Blind carrier frequency estimation for phase shift keying signals in low signal to noise ratio

In order to solve the problem of carrier frequency blind estimation of PSK signals in electronic reconnaissance, a new estimation method was proposed. The phase shift keying（PSK） signal was divided into several overlapping intervals which had equal length, and the spectrum concentration measures of every interval were extracted by the FFT. And then, using the grid-density clustering, the spectrum concentration measures were classified into two categories, the narrowband spectrum interval and the wideband spectrum interval. The narrowband spectrum interval was regarded as the characteristic class. The spectrums of the characteristic class were accumulated to estimate the carrier frequency of PSK signal. The proposed method had avoided the non linear operation in the traditional PSK signal carrier frequency estimation algorithm. Thus, the signal to noise ratio （SNR） threshold was remarkably decreased. Moreover, the proposed method did not need the prior knowledge of the signal, which was suitable to the electronic reconnaissance occasion. Experimental results had verified the validity of the proposed estimation method in low SNR.

Blind parameter estimation of pseudo-random binary code-linear frequency modulation signal based on Duffing oscillator at low SNR

Conventional parameter estimation methods for pseudo-random binary code-linear frequency modulation(PRBC-LFM)signals require prior knowledge,are computationally complex,and exhibit poor performance at low signal-to-noise ratios(SNRs).To overcome these problems,a blind parameter estimation method based on a Duffing oscillator array is proposed.A new relationship formula among the state of the Duffing oscillator,the pseudo-random sequence of the PRBC-LFM signal,and the frequency difference between the PRBC-LFM signal and the periodic driving force signal of the Duffing oscillator is derived,providing the theoretical basis for blind parameter estimation.Methods based on amplitude method,short-time Fourier transform method,and power spectrum entropy method are used to binarize the output of the Duffing oscillator array,and their performance is compared.The pseudo-random sequence is estimated using Duffing oscillator array synchronization,and the carrier frequency parameters are obtained by the relational expressions and characteristics of the difference frequency.Simulation results show that this blind estimation method overcomes limitations in prior knowledge and maintains good parameter estimation performance up to an SNR of-35 dB.

An innovative detection method of high frequency BPSK signal with low signal-to-noise ratio

Based on chaotic oscillator system, this paper proposes a novel method on high frequency low signal-to-noise ratio BPSK(Binary Phase Shift Keying) signal detection. Chaotic oscillator system is a typical non-linear system which is sensitive to periodic signals and immune to noise at the same time. Those properties make it possible to detect low signal-to-noise ratio signals. The BPSK signal is a common signal type which is widely used in modern communication. Starting from the analysis of advantages of chaotic oscillator system and signal features of the BPSK signal, we put forward a unique method that can detect low signal-to-noise ratio BPSK signals with high frequency. The simulation results show that the novel method can detect low signal-to-noise ratio BPSK signals with frequency in an order of magnitude of 108 Hz, and the input Signal-to-Noise Ratio threshold can be -20 dB.

Research on the Seismic Wave Characteristics of Low Frequency Signals before the Alxa Left Banner MS5.8 Earthquake in Inner Mongolia,China

In order to search for the seismic wave characteristics of low frequency signals in the Alxa Left Banner region,Inner Mongolia,the low frequency signals of seismic wave data are extracted from the earthquakes of MS5. 8 in 2015 and MS5. 0 in 2016 in this area. The results show that:① Before the MS5. 8 earthquake,the seismic stations located near the epicenter in Wuhai,Dongshengmiao,and Shizuishan recorded seismic waves that showed the phenomenon of spectrum shift from high to low frequency.② The low frequency signals recorded by different stations have obvious difference.③ According to the data recorded by the station closest to the epicenter,low-frequency signals were recorded about120 hours before the earthquake and had obvious anomalies. This may reflect slow slip before the earthquake.

Study on System of Low Frequency Signal′s Measurement and Extraction of its Characteristic Quantity

The essay mainly studies a system of low frequency signal′s measurement and the extraction of its characteristic quantity,introduces how matlab analyzes and extracts low frequency signal.MATLAB,a visual programming software,designs testing program for mechanic vibration signal,analyzes and identifies vibration signal.The collected data shows the effectiveness of the system.Based on XM121 modules,the testing system collects and analyzes single channel signal.

Combining Radon-ambiguity transform with second-order difference to improve detection probability of LFM signals in low SNR

The Radon-ambiguity transform （RAT）, although efficient for detecting the linear frequency modulated signals （LFMs）, is troubled by the energy accumulation of noise in low signal-to-noise ratio （SNR）. A secondorder difference （SOD） method is proposed to treat with this problem. In the SOD method, the optimal search step and difference step are derived from the LFM rate resolution formula. The sharpness of the peaks of RAT is measured by curvature, and the sharpness, but not the magnitude of the peaks, is used to detect the LFMs. The SOD method removes the noise energy accumulation and reserves the drastically changing components integrally; thus, it improves the detection probability of LFMs in low SNR. The expected performance of the new method is verified by 100 Monte Carlo simulations.

Target detection for low angle radar based on multi-frequency order-statistics

For radar targets flying at low altitude, multiple pathways produce fade or enhancement relative to the level that would be expected in a free-space environment. In this paper, a new detec- tion method based on a wide-ranging multi-frequency radar for low angle targets is proposed. Sequential transmitting multiple pulses with different frequencies are first applied to decorrelate the cohe- rence of the direct and reflected echoes. After receiving all echoes, the multi-frequency samples are arranged in a sort descending ac- cording to the amplitude. Some high amplitude echoes in the same range cell are accumulated to improve the signal-to-noise ratio and the optimal number of high amplitude echoes is analyzed and given by experiments. Finally, simulation results are presented to verify the effectiveness of the method.

Tracking algorithm of BPSK signal in low bit SNR and high dynamic scenarios

A new tracking algorithm is proposed aiming at the tracking problem in low bit signal-to- noise ratio （i. e. , Eb/N0 ） scenarios, in which the bit clock regenerated by bit synchronization loop decides loop update moment. The double frequency processing and non-coherent accumulation tech- nologies are applied to eliminate the impact of data polarity inversion, and then long time accumula- tion improves the input signal-to-noise ratio of discriminator. The frequency locked loop and phase locked loop constitute a carrier loop in parallel, which can meet the high dynamic demands. The ef- fectiveness of this algorithm has been corroborated by theoretical analysis, simulation and measure- ments, and the new tracking algorithm has been used in an aerospace engineering project successfully.

高速低载频比传感信号下的逆变器有源阻尼自适应控制

逆变器工作在高频运行和控制载波比低的情况下,存在谐振尖峰抑制,提出了高速低载频比传感信号下的逆变器有源阻尼自适应控制技术。在高速低载频比传感信号下,构建逆变器数学模型。输出电流到电容电压与定子电流之间的传递函数,将逆变器的有源阻尼等效成一个控制电压环。调整有源阻尼自适应控制回路的参数,制定逆变器有源阻尼自适应控制策略。实验结果表明:文中技术的稳定裕度由2.46 dB下降至1.18 dB,可以保证逆变器的稳定运行;在不同采样频率下,可以控制逆变器输出与电网电压相同相位和频率的并网电流,其中在采样频率为5.9f时,输出并网电流和电压均表现为正弦状态,波动范围分别为[35 A,58 A]和[185 V,225 V],具有较好的控制效果。

基于超前滞后环节附加前馈阻尼的VSG控制策略

虚拟同步发电机(virtual synchronous generator,VSG)在引入同步机二阶转子运动方程,增大电力系统等效惯量的同时,也引入了同步发电机的振荡特性,有功低频振荡等动态稳定性问题也随之而来。引入调速侧电力系统稳定器(governor power system stabilizer,GPSS)能有效抑制VSG的功率低频振荡,但其在超调量及调节时间方面的控制效果仍有待提高。通过建立VSG的小信号模型从极点配置角度分析其稳定性,揭示基于GPSS的VSG控制策略在功率动态响应上存在较高超调和较长调节时间的原因。基于此,参考GPSS控制思想,提出了一种基于超前滞后环节附加前馈阻尼补偿的虚拟同步发电机控制策略。并从理论上分析验证了所提控制策略在不影响系统稳态特性的前提下,能够提供调整自由度更高的正阻尼,在有效地抑制功率超调的同时提高了系统的调节速度,从而更好地抑制了有功功率的低频振荡。最后通过MATLAB/Simulink进行对比仿真,仿真结果与理论分析结果一致,证明了所提控制策略的正确性和有效性。

电针联合低频经颅超声刺激对创伤性脑损伤大鼠脑电信号的影响

背景:创伤性脑损伤是由头部受到撞击、打击而导致大脑正常功能被破坏的疾病,目前需要寻找有效治疗方式和客观指标,帮助医生判别损伤状况及恢复患者脑功能。目的:探究电针联合低频经颅超声刺激对创伤性脑损伤大鼠脑电信号的影响。方法:将40只6周龄SPF级雄性SD大鼠随机分为假手术组、模型组、电针组、低频经颅超声刺激组和联合组(n=8),后4组采用Feeney自由落体法造模,假手术组只开骨窗而不打击。各干预组均于造模后1 d开始实施干预,电针组进行电针干预,低频经颅超声刺激组进行低频经颅超声刺激干预,联合组进行两者联合干预,共干预7 d。造模后8 h,用改良神经功能缺损评分评定大鼠神经功能缺损情况;干预7 d后观察大鼠Y迷宫自发轮流行为百分比,而后采集脑电信号,利用快速傅里叶变换分解出α、β、θ和δ波段,计算各频段振荡幅值、能量占比百分比以及Lempel-Ziv复杂度、样本熵。结果与结论:①造模后8 h,模型组、电针组、低频经颅超声刺激组和联合组的改良神经功能缺损评分显著高于假手术组(P<0.05);②造模后第7天,模型组的α波、δ波频带振荡幅值、δ波能量占比百分比显著高于假手术组(P<0.05),自发轮流行为百分比、α波、β波能量占比百分比、Lempel-Ziv复杂度、样本熵显著低于假手术组(P<0.05);③与模型组比较,联合组的α波、δ波频带振荡幅值显著下降(P<0.05),电针组、低频经颅超声刺激组、联合组的α波、β波频带能量占比百分比显著升高(P<0.05),δ波能量占比百分比显著下降(P<0.05);④与电针组和低频经颅超声刺激组相比,联合组的δ波能量占比百分比显著降低(P<0.05),自发轮流行为百分比、α波、β波能量占比百分比、Lempel-Zi复杂度、样本熵显著升高(P<0.05);⑤结果显示,创伤性脑损伤大鼠出现脑电信号异常,而电针联合低频经颅超声刺激干预后可以改善大鼠脑电信号的异常情况,提示脑电频域特征和非线性特征可用来评估创伤性脑损伤情况。

一种基于小信号模型分析的水电机组参与电网一次调频方法

由于水电机组自身复杂的动态特性,导致高比例水电在参与电网调频过程中易产生超低频振荡,不利于电网安全稳定运行。为此,提出一种基于小信号建模分析的水电机组参与电网调频方法。首先,为体现更贴近实际工作状态的动态特性,基于小信号分析对水电机组参与电网调频进行模型构建;然后,考虑到小信号模型会反映系统诸如超低频振荡等危害的发生特征,进而突出系统的非线性,进行分数阶PID(FOPID)控制器设计调速系统;在此基础上,利用遗传算法以频率偏差最小为目标进行控制器参数优化,以进一步改善控制效果。仿真分析表明,所建水电机组小信号模型能够准确反映水轮机的动态特性,同时性能优越的FOPID控制器能有效地抑制超低频振荡。

计算电离层VLF波传输特性的时域有限差分算法

在星载甚低频（VLF）通信技术中,研究甚低频信号在电离层中的传输特性具有重要意义。现有的利用时域有限差分（FDTD）算法研究电离层传输特性大多基于高频脉冲信号,且传播模型相对粗略,计算存在一定误差。为此,建立了更为精确的电离层各向异性传播模型,对常规的FDTD算法引入变步长因子,并用该算法对VLF波在电离层中的场强衰减进行了数值计算,研究了昼夜变化及频率对其传输特性的影响。仿真结果与卫星实测数据对比表明：与常规的FDTD算法以及全波分析方法相比,引入变步长因子的FDTD算法精度更高;在VLF频段,降低频率有利于电磁波穿透电离层,且白天的衰减明显大于夜间;VLF波在射入电离层并穿透D层时衰减严重（30-40 d B）,约为F1层中衰减的3倍。

2009年7月22日日食期间VLF信号相位和场强的观测和分析

2009年7月22日日食期间,分别在重庆、桂林和青岛利用阿尔法场强与相位监测仪观测了来自俄罗斯阿尔法导航系统位于Novosibirsk、Krasnodar和Khabarovsk的3个发射台3个频率的甚低频信号,并对实验数据进行了分析。通过建立日食期间的电离层模型,结合实际传播路径地面电磁参数,推测全食区低电离层的等效高度;给出经不同路径传播的VLF(甚低频)信号相位突变与日食发生时刻的关系及原因;分析了日食期间经不同路径传播的VLF信号的场强起伏变化,发现场强变化滞后于相位变化这一现象。

风电机组附加有功控制参数对系统低频振荡的影响

附加有功控制环节使风机参与至同步机的机电振荡模式中,这使得系统功率振荡特性机理更加复杂,不利于附加有功控制环节的参数设计。为了研究风机附加有功控制对系统稳定性的影响,首先建立了考虑锁相环特性的风机与同步机动态作用的小信号模型;然后基于该模型利用阻尼转矩法分析了风机附加有功控制对系统振荡稳定性的影响机理,并提出了综合考虑系统等效惯性时间常数和阻尼比的附加有功控制环节系数设计方法;最后通过“10机39节点系统”的仿真结果量化分析了各系数对系统低频振荡稳定性的影响规律。结果表明,合理设置风电机组附加有功功率控制系数、滤波时间系数和锁相环带宽均能提升系统频率稳定性;理论分析的正确性也得到了验证。

考虑特征向量约束的低频声信号声源定位系统

低频信号在传输过程中,容易受到环境噪声的干扰,导致信号强度降低,从而影响声源定位的精度。为了提升低频声信号声源定位能力,提出一种考虑特征向量约束的低频声信号声源定位系统。通过MEMS声传感器采集低频声信号,对其进行去噪处理,并传输至低频声信号声源定位模块;采用考虑特征向量约束的低频声信号声源定位方法实现对低频声信号声源定位。实验结果表明:所提系统的低频声信号声源定位与实际位置坐标的误差小,说明该系统的定位方法性能优良,定位精度较高,能够提升低频声信号声源定位能力。

基于CNN-Swin Transformer Network的LPI雷达信号识别

针对在低信噪比(SNR)条件下,低截获概率雷达信号调制方式识别准确率低的问题,提出一种基于Transformer和卷积神经网络(CNN)的雷达信号识别方法。首先,引入Swin Transformer模型并在模型前端设计CNN特征提取层构建了CNN+Swin Transformer网络(CSTN),然后利用时频分析获取雷达信号的时频特征,对图像进行预处理后输入CSTN模型进行训练,由网络的底部到顶部不断提取图像更丰富的语义信息,最后通过Softmax分类器对六类不同调制方式信号进行分类识别。仿真实验表明:在SNR为-18 dB时,该方法对六类典型雷达信号的平均识别率达到了94.26%,证明了所提方法的可行性。

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。

模块化多电平铁路功率调节器接入的机车混跑车网耦合系统稳定性分析

基于模块化多电平换流器的铁路功率调节器(modular multilevel converter-railway static power conditioner,MMCRPC)能够有效解决牵引供电系统存在的电能质量问题,但接入MMC-RPC对车网耦合系统低频稳定性的影响尚不明确。针对此问题,首先考虑频率耦合效应,基于多谐波线性化方法建立了CRH3型、CRH5型机车变流器及MMC-RPC的端口序导纳模型,并实现了不同控制策略、不同变流器负荷序导纳模型在单相静止坐标系的统一。其次,分别研究了MMC-RPC接入牵引网前后车网耦合系统的低频振荡现象。接着,根据主导相角裕度和灵敏度指标首次定量评估了MMC-RPC接入机车混跑系统工况下不同控制器参数对系统稳定性的影响,并提出相应调参准则以提升系统稳定性。最后基于Matlab/Simulink仿真和硬件在环半实物实时仿真验证了对系统稳定性分析结果的正确性。

基于GA-MP的低复杂度OTFS检测算法

针对正交时频空(Orthogonal Time Frequency Space,OTFS)通信系统信号检测复杂度高的问题,提出一种改进的高斯近似消息传递(Gaussian Approximate Message Passing,GA-MP)检测算法。依据最大后验概率检测准则,对发送信号及隐变量进行逐符号高斯近似,基于置信传播算法与联合因子图进行消息传递,用边缘后验概率替代GA-MP中的外部信息以减少运算量,结合阻尼因子提升收敛速度,同时引入概率阈值减少后续更新的节点数,从而使运算复杂度得到有效降低。实验结果表明,改进后的GA-MP算法在保证误码率性能的前提下具有更低的复杂度。