基于压缩感知的整体叶盘多模态振动叶尖定时信号重构方法

叶尖定时测量技术是近年来发展的一种非接触式旋转叶片振动监测方法,具有非入侵性的优点,但是该系统测得的振动信号通常是欠采样的。为了能够重构叶尖定时欠采样信号,本文根据压缩感知理论以及叶尖定时采样原理引入了叶尖同步振动信号稀疏模型以及叶尖振动信号重构方法。对整体叶盘有限元模型进行瞬态分析得到叶尖振动信号,使用优化的正交匹配追踪算法以及基追踪对欠采样信号进行重构并和传统方法进行对比。计算结果表明：在信噪比为30dB的噪声环境下,限制频域的正交匹配追踪算法(OMP-RFD)可以准确地识别出叶尖振动信号的主要频率成分。最后使用试验所获得的叶尖振动信号进行重构,验证了OMP-RFD算法有效性。综上可知：压缩感知方法可以很好地应用于叶尖定时测量装置中,能够使用较少传感器识别叶尖同步振动欠采样信号参数,有效提高噪声环境下识别高阶频率的成功率以及准确度。     

欠采样在航空发动机涡轮叶片频率测量中的应用

突破了奈奎斯特采样定理的要求(采样率必须大于输入信号频率2倍的限制),将欠采样法应用于航空发动机构件的高频测量。通过叶片固有特性分析和在叶片上粘贴加速传感器两种方法,对欠采样法进行了验证;并在此基础上采用非接触激光位移传感器,实现了欠采样条件下频率较高的某型发动机涡轮叶片频率的准确测量。结果表明,欠采样方法应用于试件的固有频率测量切实可行,且在航空发动机构件的高频测量中有较大应用价值。     

欠采样信号多采样频率处理方法

讨论了带通信号 A/D 转换中的欠采样问题,通过引入余数定理,给出了一种使用多采样频率的欠采样解决方案。以模数转换为例阐述欠采样问题的解决思路,给出了一些结论。     

LFM宽带雷达信号的盲压缩感知模型

在欠采样测量基础上,提出了一种基于盲压缩感知(BCS)的线性调频(LFM)宽带雷达信号欠采样与重构新框架。这一机制利用LFM雷达信号在分数阶傅里叶变换(FRFT)域上良好的能量聚集特性,将LFM及其延迟信号看做是未知p阶次FRFT域上的稀疏线性组合。首先通过时延相关解线调欠采样得到最佳稀疏FRFT域,再以此构造出原信号对应的p阶次离散FRFT(DFRFT)稀疏基字典,最后结合离散FRFT系数的块稀疏性利用块重构算法从测量值中估计出稀疏系数,同时论证了LFM信号单通道BCS问题解的唯一性,从而实现了稀疏基未知情况下针对LFM宽带雷达信号的盲压缩感知,为非合作条件下LFM信号欠采样采集与无源探测提供了一种新思路。     

基于压缩感知的频率和DOA联合估计算法

波达方向（DOA）估计是阵列信号处理的一个重要问题,针对信号的DOA估计问题,本文基于压缩感知理论,提出了一种新的频率和角度联合估计算法。首先利用方向波数的空间稀疏性,建立过完备稀疏字典,然后利用压缩采样阵列结构通过求解最优化问题得到方向波数的高分辨估计,最后利用最优空域滤波实现信号到达角度和频率的配对。相对于传统算法,该算法能够实现多信号DOA的高分辨估计,且经过压缩采样后降低了运算量,仿真验证了该算法的正确性与有效性。     

高信噪比、高分辨宽测绘带成像

针对传统高分辨和宽测绘带以及高信噪比和宽测绘带之间的矛盾,提出一种基于脉内扫描面阵合成孔径雷达(SAR)系统的二维空域联合处理算法实现高信噪比、高分辨宽测绘带成像。文中首先建立脉内扫描面阵SAR系统模型,该系统采用低脉冲重复频率(PRF)获得宽测绘带信息,同时利用脉内扫描方式获得高信噪比的回波信号。对于低PRF采样宽多普勒谱(对应方位高分辨)引起的多普勒模糊以及脉内扫描引起的距离模糊,提出一种二维空域联合处理算法解距离和多普勒模糊,并且详细地分析了地形高度变化对解模糊算法的影响。最后,通过仿真实验验证了本文算法的有效性。     

惯导系统动态校准数据估计算法

惯导系统的动态校准是在不同频率的正弦角振动信号的激励下,通过与标准测试台的幅频和相频特性进行对比来实现的。当惯导系统输出的角速度量值是有限长的数字序列时,要得到它的幅频和相频特性,就需要对数字序列进行估计。本文介绍了两种估计算法——直接法和四参数估计法,适用于均匀采样和非均匀采样两种情况,并且通过仿真实验给出了算法选择的建议。     

一种主字母体制安控指令检测采样优化方法

针对工程实现中主字母体制安控系统的指令实时检测性能受采样方案影响较大的问题,通过对单音信号频率、检测采样频率和采样点数的合理选择,提出了一种指令检测的采样优化实现方案。仿真实验结果表明,通过对采样方案的优化,在固定多普勒频偏和可变多普勒频偏情况下,可以最低采样点数实现指令可靠检测,便于利用FPGA实现实时处理。     

运动单阵元被动合成阵列波达方向估计

 提出了一种运动单阵元被动合成阵列波达方向(DOA)估计算法。该算法基于被动合成阵列(PSA)的概念,结合空间谱估计的思想构建了运动单阵元被动合成阵列模型,通过多次不同速度合成阵列过程实现对信号DOA的无模糊估计。通过对单次匀速合成阵列过程进行分析得到,在假设信号频率已知条件下,合成阵列算法能够达到与同孔径实阵列多重信号分类（MUSIC）算法相当的DOA估计性能。仿真验证了被动合成阵列与同孔径实阵列的渐近等效性及算法的有效性。     

一种跟踪电网频率的新方法

基于正交变换,提出了一种新的电网频率跟踪方法.针对两种模型进行仿真,表明该方法能够较为精确与快速地跟踪电网频率,尤其针对突变频率的信号,具有较好的跟踪效果;同时算法克服了同步采样条件的限制,通过迭代,在不同初始频率下均具有较好的收敛性.     

利用重要性采样的时差-频差联合估计算法

针对无源定位中参考信号真实值未知的时差(TDOA)-频差(FDOA)联合估计问题,构建了一种新的时差-频差最大似然(ML)估计模型,并采用重要性采样(IS)方法求解似然函数极大值,得到时差-频差联合估计。算法通过生成时差-频差样本,并统计样本加权均值得到估计值,克服了传统互模糊函数(CAF)算法只能得到时域和频域采样间隔整数倍估计值的问题,且不存在期望最大化(EM)等迭代算法的初值依赖和收敛问题。推导了时差-频差联合估计的克拉美罗下界(CRLB),并通过仿真实验表明,算法的计算复杂度适中,估计精度优于CAF算法和EM算法,在不同信噪比条件下估计误差接近CRLB。     

适用于BOC(m,n)信号的无模糊捕获技术

针对二进制偏移载波(BOC)调制信号自相关多峰特性引起的信号捕获模糊性问题,提出了一种子相关相乘边峰消除技术(CMSCT)。根据BOC子相关函数的特性,通过将不同子相关函数相乘获得边峰消除能力,并且为了充分利用接收信号,进一步提高捕获性能,提出了相应的优化算法。分析对比了提出算法的实现复杂度和基于恒虚警率准则的峰值发现概率,对Galileo E1C中频采样信号的处理结果表明:提出的边峰消除方法有效解决了捕获模糊性问题。     

A Logarithmic Frequency Allocation Algorithm for Wideband Discrete Frequency Pulse Trains

It is shown that signal waveforms utilizing discrete frequency modulation (DFM) which are generated using a narrowband or frequency shift algorithm have ambiguity sidelobe distortion which is caused by the approximation of time compression by frequency shift. A logarithmic frequency allocation algorithm is presented which couches the signal design problem in terms of band and step ratios, rather than in terms of bandwidth and frequency steps, and is consistent with the wideband formulation of the ambiguity function. The algorithm makes use of the same basic code generating sequence used for narrowband frequency allocation, but the resulting signal will have invariant ambiguity sidelobe positions for any receiver realization in the delay-time compression plane.     

Doppler ambiguity resolution using multiple PRF

An algorithm for velocity ambiguity resolution in coherent pulsed Doppler radar using multiple pulse repetition frequencies (PRF) is presented. It relies on the choice of particular values for the PRFs. The folded frequency of the target signal is obtained by averaging the folded frequency estimates for each PRF, and a quasi maximum likelihood criterion is maximized for ambiguity order estimation. The fast implementation of this nonambiguous estimation procedure is based on the fast Fourier transform (FFT), The proposed waveform allows full exploitation of any (even) number of PRFs, which appears to be important for estimation improvement. The effects of the waveform parameters and the folded frequency estimation variance on the performance of the ambiguity order estimation procedure are evaluated theoretically and through computer simulations. Mean square error (MSE) curves are given to assess the Doppler frequency estimation accuracy. Finally, the new method is compared with a classical technique and the implementation of the algorithm in a clutter environment is addressed.     

GPS多径信号的自适应滤波估计方法

 研究全球定位系统(GPS)多径信号估计的问题。通过分析自适应滤波器的原理,建立了数字中频信号处理的数学模型,提出一种用自适应滤波实现GPS多径幅度、码相位和载波相位估计的方法。该方法采用不同延迟的伪随机序列对信号进行解扩、解调和累加,得到了作为期望信号的系列自适应滤波相关值。对该方法与其他3种方法进行了理论上的分析比较,得出本方法具有信噪比高、自适应滤波性能好、带有码相位信息和不存在载波模糊度问题等优点。根据各种滤波器算法的特点和本应用的需求,给出了选用递归最小二乘算法实现的方法。通过计算机仿真,验证了提出的方法能够在14 dB的信噪比下,以1个采样间隔的时间延迟分辨率和0.005周的载波相位估计精度估计出GPS L1的多径信号。     

Self-Clutter Cancellation and Ambiguity Properties of Subcomplementary Sequences

In radar signal design it is well known that a fixed volume under the ambiguity surface representing signal energy can only be shifted but not eliminated in the delay-Doppler plane because of the constraint imposed by Woodward's total volume invariance. Rihaczek has shown that periodic signal repetition, though appealing to increased energy, increases the time-bandwidth product at the expense of introducing pronounced ambiguities in the delay-Doppler plane, and thus self-clutter is generated when signals are repeated in the time domain to increase energy. The undesirable self-clutter has a masking effect on targets in different resolution cells thereby limiting performance. An analysis is presented to show that a class of waveforms described in an earlier paper as the subcomplementary set of sequences which are basically repetitive and Hadamard coded, exhibit the property of cancelling self-clutter completely in the delay-Doppler plane if their ambiguity functions are combined. By this technique it is possible to repeat contiguously a basic waveform N times in a prescribed manner to increase signal energy and to cancel totally the resulting self-clutter by combining the ambiguity functions of N different repetitive waveforms which are Hadamard coded. A convenient matrix method to combine the ambiguity functions of subcomplementary sequences, which is an extension of known methods to derive the ambiguity function of repetitive waveforms, is presented. Radar implementation considerations and comparison of performance with various forms of linear frequency modulation (FM) are also discussed.     

脉冲超宽带信号测量性能分析

超宽带技术是一项新兴的无线通信技术,具有极其广阔的发展前景,但目前仅用于室内短距离通信,少见用于航天测控系统。为了将超宽带技术应用于测控系统中,以模糊函数为工具,对脉冲超宽带信号的测量性能进行分析。首先推导矩形脉冲串信号和载波调制矩形脉冲串信号的模糊函数,并对其模糊特性进行仿真分析。在此基础上,主要针对用于测控系统的伪码调制脉冲超宽带信号,利用其模糊函数分析其测距测速性能。结果表明:该超宽带信号具有良好的测距测速性能,其最大无模糊距离为1个伪码周期,最大无模糊多普勒频率为脉冲重复频率的倒数;单脉冲宽度越窄,其测距性能越好而测速性能越差。     

Design of Zigzag FM Signals

Since no practical method is available for synthesizing radar waveforms, a sizable effort has been directed into studies of the matched-filter response, or ambiguity function, of many waveforms. In this paper, we investigate the class of FM signals whose instantaneous frequency varies in a zigzag pattern. The waveforms thus consist of linear FM segments and are relatively easy to generate and process. The paper discusses the relation between the characteristics of the waveform and the features of the associated ambiguity function. The effects studied include those of signal repetition, changes in the FM slope, phase-shift and frequency-shift coding, and staggering of frequency step and segment duration. Ambiguity functions of interesting waveforms illustrate the general results. These ambiguity functions are computer-plotted projections of the three-dimensional surface above the delay-Doppler plane.     

基于小波分析的转子故障信号自适应降噪技术研究

在转子故障信号的小波降噪研究中,降噪效果常常依赖小波分解层数、故障转子转速和信号的采样频率,难于自动完成.针对该问题,提出了一种转子故障信号的自适应小波降噪新方法,该方法先对原始数据进行重采样,然后将重采样信号用小波变换分解到规定的层数,最后运用Donoho软阈值法实现降噪.该方法无需人为选取小波分解层数,降噪过程自动完成.大量的仿真和实验算例验证了方法的正确有效性.      

Optimum Signals for Radar

The research reported herein deals with the general problem of the selection of radar waveforms. The investigation is specifically concerned with the synthesis of radar signals which are optimum in the sense that they are characterized by ambiguity surfaces minimized over certain predetermined regions of the ambiguity plane. The weighted ambiguity surface is utilized as the weighted error criterion. This error criterion is mathematically tractable and pertinent to radar system performance but is not unduly restrictive as some orientation parameters are left unspecified for subsequent cost or penalty function analysis. The signal optimization is approached by variational techniques augmented by equality and inequality constraints, for example, limiting the amount of bandwidth or frequency modulation to be less than some system requirement. Several examples are presented demonstrating the optimization techniques and providing a minimum error for the stated problem. It is shown that for any given type of amplitude modulation of the radar signal, the variance or dispersion of the ambiguity surface is not decreased for any type of phase modulation added. The optimum signal for an elliptical weighting function is derived for several cases. The minimum error is shown to depend upon the constraints and the unspecified orientation parameters and, for one case, on the second moment of the signal.