Saw-based chirp fourier transform and its application to analogue on-board signal processing

This paper reports on the work done at ELAB-RUNIT on surface acoustic wave (SAW) on-board signal processing. The main processing is done by the analogue chirp Fourier transformer (CFT) and its inverse (ICFT). In a CFT, the input signal is transformed from an FDMA format to a TDM format and at the same time filtered by a filter bank. By multiplying and convolving the signal with chirp waveforms, the CFT is implemented by one bandpass cover filter and one chirp filter. The paper demonstrates that SAW reflector array compressors (RAC) built by ELAB-RUNIT have suitable chirp responses and adequate precision for digital satellite communication. Two applications are described. An on-board multicarrier demodulator (MCD) for 9·6 kb/s QPSK carriers and a processor for filtering, routeing and beam steering (FROBE) for flexible transparent repeaters. For MCDs the use of SAW CFTs leads to a power consumption for demultiplexing and A/D conversion of 15 mW per carrier with room for improvements. For transparent paylods, the FROBE leads to more flexibility and narrower guardbands than can be obtained by other analogue processors.     

分布式光纤传感系统的全数字信号处理

文章介绍了一种新颖的全数字分布式光纤Sagnac传感系统信号处理方案,重点阐述了闭环检测电路、基于FPGA和DSP的全数字信号处理方法、电路设计及调试.实验结果表明,该系统具有很高的性能.     

基于伪逆算子的超分辨率信号处理方法研究

为了解决信号压缩过程中旁瓣串扰问题并提高参数估计时频率的估计精度,在研究超分辨信号处理理论的基础上,从框架理论入手,提出了可改善系统性能的恒噪声灵敏度分解算法。首先在基于矩阵表示的超分辨信号处理模型的基础上,采用矩阵伪逆算子,进行基于信号压缩的微波成像处理,讨论了伪逆算子应用于信号分解过程中的噪声性能;然后针对伪逆算子导致系统噪声增益增加的问题,通过根据信号处理的噪声指标要求设定处理门限,实现对信号的超分辨处理。仿真实验结果表明,该方法可消除匹配滤波类算法不可避免的旁瓣串扰问题,并可在一定程度上改善系统分辨率性能。     

小波变换与匹配滤波耦合的激光雷达弱信号处理

远距离激光雷达回波信号弱,干扰强,处理比较困难。距离越远,得到的有用信号就越弱。为了提高激光雷达检测距离,对弱信号进行数字信号处理就显得很重要。采用一般方法常将干扰信号判断成有用信号,从而影响了激光雷达的工作能力。夺文采用小波变换和匹配滤波耦合的方法对激光雷达弱信号进行处理,既能从强噪声中提取有用信号,又能有效的去掉强干扰信号。采用一台TEA—CO2激光器进行实验,当采样速率达到200MHz时,对于信噪比大于1．2的含噪信号能有效地去掉噪声和强干扰信号,在保持原信号特征的情况下,准确地提取出有效的弱信号。这就有效地提高了激光雷达的工作能力。     

Solution to some electromagnetic problems using fast Fourier transform with conjugate gradient method

Using the fast Fourier transform (FFT) to compute the convolution integrals that appear in the conjugate-gradient method (CGM), an efficient numerical procedure to solve electromagnetic problems is obtained. In comparison with the method of moments (MM), the proposed FFT-CGM avoids the storage of large matrices and reduces the computer time by orders of magnitude.     

Commutative reduced biquaternions and their Fourier transform for signal and image processing applications

Digital signal and image processing using reduced biquaternions (RBs) are introduced in this paper. RBs are an extension of the complex numbers, following the doubling procedure. Two useful representations of RBs (e/sub 1/-e/sub 2/ form and matrix representation) are discussed in this paper. Besides, we propose a new representation of RBs (the polar form) to calculate the multiplication and conjugation of RBs easily. Furthermore, we define a unique and suitable RB norm and its conjugate. These definitions are similar and compatible with the complex numbers. The efficient algorithms of the discrete reduced biquaternion Fourier transform (DRBFT), convolution (DRBCV), correlation (DRBCR), and phase-only correlation are discussed in this paper. In addition, linear-time-invariant and symmetric multichannel complex systems can be easily analyzed by RBs. For color image processing, we define a simplified RB polar form to represent the color image. This representation is useful to process color images in the brightness-hue-saturation color space. Many different types of color template matching and color-sensitive edge detection (brightness, hue, saturation, and chromaticity matched edges) can be performed simultaneously by RBs.     

HHT在激光云高仪后向散射信号处理中的应用

根据半导体激光云高仪后向散射信号的特点,基于希尔伯特-黄变换(HHT)提出了一种突出后向散射信号细节特征的处理方法。该方法有效地发挥了HHT对非线性、非平稳信号处理的能力,从原始后向散射信号中分别重构出初步去噪项和信号趋势项并实现二者的结合,从而生成全新的经特征突出的后向散射信号。大量实验数据分析证明,该特征突出方法利用了EMD分解和重构滤波的优势,摒弃了其去噪同时削弱有用信号、忽略细节特征的缺陷,适用于云高仪后向散射信号处理;配合相应的后向散射参数反演方法,可以有效提高云高识别能力和垂直能见度反演的精度,降低了云高误报和漏报率。     

APPLICATION OF FM^m let TRANSFORM TO SIGNAL SEPARATION

Since the multicomponent signal with nonlinear time-frequency structures occupies a wide frequency band ,and the spectral contents may alias,it is therefore diffcult to separate the signal components and to separate the signal from background noise .In this paper ,a new signal separation method using FM^m let transform is proposed by taking the advantage that the atoms of FM^m let transform can match both the linear and nonlinear time-varying structures.Theoretical predictions and numerical experiments show the feasibility of the methodology advocated.     

匹配傅里叶变换快速算法及在雷达信号处理中应用

为了减小匹配傅里叶变换分析的计算量,提出了一种基于快速傅里叶变换的快速算法。根据匹配傅里叶变换的分解将积分形式转化为离散形式,推导出快速算法表达式。该算法与直接的数值离散匹配傅里叶变换算法相比较,计算量大大减少。同时给出了其在雷达信号处理中线性调频信号的检测与参数估计的应用。理论及计算机仿真结果表明了该算法的有效性和精确性,有良好的工程应用前景。     

The application of bionic wavelet transform to speech signal processing in cochlear implants using neural network simulations

Cochlear implants (CIs) restore partial hearing to people with severe to profound sensorineural deafness; but there is still a marked performance gap in speech recognition between those who have received cochlear implant and people with a normal hearing capability. One of the factors that may lead to this performance gap is the inadequate signal processing method used in CIs. This paper investigates the application of an improved signal-processing method called bionic wavelet transform (BWT). This method is based upon the auditory model and allows for signal processing. Comparing the neural network simulations on the same experimental materials processed by wavelet transform (WT) and BWT, the application of BWT to speech signal processing in CI has a number of advantages, including: improvement in recognition rates for both consonants and vowels, reduction of the number of required channels, reduction of the average stimulation duration for words, and high noise tolerance. Consonant recognition results in 15 normal hearing subjects show that the BWT produces significantly better performance than the WT (t = -4.36276, p = 0.00065). The BWT has great potential to reduce the performance gap between CI listeners and people with a normal hearing capability in the future.     

On strategies of multiuser MIMO transmit signal processing

In this letter, we introduce five different strategies of linear transmit signal processing for multiuser multiple-input multiple-output (MIMO) systems and provide performance comparisons in terms of maximum throughput in both uncorrelated and correlated channels when the number of transmit antennas is much larger than the number of receive antennas. It is shown that the multiuser MIMO schemes are preferable to time-division multiple-access (TDMA)-based MIMO schemes, hence demonstrating the power of multiuser MIMO signal processing. Our work also indicates possibilities for future research in finding efficient suboptimal algorithms. As an example, we show that our multiuser MIMO decomposition scheme can improve the maximum throughput compared to TDMA-based MIMO schemes for large number of transmit antennas or high transmit power.     

多速率信号处理在通信系统中的应用

讨论了通信系统中多速率信号处理技术,即现应用于软件无线电中的抽样率转换 技术及其具体的实现方法。利用多速率信号处理的方法,降低接收端采样后的数据速率,以减 小后级处理的运算量。针对仿真中由滤波器引起的信号码间干扰失真,提出了两种补偿滤波 器的方案,并通过实例说明了该方案的可行性。     

On algorithms for digital signal processing of sequences

In this work, we analyze the algebraic structure of fast algorithms for computing one- and two-dimensional convolutions of sequences defined over the fields of rational and complex rational numbers. The algorithms are based on factorization properties of polynomials and the direct sum property of modulo computation over such fields. Algorithms are described for cyclic as well as acyclic convolution. It is shown that under certain nonrestrictive conditions, all the previously defined algorithms over the fields of rational and complex rational numbers are also valid over the rings of finite integers. Examples are presented to illustrate the results.     

On the roots of digital signal processing. Part I

The roots of what we refer to today as digital signal processing are actually the roots of modern mathematics and to trace the evolution of DSP we need to go back to Newton, even to the great Archimedes of Syracuse. This two-part article will attempt In a not-so-rigorous exposition to outline the major historical developments that led to DSP     

傅里叶变换与小波变换在信号去噪中的应用

对于高频信号和高频噪声干扰相混叠的信号,采用小波变换去除噪声可以避免用傅里叶变换去噪带来的信号折损。对于噪声频率固定的平稳信号,在对信号进行傅里叶变换后使用滤波器滤除噪声。对高频含噪信号则采用正交小波函数sym4对信号分解到第4层,利用极大极小值原则选择合适的阈值进行软阈值处理,最后利用处理后的小波系数进行重构。实验结果表明,对于高频含噪信号傅里叶去噪会出现严重的信号丢失现象,使用极大极小值原则选择阈值进行小波去噪可以有效地保留高频部分的有用信号。