Sound Source Localization Based on SRP-PHAT Spatial Spectrum and Deep Neural Network

Microphone array-based sound source localization(SSL)is a challenging task in adverse acoustic scenarios.To address this,a novel SSL algorithm based on deep neural network(DNN)using steered response power-phase transform(SRP-PHAT)spatial spectrum as input feature is presented in this paper.Since the SRP-PHAT spatial power spectrum contains spatial location information,it is adopted as the input feature for sound source localization.DNN is exploited to extract the efficient location information from SRP-PHAT spatial power spectrum due to its advantage on extracting high-level features.SRP-PHAT at each steering position within a frame is arranged into a vector,which is treated as DNN input.A DNN model which can map the SRP-PHAT spatial spectrum to the azimuth of sound source is learned from the training signals.The azimuth of sound source is estimated through trained DNN model from the testing signals.Experiment results demonstrate that the proposed algorithm significantly improves localization performance whether the training and testing condition setup are the same or not,and is more robust to noise and reverberation.

NOVEL SPECTRUM SENSING METHOD BASED ON THE SPATIAL SPECTRUM FOR COGNITIVE RADIO SYSTEMS

Spectrum sensing is the key problem for Cognitive Radio(CR) systems.A method based on the Peak-to-Average Amplitude-Ratio(PAAR) of the Spatial Spectrum(SS) of the received signals is proposed to sense the available spectrum for the cognitive users with the help of the multiple antennas at the receiver of the cognitive users.The greatest advantage of the new method is that it requires no information of the noise power and is free of the noise power uncertainty.Both the simulation and the analytical results show that the proposed method is robust to noise uncertainty,and greatly outperform the classical Energy Detector(ED) method.

Effect of spatial spectrum overlap on Fourier ptychographic microscopy

Fourier ptychographic microscopy(FPM)is a newly developed imaging technique which stands out by virtue of its high-resolution and wide FOV.It improves a microscope's imaging perfor-mance beyond the diffraction limit of the employed optical components by illuminating the sample with oblique waves of different incident angles,similar to the concept of synthetic aperture.We propose to use an objective lens with high-NA to generate oblique illuminating waves in FPM.We demonstrate utilizing an objective lens with higher NA to iluminate the sample leads to better resolution by simulations,in which a resolution of 0.28 pum is achieved by using a high-NA illuminating objective lens(NA=1.49)and a low-NA collecting objective lens(NA=0.2)in coherent imaging(λ=488 nm).We then deeply study FPM's exact relevance of convergence speed to spatial spectrum overlap in frequency domain.The simulation results show that an overlap of about 60%is the optimal choice to acquire a high-quality recovery(520*520 pixels)with about 2 min's computing time.In addition,we testify the robustness of the algorithm of FPM to additive noises and its suitability for phase objects,which further proves FPM's potential application in biomedical imaging.

SPATIAL SPECTRUM ESTIMATION OF COHERENT SOURCES IMPINGING ON NONUNIFORM ARRAYS

The problem of bearing estimation of coherent signal impingiog on an array ofarbitrary geometry is studied.Both approaches are developed,the first one synthesizes theobserved array data into the outputs of a linear uniform array and then processes them viaconventional techniques such as spatial smoothing etc.The second approach is based on theinvariant subspace rotation operation which is equivalent to the translational displacement ofthe artay,linearly independent signal vectors are obtained thereby to span perfectly the signalsubspace.As compared with the conventional processing techniques,the approach based oninvariant subspace rotation does not lead to an effective decrease in aperture size and thereforea decrease in resolution capability.The computer simulations are conducted to demonstrate theeffectiveness of the presented approaches.

A detecting method for line-spectrum target by fusing output DC jump to fluctuations ratio of sub-band spatial spectrum and beam space

The low frequency line components of the radiated noise from an underwater target usually have both high spectrum level and sustained stability. This feature could be used to increase the detection performance of conventional broadband energy integration method. The required spectrum level is theoretically discussed when the detection performance of the known line detection is better than that of broadband energy integration method. Under the condition of the target can be detected in line spectrum band, the relationship between the line spectrum level and signal to noise ratio （SNR） is also discussed. This paper proposes a line spectrum target detection method that a matrix using DC jump to fluctuations ratios of sub-band spatial spectrum and beam space output is constructed. This matrix acts as a filter that the line spectrum target with certain frequency and azimuth is passed at most. By fusing with the other sub band results, the conventional detection performance can be improved. At the same time, the applicable condition and detection performance are analyzed in the paper. The simulation and the sea trial data processing results show that the algorithm can effectively extract weak goal line spectrum target under the condition of multi-interference. The algorithm doesn＇t need multi-frame statistics and the detection performance is closer to the optimal line spectrum method.

Spectrum spatial structure characteristic analysis of remote sensing alteration information and interference factors

Based on the statistical characteristics of remote sensing data, the spatial geometric structure characteristics of spectral data and distribution of background, interference and alteration information in characteristic space were researched through the analysis of two-dimensional and three-dimensional scatter diagrams. The results indicate that the hyper-space of remote sensing multi-data aggregation belongs to low-dimensional geometric structure, i.e. hyperplane form, and anomalous point groups including alteration information usually dissociate out of hyperplane. Scatter diagrams of remote sensing data band are mainly presented as two distribution forms of single-ellipse and dual-ellipse. Clarifying the relations of three objects of background, disturbance and alteration information in remote sensing images provides an important technical thought and guidance for accurately detecting and extracting remote sensing alteration information.

Spatio-Temporal Population Density and Spatial Dynamic Spectrum Allocation

A realistic population density distribution scenario in conjunction with the spatial dynamic spectrum allocation （DSA） is taken into account to mitigate the spectrum wastage in terms of extra guard bands. For the insertion of the extra guard bands, an efficient strategy based on self-assessment is applied to each victim cell individually and independently. Consequently, it is no more required to spread the extra guard band over the whole DSA region. Simulation results StlOW an improvement of 3% -4% in percentage of satisfied users for Universal Mobile Telecommunications System （UMTS） network and 4%-5% for Digital Video Broadcasting Terrestrial （DVB-T） network.

2-D SPATIAL-SPECTRUM ESTIMATION FORWIDE-BAND SOURCES BASED ON INTERPOLATED CIRCULAR ARRAYS

In array signal processing, 2-D spatial-spectrum estimation is required to determine DOA of multiple signals. The circular array of sensors is found to possess several nice properties for DOA estimation of wide-band sources. C. U. Padmini, et al.(1994) had suggested that the frequency-direction ambiguity in azimuth estimation of wide-baud signals received by a uniform linear array (ULA) can be avoided by using a circular array, even without the use of any delay elements. In 2-D spatial-spectrum estimation for wide-band signals, the authors find that it is impossible to avoid the ambiguity in source frequency-elevation angle pairs using a circular array. In this paper, interpolated circular arrays are used to perform 2-D spatial-spectrum estimation for wide-band sources. In the estimation, a large aperture circular array (Υ】λmin/2) is found to possess superior resolution capability and robustness.

A new spatial coherence model and analytical coeffi cients for multi-support response spectrum combination

In this paper, a new spatial coherence model of seismic ground motions is proposed by a fitting procedure. The analytical expressions of modal combination （correlation） coefficients of structural response are developed for multi-support seismic excitations. The coefficients from both the numerical integration and analytical solutions are compared to verify the accuracy of the solutions. It is shown that the analytical expressions of numerical modal combination coefficients are of high accuracy. The results of random responses of an example bridge show that the analytical modal combination coefficients developed in this paper are accurate enough to meet the requirements needed in practice. In addition, the computational efficiency of the analytical solutions of the modal combination coefficients is demonstrated by the response computation of the example bridge. It is found that the time required for the structural response analysis by using the analytical modal combination coefficients is less than 1/20 of that using numerical integral methods.

Media Access with Spatial Reuse for Cooperative Spectrum Sensing

The increasing interest for wireless communication services and scarcity of radio spectrum resources have created the need for a more flexible and efficient usage of the radio frequency bands. Cognitive Radio (CR) emerges as an important trend for a solution to this problem. Spectrum sensing is a crucial function in a CR system. Cooperative spectrum sensing can overcome fading and shadowing effects, and hence increase the reliability of primary user detection. In this paper we consider a system model of a dedicated detect-andforward wireless sensor network (DetF WSN) for cooperative spectrum sensing with k-out-of-n decision fusion in the presence of reporting channels errors. Using this model we consider the design of a spatial reuse media access control (MAC) protocol based on TDMA/OFDMA to resolve conflicts and conserve resources for intra-WSN communication. The influence of the MAC protocol on spectrum sensing performance of the WSN is a key consideration. Two design approaches, using greedy and adaptive simulated annealing (ASA) algorithms, are considered in detail. Performance results assuming a grid network in a Rician fading environment are presented for the two design approaches.

非均匀强激光场下正负电子对的产生

随着强激光技术领域的不断突破,使得能量转化成物质的施温格过程的实验指日可待.在这样的背景下,在接近实际强激光的模型中理论研究施温格效应至关重要.本文采用量子场论模拟方法在非均匀电场中研究施温格效应的空间特性.首先,发现在能量保持不变的情况下电场的空间尺度显著影响正负电子对的产生率、动量和空间分布.正负电子对的动量和空间分布显示,当电场的空间尺度增大时,因为电场强度变小,所以产生的正负电子对无法及时被分开,抑制正负电子对的产生.最后,用连续性方程研究正负电子对的产生位置分布,发现正负电子对的产生位置分布与电场强度分布是对应的,电子和正电子的产生位置分离一个康普顿波长.此研究结果展示了施温格效应的空间特性,同时解释了弱电场下施温格效应的抑制机制.这些结论在人们常采用的均匀电场近似研究中无法得到.我们的研究对检测施温格实验中的正负电子对具有重要的指导意义.

Temporal-spatial Variation Characteristics of the Extreme Precipitation Days over South China from 1961 to 2010

[ Objective] The research aimed to analyze temporal-spatial variation characteristics of the extreme precipitation days over South China from 1961 to 2010. [ Method] Based on the daily precipitation data in meteorological stations over South China, extreme precipitation thresholds were determined according to the percentiles distribution for different stations. Temporal-spatial variation characteristics of the extreme precipitation days over South China were studied by the methods of fuzzy clustering, trend coefficient, wavelet analysis and cross spectrum analysis, etc. [ Re- suit] Four sub-regions were identified over South China. They were respectively Nanling area, west Guangxi area, Coast area and Hainan area. Occurrence seasons of the extreme precipitations in each sub-region were significantly different. Extreme precipitation clays in four sub-regions all had increase trends, and those of Nanling area and Coast area were significant. From wavelet analysis and cress spectrum analysis, there were significant periodic variation characteristics. Extreme precipitation days in each sub-region all had significant same-phase evolution trends at the peri- od of 2 -5 years, but backward time length was different. [ Conclusion] The research provided background materials for forecast and influence as- sessment of the extremely heavy precipitation over South China.

一种波段聚类和多尺度结构特征融合的高光谱图像分类模型

高光谱图像包含丰富的地物信息,在农业、工业和军事等领域应用广泛。因此,高光谱图像的识别与分类是一项重要的研究课题。然而,高光谱图像存在光谱维度高、噪声大、标记样本有限等问题,并未取得很好的分类效果。针对以上问题,提出一种波段聚类和多尺度结构特征融合的高光谱图像分类模型(ASPS-MRTV)。该方法主要包括以下几个步骤,首先,对高光谱数据进行归一化处理,将归一化后的三维图像按光谱维等分为n个子空间;其次,采用粗细划分策略构造自适应子空间光谱特征提取框架,将每个空间波段拉伸为一维向量后用信息散度构造波段的相似性矩阵,按照聚类的思想对n个子空间进行自适应;然后,将每个自适应子空间的光谱波段平均值进行叠加,形成光谱特征;最后,对所得到的光谱特征数据利用多尺度相对全变分技术提取结构特征。为了增强样本的线性可分性,在数据堆叠之后进行核主成分分析,最终形成空谱特征。对比实验中统一使用惩罚参数C和核参数σ都为24.5的SVM进行分类。经测试,ASPS-MRTV网络模型在Indian Pines、 University of Pavia两个数据集上分别以5%, 1%的训练样本达到了97.06%、 98.98%的总体分类精度。实验结果表明,该模型与SVM、 ASPS(ED)、 ASPS(ID)、 ASPS-LBP、 ASPS-GlCM、 ASPS-BF模型相比,在分类性能和计算效率方面都取得了更优的效果,有效提高小样本下高光谱图像的分类精度。

半监督空谱局部判别分析的高光谱影像特征提取

为充分利用高光谱影像中蕴含的空谱特征,提出了一种半监督空谱局部判别分析的高光谱影像特征提取算法(S4LFDA)。鉴于高光谱数据集具有空间一致性,首先将像元进行空间重构,保存高光谱数据的近邻关系;其次引入光谱信息散度重构像元间的相似度;为了充分利用大量无标签样本提高算法性能,采用模糊C均值聚类算法对样本进行聚类分析得到伪标签;然后通过增加规范化项到局部力导引算法(FDA)的类内散度矩阵和类间散度矩阵中,以此保持无标签样本的聚类结构一致性;最后通过局部FDA算法来保持有标签样本类间散度最大化和类内散度最小化并求解最佳投影向量。S4LFDA算法既保持了数据集在光谱域的可分性,又保持了像元在空间区域内的近邻关系,合理利用有标签样本及无标签样本,提高了算法的分类性能。在Pavia University和Indian Pines数据集上进行实验,总体分类精度达到95.60%和94.38%。与其他维数约简算法相比,该算法有效提高了地物分类性能。

Determination of Fourier Components of Spatial Correlation Function of Dielectric Susceptibility of Random Medium

In this work, we present a new method of directly determining Fourier components of the spatial correlation function of the dielectric susceptibility of random medium. The method is based on the analysis of the ratio of the spectrum of the light scattered by the spatial correlation components of the dielectric susceptibility of tissue to the spectrum of light scattered by the randomly distributed scatterers which are independent on the value of the spectrum of the incident light and the direction of the observation. The results may find wide applications in areas such as in biomedical diagnosis.

一种改进的盲源分离抗主瓣干扰方法

在主瓣干扰场景下,由于常规自适应空域滤波的方法效果不佳,雷达常采用盲源分离抗主瓣干扰。但是,盲源分离后的信号难以估计目标角度。本文针对盲源分离后目标测角误差较大的问题,提出了一种改进方法,既能有效分离目标和干扰,又能准确估计目标角度。该方法对天线阵面进行非规则子阵划分,先对每个子阵进行波束域盲源分离,再对分离出的目标信号进行空间谱估计。本文分别采用JADE算法和MUSIC算法进行盲源分离和空间谱估计,测角性能受干扰功率影响较小,测角精度高。仿真结果证明了该方法的有效性和可行性。

基于空间光调制器的艾里光束能量调制方法

艾里光束由于具有无衍射、自加速和自愈合等特性,具有重要的应用前景。本文基于空间光调制器可编程特性,提出了一种可调谐的艾里光束能量调制新方法。从理论上深入分析通过在相位图中引入一个可控的调制相位而实现了艾里光束能量调控的方法,并且量化了调制参数与能量调制范围的关系。仿真和实验结果表明通过改变调制相位可以灵活地调节光束能量分布,本文的研究有助于进一步推动艾里光束的应用。

Minimizing Traffic Blocking and Inter-Crosstalk in Spatial Division Multiplexing over Elastic Optical Networking

As a promising solution, virtualization is vigorously developed to eliminate the ossification of traditional Internet infrastructure and enhance the flexibility in sharing the substrate network (SN) resources including computing, storage, bandwidth, etc. With network virtualization, cloud service providers can utilize the shared substrate resources to provision virtual networks (VNs) and facilitate a wide and diverse range of applications. As more and more internet applications migrate to the cloud, the resource efficiency and the survivability of VNs, such as single link failure or large-scale disaster survivability, have become crucial issues. Elastic optical networks have emerged in recent years as a strategy for dealing with the divergence of network application bandwidth needs. The network capacity has been constrained due to the usage of only two multiplexing dimensions. As transmission rates rise, so does the demand for network failure protection. Due to their end-to-end solutions, those safe-guarding paths are of particular importance among the protection methods. Due to their end-to-end solutions, those safeguarding paths are of particular importance among the protection methods. This paper presents approaches that provide a failure-independent route-protecting p-cycle for path protection in space-division multiplexed elastic optical networks. This letter looks at two SDM network challenges and presents a heuristic technique (k-shortest path) for each. In the first approach, we study a virtual network embedding (SVNE) problem and propose an algorithm for EONs, which can combat against single-link failures. We evaluate the proposed POPETA algorithm and compare its performance with some counterpart algorithms. Simulation results demonstrate that the proposed algorithm can achieve satisfactory performance in terms of spectrum utilization and blocking ratio, even if with a higher backup redundancy ratio.

基于空间谱估计的无人机协同目标方位感知算法

无人机协同目标感知技术是有人机无人机混合运行的重要安全保障.针对复杂空域环境下的感知可靠性问题,分析大中型无人机的复杂融合空域运行场景,并确定无人机协同目标感知的精准性、高实时性、抗干扰性和低载荷性等需求,提出一种四单元阵列天线和数字化射频体制的无人机协同目标感知系统架构;同时,结合空管雷达信号特性和天线体制,设计方位感知算法,通过修正协方差矩阵、信号子空间加权和噪声子空间加权等方法,设计基于多信号分类(multiple signal classification,MUSIC)的空间谱估计算法,并提出基于子空间分解的幅相误差在线估计算法;最后,开展算法仿真试验和实际空域环境飞行试验.研究结果表明:相比传统MUSIC算法,优化算法的方位感知高分辨性能提升23.3%,并改善了无人机协同目标方位感知的高实时性、抗干扰性和低载荷性.

数字全息显微信号项频谱定位及干扰项抑制

在离轴数字全息显微和非相干光成像研究中,空间频域滤波是重建目标物体的振幅和相位信息的关键步骤。信号项频谱选取及中心定位对滤波后重建相位的质量有着极大影响,即使像素级的微小差异也会导致重建相位的严重失真。为了解决这个问题,文章提出了一种数字全息显微信号项频谱定位及干扰项抑制的方法。方法根据全息图频谱的直方图分布特性,自适应确定滤波形状和大小,同时,采用质心法来快速准确的确定信号项频谱的中心,并在频域中运用形态学处理来消除信号项频谱周围的干扰项。实现了信号项频谱自适应滤波,从而提高了相位重建的质量。文章使用二维山形图模拟相位进行了仿真验证,并搭建光路拍摄USAF1951标定板上的数字区域和洋葱表皮细胞进行了实验验证。仿真和实验结果表明,算法可以实现高质量的相位重建,并对干扰项进行抑制,提高了离轴数字全息显微系统的成像质量。