线性调频的脉冲压缩雷达视频信号仿真

利用数字方法实现线性调频的脉冲压缩雷达视频目标模拟信号具有诸多优点：信号模拟的精度高，灵活性好，幅度、相位补偿方便，可以模拟复杂情况，系统结构简单，可靠性高，可扩展性强。详细介绍了基于FPGA设计线性调频的脉冲压缩雷达视频目标模拟信号的原理、结构、具体实现以及简要的性能分析。结果表明该方案性能良好，具有现实可实现性。     

相干源二维波达方向估计

本文分析了平面阵接收信号的协方差矩阵，发现它可分解为一个广义对称矩阵与一个非广义对称矩阵之和，利用信号协方差矩阵的这一结构特征，重点研究了相干源二维波达方向（DOA）估计．该方法通过构造一个差矩阵，求出其本特征值对应的任一特征向量，利用谱函数估计相干源二维DOA．简要分析了二维DOA估计的分维处理。     

Driver detection and recognition of lineside signals and signs at different approach speeds

A study was carried out using simulation to investigate driver responses to lineside signals and signs at various approach speeds. The objectives of the study were: (1) to find out whether train speed would significantly affect signal/sign reading; (2) to examine at which point certain types of signs or signals could be detected or recognised, and (3) to determine a speed cut-off level above which certain types of signs or signals are no longer recognisable or detectable. Fifty-seven train drivers from 12 Train Operating Companies in the UK participated in the trials. Twenty different types of lineside signs and ten types of signals were tested under six different approach speeds ranging from 100 to 350 km/h (62–218 mph). Driver performance measures were ‘time remaining to the signal/sign’ at the point of detection or recognition, and reading error rate. The results showed a significant influence of train speed on driver responses to lineside signals/signs and demonstrated a non-linear relationship between driver responses to signals/signs and approach speed. This has been used to estimate a maximum approach speed limit within which a specific signal or sign can be correctly detected or recognised. The findings and implications of the study are discussed in the paper.     

非平稳ARMA信号自校正滤波器及其应用

本文处理带白色观测噪声的非平稳ARMA信号估计问题.应用状态空间方法和现代时 间序列分析方法[1],基于ARMA新息模型,提出了非平稳ARMA信号自校正滤波器,推广了 Hagander和Wittenmafk的结果[2],并给出了在雷达跟踪系统和检测数据数字滤波方面的应 用.仿真结果说明了本文结果的实用性和有效性.     

Measurement accuracy enhancements for wideband modulated signals

Time‐domain waveform measurements of wideband modulated signals, although attractive for communication systems modeling applications, have until now lacked the required accuracy for quantitative analysis. New developments described here enhance the accuracy of these measurements, enabling their application to communication system characterization and modeling. © 2003 Wiley Periodicals, Inc. Int J RF and Microwave CAE 13: 32–39, 2003.     

脉冲噪声环境下宽带循环平稳信号DOA估计算法

针对传统二阶循环相关算法在脉冲噪声环境中的显著退化问题,本文以α稳定分布为噪声模型,提出基于分数低阶循环相关的波达方向(Direction of arrival,DOA)估计算法。利用分数低阶循环相关的相移特性,将宽带循环平稳信号的DOA估计问题转化为"中心频率"为ε的窄带问题,解决了宽带情况下DOA估计困难的问题。计算机仿真结果进一步验证了此算法的有效性,且性能优于传统SC-SSF(Spectral correlation signal subspacefitting)算法。     

基于Shannon熵的飞机交流发电机振动分析

飞机交流发电机是飞机关键部件之一,监测其健康状况具有重要意义。通过设计实验数据获取平台采集交流发电机在转速上升(从6000转/分到8500转/分)、平稳运行(7500转/分)及转速下降(8500转/分到6000转/分)三个阶段的振动信号,利用符号序列Shannon熵的计算方法以及符号化方法设定合适参数对振动信号进行了处理,得出了交流发电机在三个阶段的振动信号的Shannon熵;通过初步的分析表明,交流发电机在正常状态下三个阶段的Shannon熵都比较有规律的在一定范围内变化,一旦发生振动异常将会引起Shannon熵突变;经过分析讨论,Shannon熵的突变与否是可以用来反映交流发电机在机械方面是否存在故障隐患的。     

Auditory signals in military aircraft: ergonomics principles versus practice

The complete ensembles of auditory signals in selected USAF aircraft (the F-4D, F-15, two models of the F-16, the C-5, and the C-141) are described and evaluated. Human factors research related to the design of speech and non-speech auditory signals is reviewed. Major findings are: that auditory signals are not well standardised among the aircraft, even between those with similar combat roles; that a relatively large number of non-speech auditory signals are used, which may make it difficult for the aircrew to recall the meanings of all the signals; that some non-speech signals are sufficiently similar that they may be confused, particularly in high workload and stressful conditions; and that the criticality of the warnings is not reliably indicated by any characteristic of the signals. Four problem areas requiring further research are discussed: reduction of signal loudness, enhancement of the distinctiveness and masking resistance of non-speech signals, effects of concurrent warning signals on aircrew performance, and additional uses of auditory information.     

基于多学习单元卷积神经网络的雷达辐射源信号识别

现有基于人工提取特征的复杂体制雷达辐射源信号识别方法时效性低,识别准确率不佳. 为此,提出了一种基于多学习单元卷积神经网络的识别方法. 首先对辐射源信号的模糊函数进行高斯平滑,以校正噪声带来的毛刺与畸变;然后提取其正交切片作为进一步的特征提取对象;最后构建多学习单元卷积神经网络,学习和提取正交切片深层、泛在的特征,并通过softmax分类器进行分类识别. 仿真实验结果表明,所提方法在信噪比为-2 dB时对6类典型雷达信号的整体平均识别率均保持在99.86%以上,即便是在-6 dB环境中,雷达信号的识别率也可达到88.50%,在极低信噪比条件下具有良好的性能和可行性.     

基于功率谱估计的造纸生产线断纸预测

建立打浆度、定量、水分等信号随机分量的自回归(AR)模型,并采用Levinson-Durbin递推算法对AR模型参数进行在线估计,由AR模型参数得到信号的功率谱估计,并根据功率谱的变化预测断纸过程的发生.将这种方法应用于生产,实践表明预报效果显著.