Scale analysis of pre- and post-midnight ESF bubbles at storm time and quiet time

This paper adopts a scale analysis technique to investigate the properties of intermediate-scale plasma structures observed by ROCSAT-1 in the equatorial F-region. A procedure of scale analysis that is developed via the empirical mode decomposition (EMD) method of Hilbert–Huang transform (HHT) technique allows the mutually correlated components in velocity, density and relative density gradient to be identified and extracted. Comparing the three parameters, good match in wave form is found for density and velocity in the scales between kilometers and hundred meters (few kilometers to 300 m). It implies that there are electric fields proportional to density fluctuation −δn/n in the form similar to what is expected for the generalized Rayleigh–Taylor instability. We find that such a one-to-one match holds for various pre- and post-midnight ESF bubbles during quiet and storm times. It, therefore, means that spatial structures of electric field in the intermediate-scale (300 m to few kilometers) correlates to the density structures in a manner of δE ∝  −δn/n that is not necessarily depending on the driving mechanism of ESF bubbles, although it is known that ESF bubbles can be driven by different mechanisms under different space weather conditions. In smaller scales (300–50 m), fluctuation patterns of density and velocity do not correlate to each other any more, the good match is then found in the density gradient ∇_xn/n and velocity. It is known as the manifestation of the Boltzmann relation. We note that the GRT instability related relationship δV_z ∝  −δn/n for irregularities in scale of kilometers holds only for ESF bubbles that occur within ±5 dip latitude, while the Boltzmann relation (δV_z proportional to ∇_xn/n) holds for small-scale irregularities without such a limitation.     

基于小波神经网络的航空发动机建模研究

提出将多个多输入单输出小波神经网络(WNN)组合构造多输入多输出(MIMO)的WNN来逼近MIMO非线性动态系统的快速而简单的实现方法，并采用高效率的初始化方法缩短了训练时间。采用某型航空发动机在飞行包线内均匀分布的工作点参数来训练，建立了全包线适用的动态小波神经网络航空发动机模型，用交叉验证的方法检验表明在全包线内有较高的精度及泛化能力。与反传算法神经网络(BPNN)、径向基函数神经网络(RBFNN)建立的动态模型在精度及泛化能力等方面做比较，结果表明WNN建立的模型训练精度高而且泛化能力强。     

一种用于版权认证的数字图像水印算法

提出了一种基于DWT域的用于图像版权认证和保护的数字图像水印方法。首先,将原始图像分块,并对每块进行多层DWT变换;然后,把置乱的水印图像嵌入到图像的多层低频小波系数上;最后,再对图像进行IDWT变换。文中所采用的二值标识水印图像直观,信息量大,并根据实际需要,用航拍图像作为载体图像进行实验。实验结果表明,该方法简单高效, 可嵌入的数字水印信息容量大,对一般的图像处理和各种攻击有很好的鲁棒性,如:JPEG压缩、滤波、加噪声、旋转、缩放,涂抹、剪切等,能够准确可靠地提取水印。     

NOVEL HIGH-SPEED FPGA-BASED FFT PROCESSOR

A novel architecture for computing the fast Fourier transform ( FFT ) on programmable devices is presented.To improve the system operation speed , a hybrid parallel FFT algorithm is used.Results indicate that the use of an 8×8parallel structure for realizing the 64-point FFT leads to a 8times higher processing speed compared with its counterparts employing other series of techniques.     

航拍视频拼图中基于特征匹配的全局运动估计方法

 主要研究了航拍视频拼图中的全局运动估计问题。根据航拍视频成像过程的特点,得出相邻帧之间全局运动的4参数近似变换模型,该模型参数较少,鲁棒性好且计算简单,任意帧之间的变换模型通过“帧到帧”的方式递归获得。提出了一种双向最近邻距离比的尺度不变特征(SIFT)的匹配方法,提取出有效的匹配点,并采用随机采样一致性(RANSAC)方法去除外点和估计全局运动参数。从试验结果可以看出,该方法估计出的全局运动参数精度高,鲁棒性好。     

An approach for parameter estimation of combined CPPM and LFM radar signal

In this paper, the problem of parameter estimation of the combined radar signal adopting chaotic pulse position modulation (CPPM) and linear frequency modulation (LFM), which can be widely used in electronic countermeasures, is addressed. An approach is proposed to estimate the initial frequency and chirp rate of the combined signal by exploiting the second-order cyclostationarity of the intra-pulse signal. In addition, under the condition of the equal pulse width, the pulse repetition interval (PRI) of the combined signal is predicted using the low-order Volterra adaptive filter. Simulations demonstrate that the proposed cyclic autocorrelation Hough transform (CHT) algorithm is theoretically tolerant to additive white Gaussian noise. When the value of signal noise to ratio (SNR) is less than 4 dB, it can still estimate the intra-pulse parameters well. When SNR = 3 dB, a good prediction of the PRI sequence can be achieved by the Volterra adaptive filter algorithm, even only 100 training samples.     

基于解析小波的光流计算方法

在基于小波变换的光流计算中,实值小波系数的相位振荡和多分辨率计算的累计误差是影响光流计算精度的两个主要原因.通过引入解析小波以降低相位振荡的影响,同时结合M估计子能够有效抑制参数估计产生的大误差项,提出一种多尺度多分辨率的光流计算方法.实验表明,与现有的基于小波变换的光流计算方法相比,提出的方法不论在光流计算的精度还是可计算范围上都有很大程度的提高.      

三种时频分析在复合材料无损检测中的应用

随着复合材料的广泛应用和现代信号处理技术的发展,时频分析方法已广泛应用于各类复合材料的损伤检测。将短时傅立叶变换、小波变换和黄氏变换三种时频分析技术经过Matlab编程,结合Lamb波应用于玻璃纤维增强的复合材料层合板的无损检测,并对三种时频结果进行比较与分析。结果表明：上述三种时频分析方法都能进行复合材料的损伤判定,但黄氏变换方法的分析精度更高。     

一种基于三正交主轴平面的快速星图模拟方法

为在地面上进行星图模拟以测试星图识别算法和星敏感器性能, 提出了一种新的快速星图模拟方法. 该方法利用截面圆和固定区域的性质, 将单位天球按照三个正交主轴平面进行等分, 根据赤纬值求解恒星矢量与主轴平面夹角来确定选星条件, 进而根据坐标变换原理进行星图模拟. 为验证所提方法与现有方法相比的优势, 进行了大量的仿真实验. 实验结果表明, 与现有星图模拟方法相比, 本文方法在保证星图模拟精度的条件下, 选星速度提高了3倍以上.     

基于菲涅耳变换的不变矩提取及目标识别方法

提出了一种基于菲涅耳变换的不变矩特征提取方法,并应用于图像目标识别.利用菲涅耳变换得到图像的衍射图样,将图像映射到菲涅耳衍射空间;在衍射空间提取几何矩或正交矩来获取图像全局信息的特征描述;利用k近邻法识别目标.实验结果表明基于菲涅耳变换的不变矩提取方法对于平移、尺度及旋转变化的图像目标具有更高的分类精度和抗噪声能力.