Information rates of multidimensional front ends for digital storage channels with data-dependent transition noise

This paper presents a simulation-based method for the computation of the information rates of recently proposed multidimensional front ends for digital storage channels with transition noise. First, we propose an algorithm, based on linear prediction and state reduction techniques, that extends recent work on the information rates of magnetic recording channels affected by colored Gaussian thermal noise, intersymbol interference, and signal-dependent transition noise. Following a previous study on statistical sufficiency, we apply this algorithm to compute the information rates of digital storage systems featuring a multidimensional detection front end. The resulting information rates indicate that significant gains may be achievable by multidimensional signal processing techniques in transition-noise-limited digital storage channels.     

基于最大相关熵准则的水下生物脉冲噪声消除方法

近海生物噪声表现为脉冲噪声,这一类噪声显著降低了水声通信系统的性能。结合水声信道的稀疏特性,提出一种基于最大相关熵准则的级联滤波器算法,该算法实现了脉冲噪声的消除及稀疏信道估计。第一级自适应滤波器完成对噪声的消除工作,第二级滤波器对去噪后的信号进行稀疏信道估计。该方法的优势在于无需知道信号和噪声的相关信息。仿真结果表明,提出的方法比单一的滤波器结构和传统信道估计算法性能更加优越。     

Far-end crosstalk identification method based on channel training sequences

Far-end crosstalk identification results to improved frequency spectrum utilization in asymmetric digital subscriber line (ADSL) systems. The accurate determination of the crosstalk coupling function is a demanding task that is affected by various system impairments. In this paper, we present a new real-time method that exploits the exchange of signaling information between the modems of a new activated ADSL line in order to determine the crosstalk function between this line and any other active line in the binder. Each remote modem subtracts the decoded data from the received signal, decreases the noise effect of the previously identified crosstalkers, is synchronized to the disturber's timing and then applies a least-squares estimator for identifying the new crosstalk coupling function. The method is used along with a maximum margin bit-loading algorithm in order to provide the best possible estimation results. The estimated crosstalk coupling functions, the transfer function of each line and the noise measurements can be exploited by a centralized bit-loading algorithm for maximizing the total system performance in terms of maximum achievable data rate and/or bit error rate.     

基于高阶累积量的高精度时延估计算法

针对海洋探测中由于接收信号信噪比低并存在各种噪声干扰导致时延估计精度低的问题,提出一种基于二次相关和高阶累积量的具有多种噪声抑制能力的高精度时延估计新方法——SC-HOCS法。该方法首先对两路接收信号进行自相关和互相关处理,抑制部分高斯噪声,然后利用高阶累积量一维切片法对信号进行处理,抑制相关高斯噪声和非高斯色噪声,通过对接收信号的上述处理提高信噪比,最后结合希尔伯特变换对相关峰进行锐化处理,进一步提高时延估计精度。与广义相关法、二次相关法及高阶累积量一维切片法相比,该方法能很好地抑制相关噪声并且能在更低的信噪比下获得较好的时延估计精度,同时该算法计算量较小,可满足对数据实时处理的需求。计算机仿真和水池实验验证了该方法的有效性。该方法为海洋探测中低信噪比信号的高精度时延估计提供一种新的技术途径。     

Efficient DFT-based channel estimation for OFDM systems on multipath channels

An improved discrete Fourier transform (DFT)-based channel estimation for orthogonal frequency division multiplexing systems is proposed. Conventional DFT-based channel estimations improve the performance by suppressing time domain noise. However, they potentially require information on channel impulse responses and may also result in mean-square error (MSE) floor due to incorrect channel information such as channel delay spread. In contrast, our purposed channel estimation can improve the performance by deciding significant channel taps adaptively without requiring any channel statistical information. Significant channel taps are detected on the basis of a predetermined threshold. The optimal threshold to reduce the MSE of the estimation is also derived, and it is confirmed by computer simulation. Simulation results demonstrate that the proposed algorithm can improve the MSE performance ~6.5 dB compared with the conventional DFT-based estimation, and the MSE floor is not observed in any channels.     

Turbo-coded optical recording channels with DVD minimum mark size

Recent work on turbo codes applied to partial response (PR) optical recording channels has focused on unconstrained channels. In this paper, we consider the application of turbo codes to a (1,7) constrained, PR-equalized optical recording channel with digital versatile disc (DVD) parameters. The addition of a (1,7) run-length-limited (RLL) constraint requires the use of a soft RLL decoder to communicate with the turbo code. Although soft RLL decoders were previously developed for use with iterative decoding, application to a practical optical channel has not been addressed until now. Here, results on both correlated noise and media noise optical recording channel models are given for two PR targets, 1+D and 1+D+D²+D ³. We achieved coding gains of 4 to 6.3 dB over a baseline RLL-coded system. We also evaluated system performance at smaller mark sizes, and found that density gains of 17% and 22% are achievable for the two targets, respectively     

Flaw signature estimation in ultrasonic nondestructive evaluation using the Wiener filter with limited prior information

Flaw signals measured in ultrasonic testing include the effects of the measurements system and are corrupted by noise. The measurement system response is both bandlimited and frequency dependent within the bandwidth, resulting in measured signals which are blurred and distorted estimates of actual flaw signatures. The Wiener filter can be used to estimate the flaw's scattering amplitude by removing the effect of the measurement system in the presence of noise. A method is presented for implementing an optimal form of the Wiener filter that requires only estimates of the noise distribution parameters. The theoretical error for scattering amplitude estimation, assuming various levels of available prior information, is analyzed. Three estimation techniques, one a maximum-likelihood based method and the other two residual-sum-of-squares methods, are formulated and tested. The results demonstrate that any of the three approaches could be used to optimally implement the alternative form of the Wiener filter with limited prior information.     

Basic binary state-space model for time-varying communication channels: uncertainty and information capacity

This paper looks at capacity achieving detection strategies for information transfer over time-varying channels. The time-varying binary symmetric channel (TV-BSC) is identified as the basic binary state-space model. Separation of entropies principles and the TV-BSC model-based state-space approach are used to determine the performance bounds for coherent and non-coherent detection over time-varying communication channels. The mutual information rate over the TV-BSC, assuming channel estimation in the presence of channel noise, is shown to be below the channel information capacity because of lack of perfect channel knowledge. Furthermore, it is shown that TV-BSC model-based differential detection has a fundamental advantage over the channel estimation based detection since it theoretically preserves the TV-BSC information capacity when the observation interval approaches infinity. Simulation analysis corroborates the theoretical results, showing that multiple-symbol differential detection practically achieves the TV-BSC capacity in just a few symbol observation times.     

线性回归模型中的递推辨识及其应用

摘要：因机械系统振动响应离散差分方程可以改写为关于结构模态参数的线性回归形式,对于此线性回归形式中的结构模态参数的辨识问题可转化为系统辨识理论中线性回归模型的未知参数矢量的辨识估计问题。当系统对象在白噪声激励下,常规的最小二乘辨识法可以给出参数估计的无偏估计。当系统对象在有色噪声作用下,在常规最小二乘辨识法的基础上提出一种新的可分离迭代最小二乘辨识法。在缺乏关于噪声的统计先验信息,仅有噪声为未知但有界的情况下,提出一种带死区的最小二乘辨识法,该辨识法不仅能给出未知参数矢量的一致性无偏估计,而且还能保证参数估计值逐渐向真值靠拢,任何相邻两估计值之间的逼近程度远远小于噪声的上界。在有界噪声出现的情况下,该算法的鲁棒性可以通过在参数修正方程中引入死区的方法来增强。最后用理论上的仿真算例和弹簧-质量-阻尼系统的振动响应来验证两方法的有效性和可行性。     

The efficiency of methods for measuring A/D converter linearity

In this paper, the efficiency of three methods commonly used to measure the linearity characteristics of precision Nyquist-rate analog-to-digital (A/D) converters is evaluated. The efficiency of each method, which is determined by the time required to obtain linearity estimates at a specified level of accuracy, is compared to the maximum efficiency that is theoretically achievable, as given by the Cramer-Rao bound. Simulation results are presented for two open-loop measurement methods, the tally and weight method and the code density method, demonstrating that the code density method obtains an efficiency close to the theoretical optimum over a wide range of measurement times and converter noise levels, whereas the tally and weight method falls short of the optimum for converters with noise levels exceeding ¼ LSB. The efficiency of the servo loop method, a common closed-loop method for measuring linearity, is similarly evaluated, and is found to fall short of the maximum efficiency that is theoretically achievable in the closed-loop configuration. A modified closed-loop measurement method is described that obtains an efficiency close to the theoretical optimum through the use of maximum-likelihood estimation     

噪声相关条件下多传声器时延多尺度估计

提出一种基于小波分解的多尺度时延估计方法,解决非稳态、有色噪声且通道间噪声存在相关性的条件下提高时延估计精度问题,并把这一理论应用于声阵列对声源的定位.利用小波良好的时间-频率分解性能将非稳态信号分解为多个稳态信号,同一尺度内进行互相关获得多尺度时延值,并证明了小波分解不会改变信号之间的固有时延值.针对不同尺度内时延值不一致、无法识别出正确时延值这一问题,提出用三传声器之间时延匹配关系消除噪声相关性,来识别正确时延,从而实现非稳态、噪声相关条件下的时延估计.最后通过正四方形声阵列试验检验了该方法,试验证明:该方法不但提高了识别率、细化和突出了相关函数的波峰,还提高了时延估计的稳定性和精度.     

OFDM水声通信系统的LS-OMP信道估计

对于正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)水声通信系统,最小二乘(Least Squares,LS)信道估计方法受噪声影响较大,并且使用的导频数量较多,影响通信效率。而基于压缩感知理论的正交匹配追踪(Orthogonal Matching Pursuit,OMP)信道估计方法可以充分利用水声信道的稀疏特性,同时能够有效地抑制系统噪声,但控制迭代运算次数的相关参数(稀疏度或误差容忍值)是OMP算法的关键条件。针对上述问题,提出了利用少量导频随机分布的LS和OMP联合的信道估计方法,该方法首先利用少量导频采用LS方法估计出OMP算法的误差容忍值,再利用OMP算法恢复数据子载波的信道信息。理论分析和仿真结果同时表明,与传统的LS算法或OMP算法相比,新算法能够在数据恢复的同时有效抑制系统噪声,应用稀疏特性及较少量的导频,进一步提高了系统的频谱效率,对时变稀疏水声信道具有更好的适应性。     

广义互相关时延估计声定位算法研究

针对地面目标声定位因信噪比较低而定位精度差的现象,提出了基于广义互相关法的声定位系统,根据平面四元法目标定位计算式,研究了广义互相关算法在实际中的应用。环境噪声、军事目标声和民用目标声频谱范围大多集中,即出现目标声会与背景噪声高度重合的情况,发现一般加窗滤波法在降低噪声的同时亦会将目标声强度大大削弱,而广义互相关时延估计法是通过计算两路信号互相关函数的最大值而求得时延差,其精度高、稳定性好。通过计算机仿真得到在信噪比较低的情况下,加窗滤波因大大削弱目标声强度而造成定位精度较低,而利用广义互相关方法可得到较为精确的声定位坐标。     

Blind channel estimation for multiple input multiple output uplink guard-band assisted code division multiple access systems with layered space frequency equalisation

Single carrier (SC) code division multiple access (CDMA) with block transmission has been shown to be more effective while utilising a low-complexity equaliser to combat frequency-selective fading channels, when compared with conventional direct sequence CDMA technology. It also has lower peak-to-average power ratio and lower frequency sensitivity compared with multicarrier CDMA. The authors propose two blind channel estimation methods for uplink multiple input multiple output SC-CDMA systems with block transmisssion-one is the subspace-based method and the other is the so-called autocorrelation contribution method (ACM). Both the methods provide close performance to the case with perfect channel knowledge at high signal-to- noise ratio (SNR) without any training data required. It is shown that ACM yields a better performance than the subspace method at a lower SNR, and a similar performance at a high SNR, with the advantages of avoiding rank determination and noise power estimation as in the subspace method. In addition, the authors integrate layered space frequency equalisation with blind channel estimation, which provides improved performance over the conventional linear equalisation, by employing successive interference cancellation.     

基于三阶累积量及自适应滤波时延估计的管道定位方法

针对直接互相关被动时延估计法定位管道异常振动事件存在噪声干扰影响定位精度的问题,提出了基于三阶累积量及自适应滤波时延估计的管道异常事件定位方法。该方法对顺、反两路异常振动信号进行三阶自累积量和互累积量估计,抑制高斯相关噪声和对称分布噪声。然后利用自适应滤波时延估计算法对三阶自累积量和互累积量信号的时延进行迭代计算,在不依赖先验知识的情况下抑制非高斯相关噪声。经现场实验证明,该方法可以准确地对管道异常事件进行定位,对噪声具有很好的抑制作用,改善了直接互相关时延估计的性能。相对于直接互相关时延估计方法,相对定位误差由2.7%降低到0.6%,定位一致性提高了三倍,平均定位精度可达14m。     

运动背景中结合特征位移矢量场模糊分割与 OTSU法的运动检测

运动背景中的运动检测难度较大,背景运动补偿后差分以及分割光流场可实现动目标和背景的分离,差分前需进行鲁棒的背景估计,且差分后易出现空洞,而光流估计在噪声以及目标运动速度较大时并不准确,尤其在光照变化时,两种方法均易失效。本文提出一种特征点位移矢量场模糊分割与图像自适应阈值化相结合的运动检测方法,实现在无任何关于运动目标或者运动背景先验信息条件下的动目标检测。通过改进的 SIFT匹配方法生成鲁棒的特征位移矢量场,采用模糊 C均值聚类算法对 SIFT位移矢量场进行无监督分类,实现动目标与背景特征的自适应分离。 OTSU法和形态学操作实现图像的自适应分割,用以修正特征点凸包,最终分割出动目标区域。与鲁棒的背景运动补偿后差分以及光流估计的对比实验表明,在目标运动速度较大、光照变化以及噪声情况下,本文方法均能够检测出运动目标,且在光照变化下的优势明显。     

相关噪声背景下加权高阶累积量的时延估计方法

时延估计是双基阵被动定位中的重要问题。在非相关噪声干扰下,应用广义互相关法进行时延估计可以取得良好的估计效果,但在相关噪声干扰情况下其估计性能严重下降。使用高阶累积量进行时延估计,可以有效地去除相关高斯噪声的干扰。采用类似广义互相关加权的方法对高阶累积量进行PHAT加权,进一步抑制噪声的影响,提高了高阶累积量法的估计性能。结果表明,在相关噪声背景下加权高阶累积量时延估计效果优于广义互相关法和高阶累积量法。     

Application of linear minimum mean-squared-error equalization for volume holographic data storage

When target densities of volume holographic data storage systems are increased, the systems experience increased interference from adjacent pixels and noise. Here we present a method for designing and applying linear minimum mean-squared-error (LMMSE) equalization to improve the bit error rates (BER's) and hence the storage densities achievable. Numerical results with five defocused data pages indicate that a significant improvement in the BER is possible with LMMSE equalization.     

Information theoretic limits to the capacity of volume holographic optical memory

We derive the information theoretic limit to storage capacity in volume holographic optical memories for the limiting cases of dominant intensity noise (Gaussian noise) and dominant field noise (Rician noise). These capacity bounds are compared with the performance achievable using simple Reed-Solomon error-correcting codes.     

基于超拉普拉斯先验与核谱特性噪声图像盲去模糊

现有大部分盲图像去模糊方法对噪声敏感,即使少量的噪声可大大降低恢复图像的质量．考虑到模糊图像中同时隐含有清晰图像信息和模糊核信息,我们同时利用卷积核谱特性先验和清晰图像梯度域超拉普拉斯先验联合建立含噪图像盲去模糊模型,较单独使用卷积核先验与清晰图像先验建模更合理,也能获得更精确的估计图像．本文借助于Hessian矩阵,利用模糊图像及卷积核联合生成先验子,而非单独的估计图像先验子,建立优化模型．求解模型时,通过迭代策略交替细化模糊核和清晰图像．在清晰图像恢复阶段,因存在超拉普拉斯先验项,提出用变量分离法计算清晰图像．清晰图像采用快速傅里叶变换及封闭阈值公式求解,以提高优化速度．实验结果表明：与其他方法相比,本文方法能获得更鲁棒的模糊核和更精确的清晰图像,且收敛速度更快．