Machine Learning for Signal Demodulation in Underwater Wireless Optical Communications

The underwater wireless optical communication(UWOC)system has gradually become essential to underwater wireless communication technology.Unlike other existing works on UWOC systems,this paper evaluates the proposed machine learningbased signal demodulation methods through the selfbuilt experimental platform.Based on such a platform,we first construct a real signal dataset with ten modulation methods.Then,we propose a deep belief network(DBN)-based demodulator for feature extraction and multi-class feature classification.We also design an adaptive boosting(Ada Boost)demodulator as an alternative scheme without feature filtering for multiple modulated signals.Finally,it is demonstrated by extensive experimental results that the Ada Boost demodulator significantly outperforms the other algorithms.It also reveals that the demodulator accuracy decreases as the modulation order increases for a fixed received optical power.A higher-order modulation may achieve a higher effective transmission rate when the signal-to-noise ratio(SNR)is higher.

A new method of demodulating the digital frequency modulation signals

A new method of estimating the frequency-known signals from the strong background noise was presented first. Then the new method was used in the demodulation of the digital frequency modulation (FSK) signals. The new demodulation method can complete the demodulation of the FSK signals only with the carrier frequency and without any carrier phase information. The simulation results show that the performance of anti-noise of the new method is better than that of the incoherent demodulation method and the fluctuation of the carrier phase has little effect on the new method. So the new demodulation method has a fine prospect in the practical applications.

Performance Comparison of Three Algorithms Applied to UM2000 Signal Demodulation

UM2000 signal is a type of multi-audio frequency-modulated signal which is widely used for railway blocking. Principles of three typical demodulating algorithms are presented in details in this paper. Bit error rates of the three methods at different SNRs are achieved by Monte Carlo simulation experiments. Among the three algorithms, the quadrature demodulation has the best performance at the real working environment. However, the three methods have the same problem of phase hopping when noise is too strong.

Parameterized time-frequency analysis to separate multi-radar signals

Multi-radar signal separation is a critical process in modern reconnaissance systems. However, the complicated battlefield is typically confronted with increasing electronic equipment and complex radar waveforms. The intercepted signal is difficult to separate with conventional parameters because of severe overlapping in both time and frequency domains. On the contrary, time-frequency analysis maps the 1D signal into a 2D time-frequency plane, which provides a better insight into the signal than traditional methods. Particularly, the parameterized time-frequency analysis (PTFA) shows great potential in processing such non stationary signals. Five procedures for the PTFA are proposed to separate the overlapped multi-radar signal, including initiation, instantaneous frequency estimation with PTFA, signal demodulation, signal separation with adaptive filter and signal recovery. The proposed method is verified with both simulated and real signals, which shows good performance in the application on multi-radar signal separation.

A novel demodulation method for transmission using nitrogen–vacancy-based solid-state quantum sensor

Diamond based quantum sensing is a fast-emerging field with both scientific and technological significance.The nitrogen–vacancy(NV)center,a crystal defect in diamond,has become a unique object for microwave sensing applications due to its excellent stability,long spin coherence time,and optical properties at ambient condition.In this work,we use diamond NV center as atomic receiver to demodulate on–off keying(OOK)signal transmitted in broad frequency range(2 GHz–14 GHz in a portable benchtop setup).We proposed a unique algorithm of voltage discrimination and demonstrated audio signal transceiving with fidelity above 99%.This diamond receiver is attached to the end of a tapered fiber,having all optic nature,which will find important applications in data transmission tasks under extreme conditions such as strong electromagnetic interference,high temperatures,and high corrosion.

基于Labview的分布式光纤光栅信号解调技术研究

分布式光纤光栅信号解调中受到通信信道的码间干扰导致信道均衡性不好,提出基于Labview的分布式光纤光栅信号解调技术。采用连续时间采样技术构建分布式光纤光栅信号采集模型,对信号输出的功率谱密度特征进行相位调制处理,在离散的维纳模型下提取分布式光纤光栅信号的偏移中心频率和单边带功率谱密度特征信息,通过Labview的调制解调技术实现对信号的调制解调处理,最后采用抗相位噪声干扰的星座图分析方法分析光纤光栅信号解调的抗干扰性和误码抑制能力。仿真结果得知,该方法进行分布式光纤光栅信号解调的抗干扰性较好,提高了信道的频谱带宽,降低了频率中心偏移,传输误码率低于0.05%,信号的传输延时维持在30μs左右,具有较强的应用性。

高速精确的光纤光栅信号解调方案设计

为提升光纤光栅的应用效果,为此,设计高速精确的光纤光栅信号解调方案。依据LPFG的光纤光栅信号解调原理,设计两个LPFG双边缘滤波器处理两路反射光,并且利用光电探测器探测光功率结果,以此解调光栅的中心波长;采用光纤干涉仪检测解调频率,对其进行正反扫描,依据光传播时延引起的解调误差和解调频率扫描方向之间的关联,完成解调结果补偿。测试结果显示:该方案具有较好可行性,光谱发生不同程度重叠时,光纤光栅信号的解调结果标准差均小于1.85 pm;光栅波长的解调误差均在-5~5 pm之间;有效降低解调误差,提升光纤光栅解调精度,可靠获取信号中的信息。

无线传感节点中频域传输信号解调与控制方法

为提高无线传感网络节点中的频域传输信号抗噪能力,优化前端镜像与噪声信号处理能力,以无线传感节点中的频域传输信号为研究对象,提出一种新的信号控制与解调方法。将无线传感信号输入设计的滤波器中,通过电容器、电阻、运算放大器相互协作完成信号滤波。引入前馈补偿通路组建两级节点信号解调线路,当输出传感信号功率超过标准,便可根据超出值,以前馈补偿的方式调节增益带宽积实现解调。在传感节点中外接一个校正电路,以校正电容调节码的方式,控制传感信号频域传输特性满足正常运行标准。仿真结果表明:在1 V的电源电压下,此滤波器中心频率为2 MHz,邻近信号抑制为55 dB,镜像信号抑制为33 dB,带内纹波为0.1 dB,通带电压增益为18 dB,工作电流为382μA。验证了所提方法具有较高的频域传输信号深度处理能力,且有助于实现无线传感网络高质量通信。

光学多普勒差分流速仪数据解调方法验证

光学多普勒差分流速仪在测量海水流速时,由于信号微弱和噪声干扰,接收信号信噪比很低,信号解调面临挑战,可能导致较大的测量误差。为了准确解调埋藏在噪声中的信号并获取速度信息,需要对获取的海试测量数据进行进一步算法处理。采用自适应滤波算法有效降低了多普勒信号中混杂的高频噪声干扰,提高了海试原始数据频域信号的信噪比,并利用寻峰算法更准确地获取了谱峰值。结果表明,与直接读取原始数据的谱峰值相比,经过该算法处理后,激光差分多普勒流速仪与声学多普勒流速仪比测的流速拟合度平均误差为0.2163 cm/s,误差降低了25.5%,表明该算法对激光多普勒测速信号解调是有帮助的。

应答器上行链路信号自适应解调方法的FPGA实现

为降低电磁干扰对信号传输的影响,分析了应答器上行链路信号传输过程及其易遭受干扰信号的特点,设计了基于符号最小均方误差(least mean square,LMS)算法的自适应解调方法。为在硬件平台中实现该解调方法,通过仿真计算,确定LMS算法的自适应算法中间变量变化范围,使用截位操作完成权值系数的更新,设置均衡器长度、步长因子、中值滤波系数分别为1、1/64、16,可在不占用过多硬件资源情况下获得良好的解调性能。解调算法在现场可编程门阵列(field programmable gata array,FPGA)上予以验证,实验表明,当信噪比为6 dB时,FPGA中自适应解调误码率为0.000001,在信噪比大于等于6 dB时,实测误码率与仿真分析误码率基本一致;FPGA自适应解调方法在列车不同速度等级下误码率均小于10^(-6)。

基于振动信号的控制棒驱动机构滚轮早期故障诊断研究

针对现有研究未充分关注控制棒驱动机构(control rod drive mechanism,CRDM)的早期故障诊断问题、很难将故障特征定位至具体部件以及人工引入的故障样本与装备实际故障特征存在差异等不足,提出了一种基于振动信号的CRDM滚轮早期故障诊断方法:首先,利用寿命考核试验时机采集了某密封磁阻马达式CRDM的滚轮全寿命振动信号,基于经验模态分解(empirical mode decomposition,EMD)和Hilbert变换方法进行解调分析,获得与滚轮退化状态相关的模态成分;然后,采用时、频域分析方法获得了11个能够直接表征CRDM滚轮磨损状态的特征量,并根据退化趋势提取出与实际故障特征高度吻合的早期故障样本;最后,分别基于BP神经网络和支持向量机两种方法实现了CRDM滚轮早期故障的多特征智能诊断。结果表明:提取的滚轮早期磨损故障样本与实际运行过程保持了较好的一致性,证明所提CRDM滚轮早期故障诊断方法具有较强的工程应用价值。

一种差动式位移传感器芯片的信号调理电路设计

设计了一种适用于线性可变差动式位移传感器(LVDT)的信号调理电路,该电路用于将LVDT的副边输出信号进行处理,并输出一个表征铁芯位移的直流电压;主要由解调电路、除法电路和运算放大器组成。LVDT副边输出为两个互补的正弦波信号,直接驱动信号调理电路;由于该信号调理电路采用了独特的比值架构,得到的是两个电压的差与和的比值,所以不要求LVDT初级激励使电压幅度保持稳定,同时,LVDT初级与次级线圈的相移以及干扰电压对该电路的功能不会产生影响,能有效地解决传统信号调理电路在测量精度和可靠性等方面的问题,具有更好的稳定性和性能优势,经过仿真验证及流片测试表明,该信号调理电路总误差≤1.49%/FS,线性度≤0.05%,满量程输出电压≥±10 V。各项功能指标均达到设计要求。

基于解调重构的跳频信号辐射源个体识别方法

现有跳频信号辐射源个体识别方法大多围绕跳变瞬态的特征进行讨论,其捕获和精准定位的难度较大。因此,提出了一种基于解调重构的跳频信号辐射源个体识别方法,能够有效利用跳频信号的稳态信息进行辐射源个体识别。首先对跳频信号进行跳变定时,提取出各跳的基带波形;然后解调出各跳的符号,并将其经过理想成型滤波器,得到理想的重构基带波形;最后将原始波形和重构波形一起送入神经网络,得到分类结果。给出发射机畸变模型和畸变参数范围,经过多次测试给出网络参数的建议取值范围,并进行验证实验。实验结果表明,该方法能够有效地完成跳频信号辐射源个体识别任务。

多通道光栅传感解调系统的信号同步分析

多通道光栅传感解调系统的解调精度和信号同步程度存在直接关联,为保证解调效果,研究多通道光栅传感解调系统的信号同步方法。基于多通道光栅传感解调系统的应用原理,确定解调过程中相邻光栅传输时延,导致反射光信号发生重叠,无法保证多通道信号同步;充分分析解调系统信号时延情况后,采用卡尔曼滤波方法,依据频率偏差补偿完成相位偏差补偿,实现多通道同步时间补偿,以此完成多通道光栅传感解调系统的信号同步。测试结果显示:采用研究方法进行多通道光栅传感解调系统信号同步后,时间同步偏差结果均低于0.15 ms;并且信号同步后解调系统的解调误码率均低于0.55%;解调后最大漂移结果为0.007 8 nm;可有效避免反射光信号发生重叠。

面向新型声波激励超低频天线的2FSK通信系统解调算法

针对声波激励超低频天线发射功率较小,低接收信噪比下传统二进制频移键控(2FSK)非相干解调中窄带滤波器设计难等问题,提出了一种基于Duffing混沌振子的2FSK弱信号解调方法。由于Duffing振子本身对相位敏感,首先设计了“粗同步+细同步”的相位同步方法,其中粗同步通过短时傅里叶变换完成,细同步则通过Duffing混沌振子实现;然后,利用混沌振子对同频周期信号敏感、对噪声信号免疫的特性,将信号并行通过2个Duffing振子,二者的内置信号频率与2个载频一致。在某一时刻必定有一个系统处于大尺度周期态,另一个处于混沌态,二者比较判决来实现信号解调。仿真结果表明,文中提出的基于Duffing混沌振子的解调算法比非相干解调和相干解调算法,分别有约5 dB和4 dB的性能提升。

基于磁编码器和窄带解调的太阳轮故障检测

绝对式磁编码器具有价格低、安装方便等优势,适合于工程应用,但在低转速工况下其角度信号受测量误差的影响较大,需要对角度信号进行拟合以消除测量误差带来的干扰。传统的分段拟合方法在分段点处易出现不连续现象,角度信号的不连续导致由其计算的瞬时角速度(instantaneous angular speed,简称IAS)信号中出现虚假冲击,并对基于IAS信号的故障特征提取造成干扰。针对此问题,提出一种基于绝对式磁编码器IAS估计和窄带解调的太阳轮故障检测方法。首先,为保证IAS信号的连续性与平滑性,提出基于最小二乘拟合与5次Hermite插值的方法,实现了对IAS信号的拟合估计和平滑处理;其次,结合窄带解调技术实现了对行星齿轮减速器太阳轮故障特征的有效提取;最后,通过对正常与故障太阳轮的绝对式磁编码器信号分析对比,验证了所提方法的有效性。

基于IAS信号自适应窄带解调的RV减速器摆线轮故障特征提取

RV(rotary vector)减速器广泛应用于工业机器人,研究其关键零部件的故障检测方法具有重要意义。由于RV减速器结构复杂、摆线轮转速低、故障冲击较弱等问题,造成摆线轮故障特征难以用常规振动分析方法提取。针对上述问题,提出一种基于瞬时角速度信号自适应窄带解调的RV减速器摆线轮故障特征提取方法。首先对编码器角度信号进行采集,然后使用向前差分法获得瞬时角速度信号,在此基础上,使用角域同步平均提取摆线轮周期相关同步分量,消除非同步干扰,并通过构建边带信噪比指标选取故障信息丰富的啮合谐波频带进行带通滤波,最后对滤波后的信号进行窄带解调,实现对RV减速器摆线轮的故障特征提取。试验结果表明,该方法可以有效地提取RV减速器摆线轮故障特征,且自适应实现优化带宽选择。

基于神经网络的舰船混沌保密通信系统研究

以提升舰船通信安全性及同步性为出发点,设计基于神经网络的舰船混沌保密通信系统。基于舰船混沌同步保密通信系统一般模型,在系统发射端设计基于径向基函数神经网络(RBFNN)的跟踪器,跟踪舰船信息信号,通过混沌调制模块调制系统的状态量参数,并加密舰船信息信号将其混沌视为载波进行混沌掩盖后,通过信道进行传输,经噪声消除器去除信号噪声后,在混沌解调模块设计基于RBFNN的同步控制器,输出同步解调后的原始舰船信息信号传输至接收端,实现舰船信息保密同步通信。实验结果显示,该系统加密后,信息可有效掩盖信号真实情况,信号去噪后可还原信号本真,解调后可在接收端实现高精度的信号还原;且该系统应用后的信息可有效防止攻击者窃取。

An improved initial rotor position estimation method using high-frequency pulsating voltage injection for PMSM

High frequency pulsating voltage injection method is a good candidate for detecting the initial rotor position of permanent magnet synchronous motor.However,traditional methods require a large number of filters,which leads to the deterioration of system stability and dynamic performance.In order to solve these problems,a new signal demodulation method is proposed in this paper.The proposed new method can directly obtain the amplitude of high-frequency current,thus eliminating the use of filters,improving system stability and dynamic performance and saving the work of adjusting filter parameters.In addition,a new magnetic polarity detection method is proposed,which is robust to current measurement noise.Finally,experiments verify the effectiveness of the method.

基于自适应极值的白光干涉信号解调算法研究

针对传统时域解调算法等光程点定位稳定性差、抗干扰能力弱,而频域解调算法效率低且部分方法受扫描采样步长限制等问题,课题组提出一种基于自适应极值的白光干涉解调算法。从干涉信号统计学规律出发,通过对干涉信号包络曲线加权平均,将它修正为高斯型包络曲线;然后,通过对包络曲线高斯拟合插值得到等光程点,进而得到测量方向的深度信息以及三维形貌;最后,以高度为20μm标准台阶样块为测量对象进行多次实验。结果表明:与传统算法相比,课题组所提出算法的测量重复性和精度均有显著提升。该算法为白光干涉中信号解调提供了一种重复性更好、误差更小的方法。