A TECHNIQUE FOR MEASURING THE LINEARITY OF A LINEARLY FREQUENCY-MODULATED SIGNAL

A technique for measuring the linearity of a linearly frequency-modulated continuous wave (LFM-CW) signal is presented. It uses a delay-line and a mixer to sense the slope of the output of a sweep oscillator, so that the original form of frequency function deviated from idealized linear slope is retrieved by means of spectrum analysis. Consequently,the linearity of the LFM signal is determined. The formulation is performed based on the principle that an angle-modulated signal can be approximated by an amplitude-modulated signal if the modulation coefficient is sufficiently small. To examine the validity of the procedure and to study the effect of each parameter on the accuracy of measurement, a number of computer simulations has been made. The results of simulation show that the error of the measurement is less than 2%.

Parameter estimation method for a linear frequency modulation signal with a Duffing oscillator based on frequency periodicity

In view of the complexity of existing linear frequency modulation(LFM)signal parameter estimation methods and the poor antinoise performance and estimation accuracy under a low signal-to-noise ratio(SNR),a parameter estimation method for LFM signals with a Duffing oscillator based on frequency periodicity is proposed in this paper.This method utilizes the characteristic that the output signal of the Duffing oscillator excited by the LFM signal changes periodically with frequency,and the modulation period of the LFM signal is estimated by autocorrelation processing of the output signal of the Duffing oscillator.On this basis,the corresponding relationship between the reference frequency of the frequencyaligned Duffing oscillator and the frequency range of the LFM signal is analyzed by the periodic power spectrum method,and the frequency information of the LFM signal is determined.Simulation results show that this method can achieve high-accuracy parameter estimation for LFM signals at an SNR of-25 dB.

Early detection of sudden cardiac death by using classical linear techniques and time-frequency methods on electrocardiogram signals

Early detection of sudden cardiac death may be used for surviving the life of cardiac patients. In this paper we have investigated an algorithm to detect and predict sudden cardiac death, by processing of heart rate variability signal through the classical and time-frequency methods. At first, one minute of ECG signals, just before the cardiac death event are extracted and used to compute heart rate variability (HRV) signal. Five features in time domain and four features in frequency domain are extracted from the HRV signal and used as classical linear features. Then the Wigner Ville transform is applied to the HRV signal, and 11 extra features in the time-frequency (TF) domain are obtained. In order to improve the performance of classification, the principal component analysis (PCA) is applied to the obtained features vector. Finally a neural network classifier is applied to the reduced features. The obtained results show that the TF method can classify normal and SCD subjects, more efficiently than the classical methods. A MIT-BIH ECG database was used to evaluate the proposed method. The proposed method was implemented using MLP classifier and had 74.36% and 99.16% correct detection rate (accuracy) for classical features and TF method, respectively. Also, the accuracy of the KNN classifier were 73.87% and 96.04%.

WIDELY LINEAR RLS CONSTANT MODULUS ALGORITHM FOR COMPLEX-VALUED NONCIRCULAR SIGNALS

Based on the constant modulus criterion, a new Widely Linear(WL) blind equalizer and a novel widely linear recursive least square constant modulus algorithm are proposed to improve the blind equalization performance for complex-valued noncircular signals. The new algorithm takes advantage of the WL filtering theory by taking full use of second-order statistical information of the complex-valued noncircular signals. Therefore, the weight vector contains the complete second-order information of the real and imaginary parts to decrease the residual inter-symbol interference effectively. Theoretical analysis and simulation results show that the proposed scheme can significantly improve the equalization performance for complex-valued noncircular signals compared with traditional blind equalization algorithms.

Effect of inertial mass on a linear system driven by dichotomous noise and a periodic signal

A linear system driven by dichotomous noise and a periodic signal is investigated in the underdamped case. The exact expressions of output signal amplitude and signal-to-noise ratio (SNR) of the system are derived. By means of numerical calculation, the results indicate that (i) at some fixed noise intensities, the output signal amplitude with inertial mass exhibits the structure of a single peak and single valley, or even two peaks if the dichotomous noise is asymmetric; (ii) in the case of asymmetric dichotomous noise, the inertial mass can cause non-monotonic behaviour of the output signal amplitude with respect to noise intensity; (iii) the curve of SNR versus inertial mass displays a maximum in the case of asymmetric dichotomous noise, i.e., a resonance-like phenomenon, while it decreases monotonically in the case of symmetric dichotomous noise; (iv) if the noise is symmetric, the inertial mass can induce stochastic resonance in the system.

Parameter estimation of LFM signals based on time reversal

In this paper,parameter estimation of linear frequency modulation(LFM)signals containing additive white Gaussian noise is studied.Because the center frequency estimation of an LFM signal is affected by the error propagation effect,resulting in a higher signal to noise ratio(SNR)threshold,a parameter estimation method for LFM signals based on time reversal is proposed.The proposed method avoids SNR loss in the process of estimating the frequency,thus reducing the SNR threshold.The simulation results show that the threshold is reduced by 5 dB compared with the discrete polynomial transform(DPT)method,and the root-mean-square error(RMSE)of the proposed estimator is close to the Cramer-Rao lower bound(CRLB).

Safety Performance Functions for Traffic Signals:Phasing and Geometry

A significant proportion of urban crashes,especially serious and fatal crashes,occur at traffic signals.Many of the black-spots in both Australia and New Zealand cities occur at high volume and/or high-speed traffic signals.Given this,crash reduction studies often focus on the major signalised intersections.However,there is limited information that links the phasing configuration,degree of saturation and overall cycle time to crashes.While a number of analysis tools are available for assessing the efficiency of intersections,there are very few tools that can assist engineers in assessing the safety effects of intersection upgrades and new intersections.Safety performance functions have been developed to help quantify the safety impact of various traffic signal phasing configurations and level of intersection congestion at low and high-speed traffic signals in New Zealand and Australia.Data from 238 signalised intersection sites in Auckland,Wellington,Christchurch,Hamilton,Dunedin and Melbourne was used to develop crash prediction models for key crash-causing movements at traffic signals.Different variables(road features)effect each crash type.The models indicate that the safety of intersections can be improved by longer cycle times and longer lost inter-green times,especially all-red time,using fully protected right turns and by extending the length of right turn bays.The exception is at intersections with lots of pedestrians where shorter cycle times are preferred as pedestrian crashes increase with longer wait times.A number of factors have a negative impact on safety including,free left turns,more approach lanes,intersection arms operating near or over capacity in peak periods and higher speed limits.

GNSS线极化天线干涉信号反演土壤湿度算法测试

利用全球导航卫星系统干涉信号(GNSS-IR)测量土壤湿度已成为热门的研究课题。搭载低成本线性极化天线的智能手机可以方便快捷采集干涉信号信噪比(SNR)。分别仿真垂直和水平线性极化天线采集的GNSS干涉信号,给出2种极化方式下干涉信号SNR波形和反射率随卫星高度角变化的结果。对于垂直极化分量,电磁波会在入射角65°~85°左右时发生全透射,导致干涉信号振荡效果消失,而水平极化不存在该现象。同时,分别仿真右旋圆极化(RHCP)直射和左旋圆极化(LHCP)反射天线采集的GNSS信号,并计算直反射信号的幅值比。在仿真基础上分别利用不同极化天线进行实验,结果表明:采用线性极化天线采集的GNSS干涉信号振荡效果几乎不受卫星高度角的限制,可以为土壤湿度反演提供更多的有效数据,并且反演得到的土壤湿度与同位数据具有良好的一致性,两者的相关性达到0.95。使用搭载圆极化天线的双通道接收机采集北斗系统卫星数据进行对比,相关性达到0.91。对于不同的设备,智能手机采集的GNSS数据占用空间相对比于双通道接收机降低1%,且反演结果相关性接近,由于干涉信号提取直反射信号需要一定的振荡周期,故反演结果的时间分辨率要低于双通道接收机。

试验环境水下声信号的特征提取方法

水下试验环境参数的反演是水声学研究领域的重要内容。而当前研究的关键是通过对水下声信号做特征提取从而获取参数信息。针对特征提取较难、模型很难拟合等问题。本文提出了一种试验环境水下声信号的特征提取方法。将水下声信号同时用梅尔频谱倒谱系数及线性预测系数处理,两者运用特征加权组合方法得到新的特征矩阵;再应用映射插值算法对特征矩阵进行处理,获得适应神经网络输入的三通道矩阵。本文选取的网络模型为残差神经网络。利用实验室所录制的对河口水库数据集测试表明,本文提出的特征提取方法普遍优于仅利用梅尔频谱倒谱系数或线性预测系数的特征处理方法。利用单频矩形脉冲信号对环境进行深度5分类,准确率平均提升2%。利用线性调频信号对环境进行深度5分类,准确率平均提升2.03%。本文提出的特征提取方法对线性调频信号在深度分类任务下处理的结果要优于单频矩形脉冲信号处理的结果。

面向高速移动环境的二级信号检测算法

正交时间序列复用(OTSM)可以以更低的复杂度实现类似正交时频空间(OTFS)调制的传输性能,为未来需要低复杂度收发器的高速移动性通信系统提供一种有前景的解决方法。针对现有的基于时域的高斯-赛德尔(GS)迭代均衡效率不高的问题,提出二级信号检测算法。首先在时域进行低复杂度线性最小均方误差(LMMSE)检测,其次采用连续超松弛(SOR)迭代算法进一步消除残余符号干扰。为进一步提高收敛效率和检测性能,对SOR算法进行线性优化得到改进SOR(ISOR)算法。仿真实验结果表明,与SOR算法相比,ISOR算法在增加较低复杂度前提下可以提升检测性能并加快算法收敛。与GS迭代算法相比,ISOR算法采用16QAM调制且误码率为10-4时有1.61 dB的增益。

基于线性调频连续波的合作式通信辐射源测距

针对加速运动目标参数估计中,离散多项式变换方法无法进行非整数估计的问题,本文提出基于瑞夫算法的离散多项式变换法和基于Chirp-Z变换的离散多项式变换法2种新型离散多项式变换算法,对加速运动目标速度和加速度进行估计,并对2种算法的估计误差和计算量进行了分析比较。结果表明:2种算法在信噪比-20 dB时均方误差开始接近克拉美罗界。基于瑞夫算法的离散多项式变换法与3次迭代基于Chirp-Z变换的离散多项式变换法均可在较低信噪比下可实现任意频率的有效估计且性能接近,二者均可实现低信噪比下速度、加速度的有效估计,但基于瑞夫算法的离散多项式变换法计算量远小于3次迭代基于Chirp-Z变换的离散多项式变换法。

低成本接收阵列方向图测试系统与方法

采用传统的相控阵测试方法对数字阵列及数字波束合成进行测试,存在系统复杂、设备齐套周期长、问题难解耦等弊端。因此,对于数字阵列及相关算法,需要一种不依赖天线和物理环境,且能够以低成本和高效率,在系统开发中期完成相关性能评估和迭代的方法。给出一种基于阵列信号模拟技术的低成本接收阵列方向图测试系统,并提出了随机虚拟相移技术用于解决测试精度不足的问题。基于简要的理论分析、给出了测试平台构成和测试流程,并通过仿真和实测验证了方法的有效性。

基于内电势幅值/频率和网络有功/无功电流工作点的变换器并网交流系统小扰动线性化方法

当今电力系统不明机理的振荡问题频发,亟需回归振荡的能量交换本质以认识和分析系统动态过程。系统受扰后设备将根据输入和输出有功/无功功率或电流不平衡调节内电势频率和幅值,进而调节网络中各设备端口有功/无功电流及设备输出功率。在此闭环动态过程中内电势幅值/频率对应的设备储能与有功/无功电流对应的网络储能将在一定水平上彼此交换。因此,系统动态分析的工作点和相应的小扰动数学关系应当基于表征系统储能水平的内电势幅值/频率和有功/无功电流来进行确定和构建。然而,现有研究仍然缺乏对交流系统动态过程能量内涵的认识,目前尚未从能量角度开展认识和分析交流系统动态过程的相关工作。鉴于此,该文旨在提出基于内电势幅值/频率和有功/无功电流工作点的交流电力系统小扰动线性化方法。首先以变换器并网交流系统为例,从系统基本结构及其传输有功/无功的闭环运行原理出发,通过阐述在系统受扰后内电势幅值/频率和有功/无功电流不断迭代更新的闭环动态过程中变换器和网络在一定储能水平上相互交换有功/无功的机制,明确内电势幅值/频率和有功/无功电流的稳态直流量是交流系统的工作点,并澄清其所蕴含的有功/无功存储水平物理内涵。基于内电势幅值/频率和有功/无功电流工作点,该文提出描述变换器/网络的内电势幅值/频率和有功/无功电流间的激励-响应小扰动非线性关系及其线性化的物理认识和相应的线性化方法,然后结合仿真说明系统小扰动线性化关系的适用性,最终阐释小扰动初期交、直流电气量的动态演化行为。

高光谱紫外辐照度仪CCD电路系统的设计及测试

为了在地面获得高信噪比的太阳直射紫外光谱辐照度,选用紫外敏感型线阵CCD探测器,研发了高光谱紫外辐照度仪原理样机。设计了CCD电路系统,讨论了电源电路、驱动电路、模拟前端电路以及CCD驱动时序的工作原理与设计方法,并在实验室利用标准灯光源测试了CCD电路系统的非线性和信噪比。结果表明,在340 nm波段下,CCD探测器接收信号约为饱和信号的80%时,系统信噪比超过400。最终,将测试好的CCD电路系统与光机模块装调并进行了波长定标,光谱范围覆盖280~400 nm,实现了对室内光源的紫外高光谱测量,验证了CCD电路系统设计的合理性和可行性。

基于FRFT的低信噪比LFM信号参数快速估计算法

基于分数阶傅里叶变换(Fractional Fourier Transform,FRFT)对线性调频(Linear Frequency Modulated,LFM)信号参数进行估计,问题关键是确定FRFT最佳阶数,根据误差迭代思想提出新的参数估计算法,该算法利用归一化带宽和旋转角的转化关系,由估计误差推算角度差值,有效降低了运算量,不需要调频斜率正负的先验信息,改进的对数搜索算法可以进一步提高参数估计结果的稳定性和可靠性。仿真结果表明,信噪比在-8 dB以上时该方法在高效率的前提下仍具有良好的参数估计性能,平均估计误差在1%以内,估计结果接近Cramer-Rao下限,满足工程实时处理需求。

脉冲噪声下基于CNN-FRFT的线性调频信号参数估计方法

由于脉冲噪声破坏了线性调频(LFM)信号的分数谱特征,使得基于分数谱特征的参数估计方法无法有效估计参数。针对这个问题,提出一种脉冲噪声环境下基于CNN-FRFT的LFM信号参数估计方法。首先,利用α稳定分布拟合随机脉冲噪声,构建加性含噪信号,输入卷积神经网络(CNN)进行训练和测试;其次,利用训练好的CNN模型对信号进行去噪,并验证模型的去噪能力和泛化能力;最后,利用分数阶傅里叶变换(FRFT)建立去噪信号的分数谱,通过峰值点位置来估计LFM信号的参数。实验结果表明,相比于传统的基于非线性函数的方法,该方法在强脉冲噪声环境下具有更好的精度和噪声鲁棒性,CNN的应用使其具有更强的泛化能力,在实测脉冲噪声下仍可以准确估计参数。

潮汐干线交通信号协调控制模型

为缓解城市布局等问题导致的潮汐交通拥堵现象,提出了一种潮汐交通状态下的干线信号协调控制策略.依据交通供需关系及交通量进出平衡,构建了以干线吞吐量最大化为优化目标的混合整数线性规划模型.基于冲击波理论,构建了以过饱和方向车均延误最小化为优化目标的二次规划模型.通过引入松弛变量实现可变带宽绿波的分段优化,构建了以非饱和方向带宽最大化为目标的混合整数线性规划模型.采用三阶段优化方法求解模型,获得潮汐干线的最优控制方案.算例结果表明,本文提出的模型能优化干线吞吐量,控制过饱和方向的延误,并为非饱和方向提供可变带宽绿波,从而满足潮汐交通需求.

广义线性模型在神经电生理信号分析中的应用

大脑在完成思维等功能活动时,脑中的神经细胞会产生表征不同生理状态的电活动,大脑不同功能区也会呈现不同的放电特征,例如,参与学习记忆等认知活动的海马脑区以产生尖波涟漪事件为典型特征。本研究利用多通道电生理技术记录到神经元胞外电信号,通过海马区节律性场电位进行了3种常见生理状态(清醒、快速眼动睡眠和非快速眼动睡眠阶段)的划分,并介绍了利用海马区尖波涟漪事件研究海马区和皮层区的放电特征的方法。最后,利用5折交叉验证的广义线性模型预测神经信号的方法,以特定时间窗内神经元群体放电个数矩阵为自变量,该时间窗或其他时间窗内的单个神经元放电个数向量或尖波涟漪事件是否出现为因变量,进行预测,与解耦不同生理意义下的神经活动结果进行对比。本研究将有助于分析及解码不同生理状态下大脑功能区的神经信号特征,尤其是对研究学习记忆功能及其相关脑区之间的相互作用提供方法学依据。

二极管的线性等效原理探究

二极管伏安特性方程具有一定的局限性,这使得将二极管电路等效为线性电路变得尤为重要。在小信号思想下,利用泰勒级数并忽略高次项误差的方法,以及图解法对二极管在其应用电路中的线性等效原理进行论证,通过计算得出结论,在小信号误差足够小时,二极管可以等效为线性元件。同时,对叠加定理进行了一定说明,证明了此探究过程并没有使用叠加定理。

基于RFSoC的脉冲雷达采集与测量系统设计与实现

探讨射频系统级芯片(RFSoC)在脉冲雷达系统设计中的应用,设计实现一个具有高性能数模混合信号处理能力的雷达测距系统。采用IW-RFSoC-49DR高性能RFSoC开发板(包括背景干扰滤除算法的设计),测试环境设置在空间狭窄、多金属设备干扰的实验室内。实验结果显示,在未经处理的复杂室内环境中,实验数据受到显著干扰;实现背景干扰滤除算法后,频谱图的显示分辨能力得到显著提升。随着测试目标距离由3 m提高至12 m,测距误差值从53 cm降低至5 cm。RFSoC技术在脉冲雷达系统设计中展现出显著优势,实现了高集成度低功耗设计,为后续基于RFSoC设计便携式雷达打下了基础。