accuracy with created Dataset 2 from Brain Hemorrhage CT images.     

基于波束域相干信号子空间法的宽带源小尺度基阵定向

在给定的小尺度平面四元阵的基础上,主要研究了波束域相关信号子空间算法(BeamSpaceCoherentSignal-subspaceMethod—BSCSM)在宽带源定向中的应用以及性能分析。用实测的直升机噪声仿真产生各个阵元上输出的宽带信号源,并且使得这组信号具有特定的波达方向(DirectionofArrival—DOA)。分别使用波束域相干信号子空间法(BSCSM)和阵元域的相干信号子空间法(CoherentSignal-subspaceMethod—CSM)与非相干信号子空间法(InCoherentSignal-subspaceMethod—ICSM),通过计算机仿真实验对其进行方位估计。在仿真实验中,可以直观地看出三种方法的性能优劣。根据计算机仿真结果,统计意义上的误差分析,以及对宽带平面波波达角度的角度分辨率等性能指标的分析比较,可以得出在小尺度基阵定向研究中,波束域方法能够获得比其他两种阵元域算法更好的性能。     

Operational estimation of the slant range to an object derived from a minimal volume of measurements by a direction finder

A method of operational estimation of the slant range range of an object traveling rectilinearly and uniformly is described by means of two bearing measurements with the use of a priori information on the probable value of the velocity. An estimator of the efficiency of the method is given.     

矢量水听器阵时频MUSIC算法研究

时频MUSIC算法利用信号的时频分布构造空间时频分布矩阵,并用该矩阵代替传统的相关矩阵进行DOA估计,可以有效抑制噪声和干扰,提高算法的稳健性。时频子空间算法突破了传统子空间算法中阵元数对估计信号个数的限制,时频点包含了信号的时频空三维信息,通过时频点的选择可直接确定信号的频率从而确定阵列流型矩阵。对于宽带信号,在进行方位估计时避免了频域搜索,减少了运算量。将时频MUSIC算法应用于二维矢量水听器垂直线阵中,充分利用矢量水听器的标、矢量信息和信号的时、频信息进行宽带信号的二维波达方位估计。仿真研究验证了算法的有效性。     

大视场阵列探测器归心算法研究

为了实现空间光通信系统小型化、一体化设计,建立了基于阵列探测器和快速偏转镜的一体化跟踪系统,通过分析阵列探测器的光斑位置检测原理提出了一种归心算法。首先通过设置阈值,设计了光斑不完全覆盖探测器的粗归心策略;然后采用数据库查询的方法完成精归心,最后采用无穷积分法使光斑归至原点附近;通过搭建试验平台验证了算法的正确性和可行性。实验结果表明：跟踪视场可达70.3 mrad,较原算法视场扩大了约3倍,跟踪最大误差优于1.8 μrad,为空间光通信系统的进一步工程化应用奠定了基础。     

B超诊断仪凸阵阵元高度方向复合聚焦声场的研究

文章研究B超诊断仪凸阵阵元高度方向复合聚焦声场的计算推导了方便实用的计算公式。然后进行了实验和数值计算,实验结果与理论预测相当吻合,偏差不超过7％。最后在计算机上进行数值仿真,进一步研究了声透镜的几何参数影响声场参数的规律。     

Obstacle identification using the TRAC algorithm with a second-order ABC

We consider obstacle identification using wave propagation. In such problems, one wants to find the location, shape, and size of an unknown obstacle from given measurements. We propose an algorithm for the identification task based on a time-reversed absorbing condition (TRAC) technique. Here, we apply the TRAC method to time-dependent linear acoustics, although our methodology can be applied to other wave-related problems as well, such as elastodynamics. There are two main contributions of our identification algorithm. The first contribution is the development of a robust and effective method for obstacle identification. While the original paper presented criteria for accepting or rejecting regions that enclose the obstacle, we use these criteria to develop an algorithm that automatically identifies the location of the obstacle. The second contribution is the utilization of an improved absorbing boundary condition (ABC) for the identification. We use the second-order Engquist-Majda ABC, and we implement it with a finite element scheme. To our knowledge, this is the first time that the second-order Engquist-Majda ABC is employed with the finite element method, as this boundary condition does not naturally fit in finite element schemes in its original form. Numerical experiments for the algorithms are presented.     

Block-simultaneous direction method of multipliers: a proximal primal-dual splitting algorithm for nonconvex problems with multiple constraints

We introduce a generalization of the linearized Alternating Direction Method of Multipliers to optimize a real-valued function f of multiple arguments with potentially multiple constraints \(g_\circ\) on each of them. The function f may be nonconvex as long as it is convex in every argument, while the constraints \(g_\circ\) need to be convex but not smooth. If f is smooth, the proposed Block-Simultaneous Direction Method of Multipliers (bSDMM) can be interpreted as a proximal analog to inexact coordinate descent methods under constraints. Unlike alternative approaches for joint solvers of multiple-constraint problems, we do not require linear operators \({{\mathsf {L}}}\) of a constraint function \(g({{\mathsf {L}}}\ \cdot )\) to be invertible or linked between each other. bSDMM is well-suited for a range of optimization problems, in particular for data analysis, where f is the likelihood function of a model and \({{\mathsf {L}}}\) could be a transformation matrix describing e.g. finite differences or basis transforms. We apply bSDMM to the Non-negative Matrix Factorization task of a hyperspectral unmixing problem and demonstrate convergence and effectiveness of multiple constraints on both matrix factors. The algorithms are implemented in python and released as an open-source package.     

Conformational analysis of peptides using Monte Carlo simulations combined with the genetic algorithm

In this paper, genetic algorithm (GA) was used to both sample the conformational spaces and thoroughly search the global conformations of peptides. δ-conotoxin PVIA, a peptide of 29 amino acids, was used to test our procedure. The results indicated that this procedure could not only successfully explore a set of the conformational spaces using a hybrid Monte Carlo simulations/GA minimization but also find the global conformations for most of peptides using pure GA minimization.     

利用奇偶量化的图像盲水印算法

在DCT域数字水印算法的基础上,提出了DC系数奇偶量化的盲水印算法。该算法结合JPEG压缩标准,将水印信号隐藏在经过量化后的DC值奇偶性中,在保证水印对于JPEG压缩的鲁棒性的同时,实现了水印的盲提取。同时,水印嵌入前做Arnold置乱预处理,以增强其对于图像剪裁的鲁棒性。此外,预处理时加入的密钥又进一步提高了算法的安全性。实验证明,该算法对于压缩、剪裁、加噪声等具有较好的鲁棒性,尤其对于JPEG压缩,压缩比为29时还可以达到较好的提取效果。     

模板浸润法制备聚合物纳米管阵列

以孔径为200nm的多孔氧化铝膜（AAO）为模板、常规分子量的通用聚合物为原料,采用聚合物溶液或熔体浸润模板纳米孔的物理技术,进行了多种聚合物纳米管的制备研究。结果表明：聚苯乙烯、尼龙66、聚丙烯、ABS、热塑性聚氨酯等多种聚合物纳米管及其纳米管阵列成功制得。运用扫描电子显微镜（SEM）和透射电子显微镜（TEM）观察了纳米管的微观形貌和阵列结构。并探讨了聚合物性质、纳米管制备工艺与纳米管结构的关系,初步探索了多孔模板法制备聚合物纳米管的机理。     

Hybrid finite-element-boundary integral algorithm to solve the problem of scattering from a finite and infinite array of cavities with stratified dielectric coating

This work presents a hybrid finite-element-boundary integral algorithm to solve the problem of scattering from a finite and infinite array of two-dimensional cavities engraved in a perfectly electric conducting screen covered with a stratified dielectric layer. The solution region is divided into interior regions containing the cavities and the region exterior to the cavities. The finite-element formulation is applied only inside the interior regions to derive a linear system of equations associated with unknown field values. Using a two-boundary formulation, the surface integral equation employing the grounded dielectric slab Green's function in the spatial domain is applied at the opening of the cavities as a boundary constraint to truncate the solution region. Placing the truncation boundary at the opening of the cavities and inside the dielectric layer results in a highly efficient solution in terms of computational resources, which makes the algorithm well suited for the optimization problems involving scattering from grating surfaces. The near fields are generated for an array of cavities with different dimensions and inhomogeneous fillings covered with dielectric layers.     

Hybrid finite element-boundary integral algorithm to solve the problem of scattering from a finite array of cavities with multilayer stratified dielectric coating

This work presents a hybrid finite element-boundary integral algorithm to solve the problem of scattering from a finite array of two-dimensional cavities engraved in a perfectly electric conducting screen covered with multilayer stratified dielectric coating. The solution region is divided into interior regions containing the cavities and the region exterior to the cavities. The finite element formulation is applied only inside the interior regions to derive a linear system of equations associated with unknown field values. Using a two-boundary formulation, the surface integral equation employing a closed-form multilayer Green's function in the spatial domain is applied at the opening of the cavities as a boundary constraint to truncate the solution region. The closed-form Green's function in the spatial domain for multilayer planar coating is expressed in terms of complex images using the generalized pencil-of-function method in conjunction with a two-level sampling approach. Placing the truncation boundary at the opening of the cavities and inside the dielectric coating results in a highly efficient solution in terms of computational resources, which makes the algorithm well suited for optimization problems involving scattering from grating surfaces. The near fields are generated for array of cavities with different dimensions and inhomogeneous fillings covered with dielectric layers.