基于小波阈值法的激光雷达回波信号去噪研究

为了对激光雷达探测回波信号去噪进行研究，基于小波阈值法分析了激光雷达发射和探测回波信号，创建了基于MATLAB仿真平台的模型, 研究了阈值法中选择各参量的策略，结合激光雷达信号和噪声特性，选取了去噪处理中的最佳参量，并进行了4种阈值策略的仿真实验，实现了对探测回波信号中目标信号的有效提取和去噪。结果表明，对于低信噪比信号，同一基函数分解层越高去噪效果越好，在分解层数j为4~5时去噪效果最好; 对于高信噪比信号，同一基函数分解层越低去噪效果越好，在j=3时去噪效果最好，并且信号db9基函数去噪效果好于db2基函数去噪效果。此研究获得了较为理想的去噪结果。     

小波阈值去噪的改进方法

利用小波方法去噪,是小波应用于工程实践一个重要的方面;本文指出了采用常见的阈值确定方法对含有较强高频分量的信号进行小波阈值去噪时,去噪效果与实时性存在着矛盾,不利于信号特征的提取。提出了一种新型的阈值确定方法,进一步提出了以小波去噪后特征频率分量的功率谱密度值的下降程度为依据的待定因子确定方法。以Mallat算法为例,对新型阈值确定方法进行了分析和比较,指出运用该方法进行小波去噪处理,增强了算法的实时性,同时信号拟关注的信息损失较小,去噪效果比较理想。交-交变频器输出电流的小波去噪实验结果表明,该方法行之有效。     

杂波环境中雷达通信一体化系统波形设计算法研究

针对杂波环境中雷达通信一体化系统探测性能下降的问题,该文以信干噪比作为设计准则,通过联合优化系统发射波形和接收滤波器来抑制杂波,进而增强目标探测性能。为同时保证系统信息传输的质量,将通信信号的多用户干扰能量纳入约束条件。此外,引入相似性约束使得发射波形具有良好的模糊函数。为求解发射波形和接收滤波器联合优化问题,提出了一种基于循环优化和半正定松弛的迭代算法。理论分析证明了算法的收敛性。仿真结果表明,所设计的波形不仅可以提升系统在杂波环境中的目标探测性能,而且可以高效地实现多用户通信。      

低空目标声信号去噪方法研究

声目标探测识别是目前弥补雷达低空探测不足的重要方法。采集到的声信号通常含有大量环境噪声,如何在去除噪声的同时尽可能多地保留有效信号是该领域的一个难点。针对低空战场环境噪声的特点,提出基于改进阈值经验模式分解的去噪方法。首先对信号进行经验模式分解,然后对实际能量大于噪声能量的固有模式函数进行阈值处理,最后将处理后的固有模式函数进行重构得到去噪信号。为了验证该算法的性能,对直升机声信号加入不同信噪比的典型低空环境噪声进行去噪,并与其他去噪方法进行比较,采用信噪比、均方根误差和平滑度指标进行定量分析。仿真结果表明,该算法对大部分低空环境噪声有良好的去除效果。     

基于凸优化的MIMO雷达的优化滤波器组设计

在正交波形MIMO雷达信号处理中,发射信号分离是其中的一个重要环节,一般可以通过匹配滤波器组来实现,而匹配滤波器组对信号分离是基于发射信号满足理想正交条件的,实际中由于很难得到理想的正交波形集,因此将会造成信号分离能力下降或分离不彻底,为此,提出一种优化滤波器组设计方法,以最小化滤波输出峰值旁瓣电平为目标函数,采用凸优化方法进行全局优化设计,计算机仿真表明,该方法所设计的优化滤波器组可以显著提高非理想正交波形MIMO雷达的信号分离能力。     

A／D转换芯片ADS1211在小波去噪电路中的应用

小波去噪是建立在小波变换基础上的一种滤波方法,选择不同的小波函数和分解层数可以调整滤波器的特性。小波去噪具有结构简单和性能稳定的特点。为了获得随钻测量中的解码数据,选用高精度A／D转换芯片ADS1211,以TMS320F2812作为控制核心,设计实现了数据采集电路和小波去噪算法。通过波形对比证实了小波去噪的实际效果。     

基于希尔伯特黄变换的滤波器设计

对希尔伯特黄变换理论进行了简要地介绍,研究了希尔伯特黄变换的经验模态分解过程和有噪信号的固有模态函数特征.通过研究,设计了一种基于希尔伯特黄变换的滤波器.将该滤波器应用于信号去噪,收到了满意地效果.     

基于集合经验模态的微弱激光脉冲信号自动去噪方法

由于微弱激光脉冲信号中存在噪声，需对其进行去噪处理，为此，提出基于集合经验模态的微弱激光脉冲信号自动去噪方法。首先建立微弱激光脉冲信号模型，模拟信号回波；其次采用集合经验模态分解方法分解微弱激光脉冲信号，并计算模态分量的排序熵，根据计算结果消除虚假分量；再采用基于峰度检测的加窗方法获取噪声与有效信号的分界点，确定噪声区域；最后引入小波滤波器在噪声区域内对微弱激光脉冲信号自动去噪。实验结果表明，所提方法的噪声检测精度高、去噪效果好、去噪效率高。     

一种局部放电信号去噪的新方法

小波变换是在局部放电信号去噪过程中常用的方法,由于实际信号中噪声频带较宽,仅用小波变换去噪有可能带来波形畸变。文中将经验模态分解（Empircial Mode Decomposition,EMD）引入小波阈值去噪算法中,提出了一种基于EMD的小波阈值去噪算法,信号经EMD变换后被分解成若干个频率的本征模态函数（Intrinsic Mode Function,IMF）,再对各个频率的IMF分量进行小波阈值去噪。相比于普通的小波阈值去噪算法,该方法能取得更好的去噪效果。对仿真信号和实测信号的处理结果验证了该方法的有效性。     

光纤阵列编码成像激光雷达系统

提出了一种基于光纤阵列的编码成像激光雷达,该系统采用光纤阵列代替传统成像激光雷达中的多像元光电探测器阵列。该设计通过编码、合波形探测、解码使用少探测器实现高分辨率成像,避免了高像素光电探测器阵列的研制难题。同时,对系统解码信号进行了进一步的去噪算法,仿真结果表明在低信噪比条件下小波去噪算法可以获得比较好的成像效果。     

Estimation of motor unit conduction velocity from surface EMG recordings by signal-based selection of the spatial filters

Muscle fiber conduction velocity (CV) can be estimated by the application of a pair of spatial filters to surface electromagnetic (EMG) signals and compensation of the spatial filter transfer function with equivalent temporal filters. This method integrates the selection of the spatial filters for signal detection to the estimation of CV. Using this approach, in this paper, we propose a novel technique for signal-based selection of the spatial filter pair that minimizes the effect of nonpropagating signal components (end-of-fiber effects) on CV estimates (optimal filters). The technique is applicable to signals with one propagating and one nonpropagating component, such as single motor unit action potentials. It is shown that the determination of the optimal filters also allows the identification of the propagating and nonpropagating signal components. The new method was applied to simulated and experimental EMG signals. Simulated signals were generated by a cylindrical, layered volume conductor model. Experimental signals were recorded from the abductor pollicis brevis with a linear array of 16 electrodes. In the simulations, the proposed approach provided CV estimates with lower bias due to nonpropagating signal components than previously proposed methods based on the entire signal waveform. In the experimental signals, the technique separated propagating and nonpropagating signal components with an average reconstruction error of 2.9 +/- 0.9% of the signal energy. The technique may find application in single motor unit studies for decreasing the variability and bias of CV estimates due to the presence and different weights of the nonpropagating components.     

Statistical evaluation of sequential morphological operations

In order to properly apply sequential morphological operations to random signals in applications concerned with noise suppression, the authors have examined their statistical properties using different structuring elements. The performance of flat and triangular structuring elements has been evaluated for signals with uniform, Gaussian, and Rayleigh density functions. In particular, the statistical properties of sequential morphological operations (i.e,, dilation, closing, clos-erosion, and clos-opening) are examined as a function of the parameters of the structuring element through Monte Carlo simulation, which overcomes the statistical dependency problem arising in the processed signal at different stages of morphological operations. The simulated results and their statistics (mean, variance, and skewness) present an interpretation of the signal root, biasing effects, and noise suppression capability of morphological filters     

Structuring element decomposition for efficient implementation ofmorphological filters

In order to implement morphological filters on image processing systems. The size of the structuring element must be small due to the architectural constraints of the systems. The decomposition of the structuring element is required for filters with large structuring elements. An algorithm for the decomposition of an arbitrary 4-connected binary structuring element is developed which enables sub-optimal implementation of binary morphological filters on a 3×3 pipeline machine. The given structuring element is first decomposed into the union of elements using a sequential search procedure, then each element is further decomposed optimally into 3×3 elements, resulting in final sub-optimal 3×3 hybrid decomposition. The proposed algorithm is applied to some structuring elements and results close to the optimum are obtained     

An improved morphological approach to background normalization of ECG signals

This paper describes an improved morphological approach to remove baseline wander from neonatal electrocardiogram (ECG) signals, with particular emphasis on preserving the ST segment of the original signal. The algorithm consists of two stages of morphological processing. First, the QRS complex and impulsive noise component due to skeletal muscle contractions etc., are detected and removed from the input signal. Second, the corrected QT interval (QTc) and RR interval are used to determine a structuring element. With this structuring element, the same morphological operation as in the first stage is then applied to the QRS-removed signal to obtain and remove the baseline wander. The performance of the algorithm is evaluated with simulated and real ECGs. Compared with an existing morphological method, there is a substantial improvement, especially in reducing distortion of the baseline waveform within the PR and QT intervals.     

An Interfering Signal Detection Technique Using an Ultra Wideband Chirp Template Waveform

This paper discusses a coexisting signal detection technique for sharing the spectrum of an Ultra Wideband (UWB) radio with other radio systems. In some countries’ regulations, the Detection and Avoidance technique is required to be implemented in UWB systems so they do not interfere with other radio systems. In most interference avoidance techniques it is necessary to detect emissions of the interfering system and the interfering bands. In this paper, correlation detection is applied for interfering signal detection without band pass filters. In the detector, a Chirp-UWB is prepared as a template waveform. The signal received before UWB communications is correlated with the Chirp-UWB template waveform, and is then integrated. The integral period is decided from the sweep function of the Chirp-UWB and the interfering bands. Therefore the detection technique can detect arbitrary frequency band signals by modifying the integral period. The sweep function of the Chirp-UWB also improves the detection performance. A sine function is adopted for the sweep function of the chirp. The miss Detection Error Rate and False Alarm Rate are evaluated to show the effectiveness of the proposed interference detection technique.     

基于形态滤波的心电信号基线矫正算法

基线矫正是心电(ECG)信号预处理中的一个重要步骤.本文提出了一个基于形态滤波的ECG信号基线矫正算法.首先,对原始输入ECG信号进行基于相同结构元素的形态开闭-闭开滤波,抑制其中的QRS波群;然后,采用两个不同宽度的结构元素,对去除QRS波群后的ECG信号进行广义形态开-闭滤波,分离出基线漂移信号;最后,用原始ECG信号减去估计出的基漂信号,得到经过基线矫正的ECG信号.仿真实验与实际应用结果表明,本文方法不仅可以有效去除ECG信号中的基漂干扰,而且较好地保持了ECG信号的原有特征形态,处理效果明显优于以往算法.     

复信号去噪的正则化方法

针对复信号,提出了一种新的基于正则化的去噪方法。在借鉴Tikhonov正则化参数选择方法的基础上,给出了最优正则化参数的自动选择方法。与目前大多数仅在实数域的去噪方法不同,它可直接对复信号进行处理。仿真计算结果表明,该方法有较好的去噪能力,同时能够有效地保护信号中的重要特征。     

改进的小波变换用于处理FBG信号

解调系统是光纤布拉格光栅（FBG）传感技术的核心。信号去噪和峰值搜索是影响FBG 传感系统精确解调的两个重要因素。为提高测量精度,文中针对传统方法存在的缺陷,提出了一种新的FBG 波长解调方法,此解调方法由一种改进的去噪方法与高斯拟合寻峰算法组成。采用平移不变量小波与文中提出的改进阈值和改进阈值函数相结合的方法来处理FBG 含噪信号;然后采用高斯拟合寻峰算法对去噪信号作进一步解调。实验结果表明,改进阈值的平移不变量小波能处理不同的FBG 含噪信号,该方法获得的信噪比和均方差性能优于传统小波阈值去噪法以及其他改进的小波去噪法;该改进小波的波长解调方法测量的峰值误差低于1pm,比常用的波长解调方法具有更高的测量精度。     

Theoretical aspects of vertically invariant gray-levelmorphological operators and their application on adaptive signal andimage filtering

We use vertically invariant morphological filters for time-varying or adaptive signal processing. The morphological filters adopted in this paper are vertically invariant openings and closings. Vertically invariant openings and closings have intuitive geometric interpretations and can provide different filtering scales with respect to different spatial positions. Hence, they are suitable for adaptive signal filtering. To adaptively assign structuring elements of the vertically invariant openings or closings, we develop the progressive umbra-filling (PUF) procedure. Experimental results have shown that our approach can successfully eliminate noise without oversmoothing the important features of a signal