低采样率下经验模态分解性能提升研究

经验模态分解(EMD)使用信号极值点的位置和取值信息进行分解,对采样率有较高的要求。针对EMD在低采样率下性能降低的现象,提出一种基于B样条拟合的信号局部均值计算方法。首先提取信号极值点出现的时刻作为尺度,然后通过对极值点时刻进行重新采样构造B样条节点,最后应用B样条最小二乘拟合方法直接计算局部均值。与EMD方法相比,该方法不需要信号极值点的准确位置和取值,因此不容易受到低采样率的影响。对平稳信号和非平稳信号的仿真结果表明,该方法能在接近奈奎斯特频率的低采样率下获得较高的性能。与基于插值的解决方案相比,该方法的分离性能更好。     

通用周期信号高速数据采集系统的设计

采集卡受Ａ／Ｄ转换速度的影响，采样率一般都较低，本文介绍的系统采用等效时间原理，利用低采样率Ａ／Ｄ转换器件实现对周期性信号的高速数据采集，并可根据需要调整采样率的大小。本系统分软，硬件两部分，可实际于雷达，信号源等系统中，性能稳定，可靠。     

宽带声学多普勒流速剖面仪的中频正交采样算法

宽带声学多普勒流速剖面仪(Broadband Acoustic Doppler Current Profile,BBADCP)发射由伪随机编码调制的正弦信号,信号带宽在频域上产生展宽,成为带通信号。宽带回波信号的处理多采用正交解调的方法,但此方法对采样率的要求较高,硬件较难实现。利用数字中频正交采样法来实现,大大降低了采样频率,并且针对BBADCP解模糊速度的要求,进行了宽带回波信号的仿真试验,结果证明插值的数字中频正交采样法适合于BBADCP的信号处理。     

IGS精密星历插值方法研究

目前IGS提供的精密星历一般采样率为15 min的星历,这远远不能满足高动态精密定位用户的要求,因此我们需要采用合理的数学模型计算所需历元的坐标。本文通过对常用的几种插值方法进行比较,得出了一些有益的结论。     

多项滤波器算法在水声信号处理中的研究和仿真

主要对多项滤波器算法在水声信号处理中的应用进行了理论分析和算法仿真.为实现抽样率转换而产生的多项滤波器算法,通过对信号进行抽取和插值相结合的方法来控制信号的抽样率.对抽取-插值滤波器依照减少乘法运算次数的原则进行结构上的简化,并进行数学推导,最终得到多项滤波器的结构框图和数学表达式.运用MATLAB对多项滤波器算法进行仿真,并对仿真结果作了理论分析.     

基于等效源法插值的声场重放方法

声场重放旨在保留声音内容与声场空间特性,创造或再现一个真实的空间声学环境.一套在真实"听音室"实现的声场重放听音系统,需要对扬声器阵列的声传递函数进行多次测量,这个过程繁琐且耗时.文章提出一种等效源法插值重放方法,在传声器采样率较低的情况下,实现了扬声器阵列声传递函数在整个目标重放空间内的插值.对比传统的声压匹配法,所...     

合成孔径声呐Chirp Scaling成像算法

在合成孔径声呐领域中经典的成像处理方法是距离-多普勒算法。距离-多普勒算法的主要缺点是在进行方位处理时需要进行距离二次脉压和在进行距离徙动校正时需要进行插值处理,这样将导致运算量迅速增加,并且降低了成像精度。而ChirpScaling算法是在二维频域中精确实现距离门徙动校正和二次距离压缩,避免了插值运算,用该算法处理了仿真点目标的回波数据,结果表明该算法既能够实现更加精确的成像又能够避免插值运算而提高运算效能。     

基于插值矩阵技术与二维空间平滑法的近场相干声源识别研究

在研究插值矩阵技术与二维空间平滑法两种方法的基础上,将两者进行结合,提出了一种对近场相干声源进行识别的方法。首先通过插值矩阵技术把实际阵列接收到的近场信号转换为形式上的远场信号,然后通过二维空间平滑法求出阵列的平滑协方差矩阵,再由平滑协方差矩阵得到给定方向向量对应的信号功率,实现二维相干声源的识别。算例表明,该方法比传统的波束形成能更准确地定位出声源的位置。     

CW脉冲回波信号的最小方差无畸变响应自适应检测

建立了适用于解析时间序列信号检测的最小方差无畸变响应(Minimum Variance Distortionless Response,MVDR)自适应处理模型(Time Series MVDR,TSMVDR),并针对CW声纳脉冲回波信号,通过构造解析信号和分段近似处理给出了相应算法(Algorithms of TSMVDR on CW pulse signal,AWMVDR),并进行了数值仿真研究。研究结果表明:对于CW脉冲信号:(1)在较高采样率的条件下,AWMVDR可以实现CW脉冲信号稳定的自适应检测;(2)AWMVDR较常规线性相关检测具有更高的脉冲参数估计精度和时间分辨力;(3)AWMVDR的实现需要付出较高采样率和更大计算量的代价。     

基于迭代插值的实复转换频率估计算法

为消除实信号中负频率成分对频率估计的影响,提出一种基于迭代插值的实复转换频率估计算法。通过预估计采样信号频率,构造参考信号,并通过90°相移得到采样信号的正交分量;将采样信号与其正交分量合成为复信号实现实复转换,抑制负频率成分的影响;利用迭代插值算法估计复信号的频率,重新构造参考信号并生成正交分量与复信号,并对复信号进行频率估计,得到精确的频率值。仿真实验表明:所提算法消除了负频率成分的影响,改善了抗噪性,提高了估计精度,使得频率估计的均方误差更接近于克拉美罗下限。此外,在LFMCW雷达上进行了实测实验,验证了所提算法的有效性。     

A simple adjustable window algorithm to improve FFT measurements

The Fourier spectrum of a periodic signal may be obtained by fast Fourier transform algorithms, but, as is well known, special care must be taken to avoid severe distortions introduced by the sampling process. The main problem is the leakage generated by the truncation required to obtain a finite length sampled data. The usual procedure to reduce leakage is to multiply the sampled signal by a weighting window. Several kinds of windows have been proposed in the literature, and today they are also included in many commercial instruments. A simple alternative procedure is proposed in this paper. It is implemented with a PC compatible data acquisition board (DAQ) and consists of an algorithm that uses decimation and interpolation techniques. This algorithm is equivalent to the use of an adjustable sampling frequency and correspondingly an adjustable window size. Results obtained by this method on both harmonic and polyharmonic signals are empirically analyzed and compared with those given by an instrument with built-in FFT capabilities     

Measuring power system harmonics and interharmonics by an improved fast Fourier transform-based algorithm

The fast Fourier transform (FFT) has been widely used for the signal processing because of its computational efficiency. Because of the spectral leakage and picket-fence effects associated with the system fundamental frequency variation and improperly selected sampling time window, a direct application of the FFT algorithm with a constant sampling rate may lead to inaccurate results for continuously measuring power system harmonics and interharmonics. An improved FFT-based algorithm to measure harmonics and interharmonics accurately is proposed. In the proposed algorithm, a frequency-domain interpolation approach is adopted to determine the system fundamental frequency, and the interpolatory polynomial method is applied to reconstruct the sampled time-domain signal; it is followed by using the FFT to calculate the actual harmonic components. Then, the frequency-domain interpolation is again applied to find the interharmonic components. The performance of the proposed algorithm is validated by testing the actual measured waveforms. Results are compared with those obtained by directly applying a typical FFT algorithm and by the IEC grouping method. It shows that the solutions determined by the proposed algorithm are more accurate, and a reasonable computational efficiency is maintained.     

Interpolation methods for time-delay estimation using cross-correlation method for blood velocity measurement

The cross-correlation method (CCM) for blood flow velocity measurement using Doppler ultrasound is based on time delay estimation of echoes from pulse-to-pulse. The sampling frequency of the received signal is usually kept as low as possible in order to reduce computational complexity, and the peak in the correlation function is found by interpolating the correlation function. The parabolic-fit interpolation method introduces a bias at low sampling rate to the ultrasound center frequency ratio. In this study, four different methods are suggested to improve the estimation accuracy: (1) Parabolic interpolation with bias-compensation, derived from a theoretical signal model. (2) Parabolic interpolation combined with linear filter interpolation of the correlation function. (3) Parabolic interpolation to the complex correlation function envelope. (4) Matched filter interpolation applied to the correlation function. The new interpolation methods are analyzed both by computer simulated signals and RF-signals recorded from a patient with time delay larger than 1/f(0), where f(0) is the center frequency. The simulation results show that these methods are more accurate than the parabolic-fit method. From the simulation, the worst estimation accuracy is about 1.25% of 1/f(0) for the parabolic-fit interpolation, and it is improved by the above methods to less than 0.5% of 1/f(0) when the sampling rate is 10 MHz, the center frequency is 2.5 MHz and the bandwidth is 1 MHz. This improvement also can be observed in the experimental data. Furthermore, the matched filter interpolation gives the best performance when signal-to-noise ratio (SNR) is low. This is verified both by simulation and experimentation.     

一类非均匀采样信号的内插重构算法

本针对多路Ａ／Ｄ交替采样存在的采样非均匀现象,分析了此类非均匀采样信号 ,进而推导出其内插重构算法,并通过计算机仿真验证了算法的正确性。该重构算法在工程实际中具有应用价值。     

基于慢度估计的次声台阵信号自动检测算法及应用

针对次声监测研究领域广泛使用的短时间与长时间信号功率比检测方法性能不能满足要求,渐进多通道互相关检测算法虚警率较高的缺点,利用信号的时、频、波数域特性和次声台阵各子台信号的互相关性特性,提出了一种基于次声台阵信号慢度估计的自动检测算法。次声信号慢度估计结果的合理性、一致性是该检测算法的依据。考虑到该检测算法计算量较大,在具体应用中加入其他计算量较小的传统算法,进行逐次检测,最后应用的慢度估计方法既是一种检测方法,也是对其他检测算法结果的最终审核,一方面可以降低单项检测方法对检测参数的敏感性,另一方面也可提高检测的正确率(虚警率和漏警率同时降低)。该复合检测算法应用于某实验次声台站信号的检测(信噪比大于1.1),结果虚警率为4.0%,漏警率为5.0%,表明了该方法的优良性能。从检测应用处理结果还可以推测,结合一个区域现有密集的地震台站数据和2~3个次声台阵的数据,可以方便地识别、监控爆破方式日益复杂的人工爆破事件和真正的地震(余震)事件,为地震灾害减灾防灾、采矿监控等多领域服务,具有重大推广价值。     

A new algorithm for improving the accuracy of periodic signalanalysis

Digital periodic signal analysis often requires synchronized sampling with the signal being analyzed. In certain practical situations, however, this condition is difficult to satisfy. As a result, a number of undesirable effect such as the spectral leakage associated with the discrete Fourier transform (DFT), and the truncation errors in digital wattmeters arise and degrade system performance. This paper presents a new approach which attempts to remedy the underlying problem. The basic idea of the proposed method is to modify the actual sampled sequence such that it becomes an ideal sample sequence which is synchronized with the signal subjected to sampling. A simple algorithm for modifying the sampled sequence on-line is derived based on interpolation. The proposed approach requires quite modest additional computational burden which makes it suitable for real-time signal professing. To illustrate the practical applicability of the proposed algorithm, the paper considers two distinct but common cases. First, it shows how the proposed method can be used in the case of DFT analysis of harmonic signals, and secondly, it considers the digital wattmeter application area in electrical power-system measurement. Results show that the proposed algorithm is capable of reducing both the leakage effect in DFT analysis and truncation errors in digital wattmeters     

利用二维插值核的高分辨力图像重构

利用连续图像采样及其内插公式,提出了一种基于二维插值核重建高分辨力图像的新算法。该算法先使一般低分辨力序列图像具有标准位移关系,再根据高、低分辨力图像之间的关系重构高分辨力图像。同时利用正则化技术导出了一套重复迭代算法,以提高算法的处理效果和克服病态问题。实验表明,该算法使图像的细节和清晰度大大增强,分辨力大幅度提高,明显优于零阶保持插值算法的处理结果,其峰值信噪比提高8-9dB。     

变速机械振动信号的伪同步重采样技术——Ⅰ速度与角位置的瞬时估计方法

在机械的变速运行过程中,由于存在非平稳性,使得大部分等时间间隔采样的传统方法无法适用。利用光电编码器进行角域采样虽可以快速跟踪转速的变化,但其使用安装却要受机械装置结构的限制。为解决机械变速过程状态信号的解调和特征提取问题,本文提出了一种新的数据获取和预处理方法——伪同步信号重采样技术。该技术通过对瞬时转速和角位置的估计以及对非平稳信号的自适应重采样,获取了与转速有关的信息并应用常规的信号处理方法进行特征提取。 本文主要探讨转速和角位置的瞬时估计。计算机仿真和实验验证的结果表明,改进型三次样条函数插值可以给出足够精度的估计结果。     

Design and Implementation of a Fuzzy Area-Based Image-Scaling Technique

In this paper, we propose the design and implementation of an interpolation scheme for performing image scaling by utilizing a dynamic mask combined with a sophisticated neighborhood averaging fuzzy algorithm. The functions that contribute to the final interpolated image are the areas of the input pixels, overlapped by a dynamic mask, and the difference in intensity between the input pixels. Fuzzy if–then rules for these two functions are presented to carry out the interpolation task. Simulation results have shown a fine high-frequency response and a low interpolation error, in comparison with other widely used algorithms. The interpolation can be applied to both gray-scale and color images for any scaling factor. The proposed hardware structure is implemented in a field-programmable gate array (FPGA) chip and is based on a sequence of pipeline stages and parallel processing to minimize computation times. The fuzzy image interpolation implementation combines a fuzzy inference system and an image-interpolation technique in one hardware system. Its main features are the ability to accurately approximate the Gaussian membership functions used by the fuzzy inference system with very few memory requirements and its high-frequency performance of 65 MHz, making it appropriate for real-time imaging applications. The system can magnify gray-scale images of up to 10-bit resolution. The maximum input image size is 1024 $times$ 1024 pixels for a maximum of 800% magnification.      

Triangular Self-Convolution Window With Desirable Sidelobe Behaviors for Harmonic Analysis of Power System

Weak harmonic components can easily be obscured by nearby strong harmonics due to the spectral leakage in the power system. To obtain a window suitable for solving the problem, the Triangular self-convolution window (TSCW) is constructed, with the Triangular window being the parent window to take advantages of its narrow major lobe and simple computation. A TSCW-based phase difference correction algorithm for calculating the power system signal parameters, such as frequency, phase, and amplitude, is presented in this paper. The TSCW has a low peak sidelobe level, a high sidelobe rolloff rate, and a simple spectral representation. Leakage errors and harmonic interferences are thus considerably reduced by weighting samples with the TSCW. The TSCW-based phase difference correction algorithm is free of solving high-order equations, and the overall method can easily be implemented in embedded systems. The effectiveness of the method proposed was analyzed by means of computer simulations and practical experiments for multifrequency signals without noise and with quantization noise.