基于快速平行因子分解的声矢量传感器阵二维DOA估计

将声矢量传感器阵列参数估计问题与平行因子(Parallel factor,PARAFAC)模型相结合,提出了一种基于快速PARAFAC分解的二维波达方向(Direction of arrival,DOA)估计算法。该算法首先将接收信号构建为PARAFAC模型,然后在数据域对参数矩阵进行初估计,最后利用PARAFAC分解获得信号二维DOA估计。该算法能够应用于任意结构的声矢量传感器阵列,同时能够得到和信源一一匹配的仰角和方位角估计。借助于参数矩阵的初始估计,所提算法收敛速度较快,其计算复杂度大大降低。该算法角度估计性能接近于PARAFAC算法,同时优于借助旋转不变性进行信号参数估计(Estimation of signal parameters via rotational invariance technique,ESPRIT)算法和传播算子(Propagator method,PM)算法。     

噪声与共振环境下的数字助听器鲁棒声源定位法

提出了一种噪声与共振环境下的数字助听器鲁棒声源定位方法,该方法基于房间共振模型和多通道自适应特征值分解算法,利用自适应次梯度投影方法迭代地估计声源至各麦克风的脉冲响应系数,从而获得各麦克风对的时延差,并利用几何方法计算声源位置。针对眼镜数字助听器四元麦克风方阵的仿真表明,所提出的自适应次梯度投影方法在强噪声环境中的鲁棒性和定位精度优于传统NLMS算法。     

火星探测无人机快速景象匹配算法

针对火星无人机探测飞行过程的特点及其机载计算机的局限性,在充分研究了矩阵奇异值向量性质特点的基础上,对奇异值向量进行主分量分析,提出了一种应用于火星无人机平飞段的基于奇异值分解的分层快速景象匹配算法,并给出了与之相应的机载特征数据存储方法.与相关算法的对比性实验表明,本文提出的算法具有准确,稳定,且速度更快,数据量更小的优点.通过仅在飞行末段,将本文算法切换成现有的基于SIFT算子的匹配算法,能在实现火星无人机全程快速景象匹配的同时,有效降低对其机载计算机综合性能的要求.     

三维非结构混合网格区域分解及数据处理

讨论了三维非结构混合网格区域分解技术及子分区显示技术。在三维复杂外形的流场计算中,为了得到较高的计算效率及保证数值模拟的准确性,经常要采用混合网格及并行计算技术。本文针对三维非结构混合网格的自动分区及子网格的数据处理进行了细致的讨论,编写了相应的软件。对三维实际外形非结构混合网格的处理结果表明,本文发展的方法及软件系统具有通用性强、人为干涉参数少、自动化程度高等特点,可作为通用软件推广使用。     

Numerical study of a supercritical airfoil/wing with variable-camber technology

Variable-camber technology is considered an effective way to adaptively improve the aerodynamic performance of aircraft under various flight conditions. This paper studies the aerodynamic characteristics of the trailing-edge variable-camber technology by means of Computational Fluid Dynamics (CFD) and a drag decomposition method. Trailing-edge variable-camber technology can be simply realized by the continuous deflection of the flaps and ailerons of a wing. A supercritical airfoil is used to study the two-dimensional effect of variable-camber technology, and a wide-body airplane model is used to validate the three-dimensional improvement in the wing's airfoil made by variable-camber technology. An optimization strategy for airfoil that incorporates variable-camber technology is proposed. The optimization results demonstrate that the proposed method can obtain better results than the traditional segregated shape optimization.     

A novel variable structure multi-model approach based on error-ambiguity decomposition

Model Set Adaptation (MSA) plays a key role in the Variable Structure Multi-Model tracking approach (VSMM). In this paper, the Error-Ambiguity Decomposition (EAD) principle is adopted to derive the EAD-MSA criterion that is optimal in the sense of minimizing the square error between the estimate and the truth. Consequently, the EAD Variable Structure first-order General Pseudo Bayesian (EAD-VSGPB1) algorithm and the EAD Variable Structure Interacting Multiple Model (EAD-VSIMM) algorithm are constructed. The proposed algorithms are tested in two groups of maneuvering target tracking scenarios under different modes and observation error conditions. The simulation results demonstrate the effectiveness of the EAD-VSMM approach and show that, compared to some existing multi-model algorithms, the proposed EAD-VSMM algorithms achieve more robust and accurate tracking results.     

Investigation of the characteristics of wavelike oscillations of post-sunset equatorial ionospheric irregularity by decomposing fluctuating TEC

Post-sunset ionospheric irregularities are common features of the equatorial ionosphere that affect radio communication and navigation systems; their triggering physical mechanism is not yet fully understood. Atmospheric gravity wave is considered as a seeding mechanism for the occurrence of ionospheric irregularities (Abdu et al., 2009). To understand the effects of atmospheric waves, characteristics of wavelike oscillation from ionospheric total electron content (TEC) fluctuation that can be obtained from superposition of different oscillation modes have been investigated. Decomposing fluctuating TEC into different oscillation modes and investigating oscillation characteristics of each component is also important to get insight about the characteristics of individual atmospheric waves that may cause TEC fluctuation. In this paper we have investigated characteristics of components of fluctuating TEC obtained from SCINDA GPS receiver installed at Bahir Dar, (geographic coordinate, 11.5°N, 37.6° E, and dip latitude of 2.5°N) Ethiopia during April 2012. First Empirical Mode Decomposition (EMD) has been applied to decompose TEC fluctuation into different oscillation modes that are known as Intrinsic Mode Function (IMF). Hilbert-Huang Transform (HHT) and Continuous Wavelet Transform (CWT) have been applied to investigate the characteristics of wave-like oscillations. Applying EMD on fluctuating vTEC corresponding to a GPS satellite, five components are found. Results from HHT and CWT have shown excellent agreement. In addition, it is found out that the median periods of oscillation of those five components are 9, 17, 47, 78, and 118 min. Of these periods, 17 and 47 min respectively are oscillation periods of components of TEC fluctuation with occurrence frequency of 92% and 91% that may be interpreted as the manifestation of two frequently occurring components of atmospheric gravity waves that are likely generated by the motion of solar terminator.     

涡轮叶片早期裂纹的三维叶尖间隙EEMD能量熵融合诊断方法

为了解决航空发动机涡轮叶片早期裂纹故障信号微弱、难以识别的问题,提出一种基于三维叶尖间隙集成经验模态分解（EEMD）能量熵融合的涡轮叶片早期裂纹诊断方法。采集涡轮叶片三维叶尖间隙信息,利用EEMD分别对三维叶尖间隙各维信号进行处理,得到相应的固有模态函数(IMF),以此计算每一维信号分量EEMD能量熵,构建能表征叶片裂纹状态的不同EEMD能量熵高维矢量集。建立多个堆叠自动编码器(SAE)分别对各高维矢量集进行特征学习并提取所学习的深层特征表达。利用支持向量机算法(SVM)和遗传算法(GA)融合各维深层特征以综合不同维度信息进而充分判定叶片裂纹状态。通过涡轮叶片裂纹诊断试验,结果表明:所提方法能有效提高叶片早期裂纹诊断精度,其平均准确率达到98.415%,标准差仅为0.697%,具有很好的稳定性、泛化性和自适应性。     

圆周进气对流掺混流动研究

为了研究纯径向向心涡轮出口对流撞击掺混流动组织结构,采用大涡模拟对圆周进气的对流掺混流动进行了数值仿真,并用本征正交分解(POD)方法,提取和分析了不同阶模态下的流动结构。结果表明:在水平截面,底部中心形成一个滞止区,两侧壁面附近均存在一个回流区,且流动是近似对称的;在剪切力作用下,沿流动方向,旋涡结构的不稳定性增强,上游三维涡环结构逐渐拉伸、膨胀,破裂为复杂的涡辫或发卡涡结构,这增强了掺混,从而使得流体间的动量和能量交换增强;POD结果中第1阶模态所占的能量权重最高,表明脉动场中的大部分能量主要集中在此模态,此模态中的流动结构为主要流动结构。     

新型遥感图像增强技术

基于方向辅助信号和所需带宽,提出一种基于各向异性BEMD的遥感图像融合增强算法。首先,给定的方向辅助信号和其对应负信号加到原始信号中去,构建两个待分解信号;然后,应用传统BEMD把两个待分解信号进行分解,获取的分量相加得到对应的IMFs,辅助信引同时在相加的过程中被移除,同时该过程有效地避免了边界效应和模式混叠,该方法...