小波分析在陀螺信号滤波中的研究

介绍了小波分析进行滤波法，建立了陀螺随机漂移的数学模型，使用了4种典型的小波基对陀螺的输出信号进行多尺度的小波分解，通过软阈值法消除了由噪声产生的小波系数，通过小波重构实现了滤波，试验数据验证了方法的有效性。     

基于小波包的故障信号特征提取的研究

讨论了交--交变频调速系统故障诊断的重要性,在当前的检测方法与故障诊断手段研究的基础上,提出了一种改进的小波包算法,并运用该算法对变频调速系统输出电流进行分析.该算法的计算量和占用的存储空间较标准的小波包算法均减少80%.同时,运用基于改进的小波包的频带能量法提取变频调速系统的故障特征,分析了小波包分解层次对特征量提取的影响.经过仿真证明,该方法适用于变频调速系统故障信号的特征量提取.     

Code Combining--A Maximum-Likelihood Decoding Approach for Combining an Arbitrary Number of Noisy Packets

It is well known that if the data rate is chosen below the available channel capacity, error-free communication is possible. Furthermore, numerous practical error-correction coding techniques exist which can be chosen to meet the user's reliability constraints. However, a basic problem in designing a reliable digital communication system is still the choice of the actual code rate. While the popular rate-1/2 code rate is a reasonable, but not optimum, choice for additive Gaussian noise channels, its selection is far from optimum for channels where a high percentage of the transmitted bits are destroyed by interference. Code combining represents a technique of matching the code rate to the prevailing channel conditions. Information is transmitted in packet formats which are encoded with a relatively high-rate code, e.g., rate 1/2, which can be repeated to Obtain reliable communications when the redundancy in a rate-1/2 code is not sufficient to overcome the channel interference. The receiver combines noisy packets (code combining) to obtain a packet with a code rate which is low enough such that reliable communication is possible even for channels with extremely high error rates. By combining the minimum number of packets needed to overcome the channel conditions, the receiver optimizes the code rate and minimizes the delay required to decode a given packet. Thus, the receiver adapts to the actual jammer-to-signal(J/S)ratio which is critical when the level of interferenceJis not known a priori.     

Phase Unwrapping for SAR Interferometry—A Data Fusion Approach by Kalman Filtering

This paper considers the problem of unwrapping the phase image obtained from a noisy interferometric synthetic aperture radar (InSAR) image. The implicit nonlinearity of the problem is reflected, as well as the drawbacks of this nonlinearity on the performance of phase unwrapping approaches. Some general concepts concerning basic estimation techniques are shortly reviewed. On this background, a Kalman filter-based data fusion approach to unwrap and simultaneously filter the phases of InSAR images is developed. The data fusion concept exploits phase information extracted from the complex interferogram rather than from the phase image and fuses that information with phase slope information extracted from the power spectral density of the interferogram.     

小波变换与自适应滤波在脑电信号消噪中的应用

提出了基于AR(自回归)模型的小波变换与LMS(最小均方)自适应滤波相结合的脑电信号分析方法,并利用它来消除脑电信号中的噪声干扰。实验结果表明,利用小波变换与自适应滤波相结合能有效去除脑电信号中的噪声干扰。     

Novel Area-Efficient FPGA Architectures for FIR Filtering With Symmetric Signal Extension

This paper presents four novel area-efficient field-programmable gate-array (FPGA) bit-parallel architectures of finite impulse response (FIR) filters that smartly support the technique of symmetric signal extension while processing finite length signals at their boundaries. The key to this is a clever use of variable-depth shift registers which are efficiently implemented in Xilinx FPGAs in the form of shift register logic (SRL) components. Comparisons with the conventional architecture of FIR filter with symmetric boundary processing show considerable area saving especially with long-tap filters. For instance, our architecture implementation of the 8-tap low Daubechies-8 FIR filter achieves ~ 30% reduction in the area requirement (in terms of slices) compared to the conventional architecture while maintaining the same throughput. Two of the above-cited novel architectures are dedicated to the special case of symmetric FIR filters. The first architecture is highly area-efficient but requires a clock frequency doubler. While this reduces the overall processing speed (to a maximum of 2), it does maintain a high throughput. Moreover, this speed penalty is cancelled in bi-phase filters which are widely used in multirate architectures (e.g., wavelets). Our second symmetric FIR filter architecture saves less logic than the first architecture (e.g., 10% with the 9-tap low Biorthogonal 9&7 symmetric filter instead of 37% with the first architecture) but overcomes its speed penalty as it matches the throughput of the conventional architecture.     

小波分析及其在信号处理中的应用

首先对小波变换做了概括介绍，综述了小波变换在信号处理中的2个重要方面的应用：信号特征提取和信号消噪。     

小波包分析在旋转机械故障诊断中的应用

简述了小波包分析的基本原理及其用于故障特征识别的机理,研究了小波包分析在旋转机械故障诊断中的应用。由于此技术能够从复杂的信号中有效地提取微弱的故障特征信号,因此与小波分析相比,分析更为精细简单。实例采用小波包原理对一类旋转信号进行分解重构后,成功地提取了故障特征,体现了小波包分析的优良特性,其结果证明了该方法是行之有效的。     

Multiresolution Monogenic Signal Analysis Using the Riesz–Laplace Wavelet Transform

The monogenic signal is the natural 2D counterpart of the 1D analytic signal. We propose to transpose the concept to the wavelet domain by considering a complexified version of the Riesz transform which has the remarkable property of mapping a real-valued (primary) wavelet basis of L₂(R²) into a complex one. The Riesz operator is also steerable in the sense that it give access to the Hilbert transform of the signal along any orientation. Having set those foundations, we specify a primary polyharmonic spline wavelet basis of L₂(R²) that involves a single Mexican-hat-like mother wavelet (Laplacian of a B-spline). The important point is that our primary wavelets are quasi-isotropic: they behave like multiscale versions of the fractional Laplace operator from which they are derived, which ensures steerability. We propose to pair these real-valued basis functions with their complex Riesz counterparts to specify a multiresolution monogenic signal analysis. This yields a representation where each wavelet index is associated with a local orientation, an amplitude and a phase. We give a corresponding wavelet-domain method for estimating the underlying instantaneous frequency. We also provide a mechanism for improving the shift and rotation-invariance of the wavelet decomposition and show how to implement the transform efficiently using perfect-reconstruction filterbanks. We illustrate the specific feature-extraction capabilities of the representation and present novel examples of wavelet-domain processing; in particular, a robust, tensor-based analysis of directional image patterns, the demodulation of interferograms, and the reconstruction of digital holograms.     

一种信号分选和特征提取联合处理的雷达信号分析方法研究

研究广度优先搜索邻居的聚类算法和直方图法用于雷达信号分选和特征提取的原理和方法,并将两者相结合用于雷达信号分析使分选和特征提取更加准确.仿真实验证明联合处理法是高效和实用的.     

基于小波多分辨分析的极化分析和滤波方法

在小波多分辨分析的基础上,在各个尺度上分别用协方差矩阵法计算极化参数,给出在不同的尺度上选取相应的时窗长度的方法,对协方差矩阵法不能计算的各个尺度位移的开始和结束处用瞬时法计算极化参数。这种方法有效地解决了协方差矩阵法时窗长度的选取和参数计算时存在的边界问题以及瞬时极化分析法对瞬时干扰的敏感问题．     

复解析小波变换与语音信号包络提取和分析

利用传统的Ｈｉｌｂｅｒｔ变换方法提取语音信号包络存在一些固有缺陷,为此本文建议了一种复解析小波变换包络提取新方法。该方法将Ｈｉｌｂｅｒｔ分析与小波分析紧密地结合在一起。文中推导并论述了新包络滤波器的时域、频域构造条件和设计方法,选择Ｍｏｒｌｅｔ复小波对语音信号进行了初步数字仿真实验,结果证实了理论分析的正确性,并显示出文中提出的新的分析方法对于信号处理上有许多独特优势和潜在性能。     

SDP Approximation of a Fractional Delay and the Design of Dual-Tree Complex Wavelet Transform

We show that an $H_{infty}$ optimization problem related to fractional delay approximation can be formulated as a semidefinite programming (SDP) problem and thus solved reliably. Particularly, given the finite-impulse-response (FIR) filter $H(z)$, we find the FIR filter $G(z)$ of given degree such that $Vert G(z)-z^{-1/2}H(z)Vert_{infty}$ is minimum. This half-sample delay approximation problem is used in the design of filters generating orthogonal dual-tree complex wavelet transforms. Since the solution does not conform to the orthogonality constraints exactly, we propose their enforcement in a second stage of optimization, in which an analyticity criterion is optimized. The proposed designs compare favorably with previous ones.      

光纤陀螺组合的信号频谱分析与滤波技术研究

对某惯导系统中使用的三轴向光纤陀螺(FOG)组合的输出信号做了基于FFT的频谱分析,设计并实现了中值滤波I、IR数字滤波器滤波、小波滤波三种不同方法对该信号的噪声滤除,分别给出了滤波后陀螺输出信号的幅频特性图。通过对试验数据的分析,肯定了三种方法在FOG组和输出信号滤波处理中的有效性,并分析了各自的优缺点。     

小波变换与信号分析课程的教学思路

根据近五年的教学实践,从信号分析与处理的角度出发,就“小波变换与信号分析”课程的教学内容以及教学方法进行了探讨,并提出了几点粗浅的看法。     

基于小波变换的瑞利波信号去噪探析

针对利用瑞利波对目标进行探测问题,提出了采用小波变换对瑞利波信号进行去噪的方法。通过基于MATLAB信号去噪的仿真试验,验证了小波变换降噪方法相对于传统方法的优越性。实验分析结果表明：该方法对背景噪声有较好的抑制作用,提取线谱信号的能力和精度优于FFT分析方法,滤波器方法性能提高了约13至17dB,有利于瑞利波特征线谱的提取。     

压电陀螺信号处理与滤波技术研究

针对压电陀螺在工程上实际应用的需求,对其输出做了测试和建模,设计并实现了α-β滤波、卡尔曼滤波和小波滤波3种不同方法对该信号的噪声滤除,分别给出了滤波后陀螺输出信号图和标准差的对比.通过对试验数据的分析,肯定了3种方法在压电陀螺输出信号滤波处理中的有效性,并分析了各自的优缺点.     

小波包分析在雷达信号处理中的应用

现代雷达技术的一个重要发展方向是超宽带、多功能、智能化。提高识别系统的智能化,是雷达目标识别领域的一个关键性问题。雷达所发射的信号向宽带和超宽带扩展。传统的傅里叶变换对非平稳信号几乎无法处理,小波包理论将频带进行多层次划分,并能根据被分析信号的特征自适应地选择相应频带,使之与信号频谱相匹配。     

基于小波变换的机械振动信号阈值去噪分析

随着现代机械自动化的发展,生产设备功能越来越多,性能要求越来越高。为了缩小设备成本,机械故障诊断越来越重要。振动信号分析是诊断故障是最有效简单的方法。文章为获取其有用信号特征,去除噪声信号,提出了基于小波分析新的阈值法,并全面分析了各类小波和4种经典阈值去噪的效果。此次提出的新的阈值函数同时具有软、硬阈值函数方法的优点,使它处理小波系数时更灵活。经阈值处理后,小波系数值变为2个参数取值共同决定函数由软变硬的快慢程度。实验仿真说明,新的阈值法对于振动信号去噪效果明显。     

小波图形显示算法在非平稳信号分析中的应用

对故障信息的提取是机组状态监测与故障诊断系统的核心,对于机组中大量存在的非平稳信号,目前有效的方法是用小波时频分析法、由于信号经小波分解后,其数据点随着每次分解而成倍减少,严重影响了分析精度,而小波的图形显示算法使这一问题得到解决,基于该算法的实用程序应用于实际的信号分析中,得出了满意的结果。