High-Precision Doppler Frequency Estimation Based Positioning Using OTFS Modulations by Red and Blue Frequency Shift Discriminator

Orthogonal Time Frequency and Space(OTFS) modulation is expected to provide high-speed and ultra-reliable communications for emerging mobile applications, including low-orbit satellite communications. Using the Doppler frequency for positioning is a promising research direction on communication and navigation integration. To tackle the high Doppler frequency and low signal-to-noise ratio(SNR) in satellite communication, this paper proposes a Red and Blue Frequency Shift Discriminator(RBFSD) based on the pseudo-noise(PN) sequence.The paper derives that the cross-correlation function on the Doppler domain exhibits the characteristic of a Sinc function. Therefore, it applies modulation onto the Delay-Doppler domain using PN sequence and adjusts Doppler frequency estimation by red-shifting or blue-shifting. Simulation results show that the performance of Doppler frequency estimation is close to the Cramér-Rao Lower Bound when the SNR is greater than -15dB. The proposed algorithm is about 1/D times less complex than the existing PN pilot sequence algorithm, where D is the resolution of the fractional Doppler.

Research of Frequency Discriminator on Frequency Lock Loops

Frequency lock loops （FLL） discriminating algorithms for direct-sequence spread-spectrum are discussed. The existing algorithms can＇t solve the problem of data bit reversal during one pre-detection integral period. And when the initial frequency offset is large, the frequency discriminator can＇ t work normally. To solve these problems, a new FLL discriminating algorithm is introduced. The least-squares discriminator is used in this new algorithm. As the least-squares discriminator has a short process unit period, the correspond- ing frequency discriminating range is large. And the data bit reversal just influence one process unit period, so the least-squares discriminated result will not be affected. Compared with traditional frequency discriminator, the least-squares algorithm can effectively solve the problem of data bit reversal and can endure larger initial frequency offset.

Analysis of single frequency modulation for passive hydrogen maser

Based on the theory of the passive hydrogen maser, along with the technology of frequency modulation and modulation transfer spectroscopy, the theoretical expression of the single frequency modulation for the passive hydrogen maser and the function of the cavity and H line error signals separation are derived, which are basically coincident with the experiment. The absorption and dispersion spectrum curves with different resonance widths show that the cavity and hydrogen transition serve as discriminators, and the two error signals can be separated. Through the calculations of the two error signals in the passive hydrogen maser, it analyzes the traditional method of the two error signals separation, and then describes a new improved method for the passive hydrogen servo loops consisting in the use of a single modulation frequency and frequency discrimination. A null interaction of the two error signals for the new selection of the phase setting is deduced theoretically and validated by the simulation. The preliminary experimental result confirms the feasibility of this new approach, which can reduce the influence from the cavity frequency variety on the crystal oscillator and contribute significantly to the long term performance of the passive hydrogen maser.

基于特征融合和B-SVM的鸟鸣声识别算法

为了实现在野外通过低成本嵌入式系统识别鸟类,提出了基于特征融合和B-SVM的鸟鸣声识别方法。对鸟鸣声信号提取梅尔频率倒谱系数、翻转梅尔频率倒谱系数、短时能量和短时过零率组成特征参数,通过线性判别算法对特征参数进行特征融合。利用黑寡妇算法通过测试集对支持向量机模型的核参数和损失值进行优化得到B-SVM模型。利用Xeno-canto鸟鸣声数据集对本文算法进行了测试,结果表明该方法的识别准确率为93.23%。算法维度参数的大小和融合特征维度的高低是影响算法识别效果的重要因素。在相同条件下,文中所提的基于特征融合和B-SVM模型的鸟鸣声识别算法相较于其他特征参数和模型,识别的准确率更高,为野外鸟类识别提供了参考。

基于时频感知双路径Conformer的语音增强

近年来,Conformer在语音领域的应用表现较为突出。该模块通过结合多头自注意力机制和卷积神经网络,能够同时关注短时和长时序列信息,从而在语音处理任务中表现出卓越的性能。在此基础上提出了一种基于时频感知双路径Conformer的语音增强网络(TFDPCNet)。首先,该网络将改进的Conformer结构作为核心,采用双路径结构,构成时频感知的双路径Conformer模块(TFDP-Conformer),增强了整体网络的时频提取能力;同时,为了减小时频特征融合的难度,提出了注意力门控交叉融合模块(AGCF),通过额外的注意力门进一步增强了网络训练过程中时频特征的交互,提高了时频特征的利用率;最后,引用度量鉴别器,并对其进行适当剪枝,使得增强后的音频和原始音频在量化评价指标上保持更高的一致性。实验结果表明,相比于TSTNN算法,TFDPCNet在主观和客观指标上都有明显提高。

Corticostriatal Neurons in the Anterior Auditory Field Regulate Frequency Discrimination Behavior

The anterior auditory field(AAF)is a core region of the auditory cortex and plays a vital role in discrimination tasks.However,the role of the AAF corticostriatal neurons in frequency discrimination remains unclear.Here,we used c-Fos staining,fiber photometry recording,and pharmacogenetic manipulation to investigate the function of the AAF corticostriatal neurons in a frequency discrimination task.c-Fos staining and fiber photometry recording revealed that the activity of AAF pyramidal neurons was significantly elevated during the frequency discrimination task.Pharmacogenetic inhibition of AAF pyramidal neurons significantly impaired frequency discrimination.In addition,histological results revealed that AAF pyramidal neurons send strong projections to the striatum.Moreover,pharmacogenetic suppression of the striatal projections from pyramidal neurons in the AAF significantly disrupted the frequency discrimination.Collectively,our findings show that AAF pyramidal neurons,particularly the AAF–striatum projections,play a crucial role in frequency discrimination behavior.

Anti-noise performance of the pulse coupled neural network applied in discrimination of neutron and gamma-ray

In this study,the anti-noise performance of a pulse-coupled neural network(PCNN)was investigated in the neutron and gamma-ray(n-γ)discrimination field.The experiments were conducted in two groups.In the first group,radiation pulse signals were pre-processed using a Fourier filter to reduce the original noise in the signals,whereas in the second group,the original noise was left untouched to simulate an extremely high-noise scenario.For each part,artificial Gaussian noise with different intensity levels was added to the signals prior to the discrimination process.In the aforementioned conditions,the performance of the PCNN was evaluated and compared with five other commonly used methods of n-γdiscrimination:(1)zero crossing,(2)charge comparison,(3)vector projection,(4)falling edge percentage slope,and(5)frequency gradient analysis.The experimental results showed that the PCNN method significantly outperforms other methods with outstanding FoM-value at all noise levels.Furthermore,the fluctuations in FoM-value of PCNN were significantly better than those obtained via other methods at most noise levels and only slightly worse than those obtained via the charge comparison and zerocrossing methods under extreme noise conditions.Additionally,the changing patterns and fluctuations of the FoMvalue were evaluated under different noise conditions.Hence,based on the results,the parameter selection strategy of the PCNN was presented.In conclusion,the PCNN method is suitable for use in high-noise application scenarios for n-γdiscrimination because of its stability and remarkable discrimination performance.It does not rely on strict parameter settings and can realize satisfactory performance over a wide parameter range.

Comparison of ISFs and LSFs in Speech/Music Discrimination System

The immittance spectral frequencies （ISFs） is proposed as a new set of classification features and compared with the linear spectral frequencies （LSFs） applied in a frame-level wideband speech/music discrimination system. These two sets of features can be shared by the classifier and coding module to reduce the total computational complexity, making our classification system suitable for multi-mode audio coding applications. A performance assessment and comparison of the features are made. The experiment results show that the ISFs and LSFs have similar good performance when using full covariance matrices in classification models and the ISFs perform slightly better when using diagonal matrices. Their statistical differences for speech and music signals are also revealed.

Discrimination Between Nuclear Explosions and Earthquakes: An Application of Wigner Distribution

In this paper,the nonstationary theory of Wigner Distribution is used to discriminate between underground nuclear explosions and natural earthquakes.Five underground explosions in Kazakhstan region and seven regional earthquakes in its adjacent areas have been analyzed.The result shows that the transient spectra of underground nuclear explosions are concentrated in the frequency range of 5-10 Hz,while the transient spectra of natural earthquakes are distributed widely from lower frequency to higher frequency.The transient frequency of nuclear explosions shows linearity in the first stage(0【t【0.75 s)and its initial frequency is negative.The transient frequency of natural earthquakes rapidly changes in a jumping form and its initial frequency alternates between being positive and negative.The obtained results show that the method is more effective than previous ones in discriminating between underground nuclear explosions and earthquakes.This paper also gives a preliminary explanation of the discrepancy

基于FDR和时频脉冲转换的长电缆缺陷极性识别研究

为解决采用频域反射技术进行长电缆缺陷检测时,其结果易受低频段数据缺失占比的影响,而难以判断电缆缺陷极性的问题,该文提出一种基于频域反射技术的电缆阻抗失配点时频脉冲转换算法以实现缺陷的定位和极性判别。首先,采用2阶Nuttall自卷积窗的快速傅里叶计算方法对不同类型的电缆阻抗失配点进行定位。其次,提出电缆阻抗失配点时频脉冲转换算法,利用高斯窄带包络信号良好的频段调节能力和时频特性,详细阐述了时频脉冲的参数设计和极性判断方法。之后,运用仿真,对不同类型的阻抗失配点进行时频脉冲转换,验证了该算法的有效性。最后,采用该算法对实验室含接头长1500m的10k V XLPE电缆进行实验验证。仿真和实验结果表明:时频脉冲转换算法可以有效地定位长电缆阻抗失配点并且实现不同类型阻抗失配点的极性识别;同时,不同长度电缆阻抗失配点的时频脉冲转换结果不受低频段数据缺失占比的影响,有效提高了长电缆阻抗失配点的极性识别率。

电容耦合相位鉴频器性能仿真分析

针对电容耦合相位鉴频器节点电压波形转换抽象和传统实验调试难的问题,采用软件建立电路虚拟仿真模型,通过匹配输入信号和电路参数对应关系,获得了关键节点的节点波形和输出波形,通过测试不失真数据和失真数据获得了鉴频特性曲线,通过多个参数的步进扫描方式逐步获得了电路各个元件的最佳参数,实践证明,这种电路可视化的虚拟仿真调试方法能形象直观地展示节点波形,能有效验证抽象理论知识,提升学习质量。

基于带宽调整的两种混合载波跟踪环路研究

针对高动态导致载波复现频率与实际载波频率相差较大的问题,锁频环和锁相环已无法满足环路的跟踪需求,依据频率判决因子实现三阶锁频环辅助四阶锁相环和四相鉴频器之间相互切换的2种混合载波跟踪环路算法;在三阶锁频环辅助四阶锁相环的基础上,通过相位判决因子完成对载波环带宽的动态调整。结果表明,在动态为5000/150 g/120 g、载噪比为42 dB/Hz、跟踪初始多普勒为300 Hz时,基于带宽调整的2种混合载波跟踪环路能准确地剥离出电文信息,而单一的三阶锁频环辅助四阶锁相环载波跟踪环路不能实现;当跟踪初始多普勒为0时,环路稳定跟踪后加入25/20 g/20 g的动态,基于带宽调整的2种混合载波跟踪环路可以重新完成稳定跟踪并剥离出电文信息,而三阶锁频环辅助四阶锁相环载波跟踪环路直接失锁;低载噪比下的基于带宽调整的2种混合载波跟踪环路的跟踪相位误差方差相对较小、跟踪精度较高。

相位/比例鉴频综合实验电路的设计与实现

为帮助学生更好地理解频率解调的知识点,掌握不同的频率解调方案,设计了一套相位/比例鉴频综合实验电路。利用信号源产生调频波作为电路输入,通过选择开关实现比例鉴频器和叠加型相位鉴频器的灵活切换,达到两种电路形式有机结合的目的。通过鉴频功能、鉴频灵敏度以及限幅作用的测试与分析,深入探讨两种鉴频器的异同,实现理论和实践的融会贯通。教学实践表明,该实验效果良好,适用于本科实验教学、大学生科研和电子设计竞赛等多种场合。

微型离子漏斗减少低质量歧视效应的理论模拟研究

为减少微型离子漏斗的低质量歧视问题,本文提出了一种梯度下降射频(radio frequency,RF)信号施加方法,通过在漏斗出口端的多片电极上施加幅值递减的RF信号,提高低质荷比离子的传输效率。采用电场模拟软件SIMION和离子运动轨迹仿真软件AXSIM模拟分析微型离子漏斗在施加梯度下降RF信号时的离子传输性能。结果表明:相较于传统的RF施加方式,梯度下降RF施加方法能有效减少低质量歧视问题,且不影响高质量段的离子传输效率。另外,详细研究了在梯度下降RF施加方式下,RF的频率和直流场梯度等参数对离子传输效率的影响。进一步对梯度下降RF施加方法简化后,离子传输效率略有下降,但仍优于传统的RF施加方式,且降低了操作难度,提升了方案实施的可行性。

Baseline drift effect on the performance of neutron and γ ray discrimination using frequency gradient analysis

Frequency gradient analysis （FGA） effectively discriminates neutrons and γ rays by examining the frequency-domain features of the photomultiplier tube anode signal. This approach is insensitive to noise but is inevitably affected by the baseline drift similar to other pulse shape discrimination methods. The baseline drift effect is attributed to factors such as power line fluctuation, dark current, noise disturbances, hum, and pulse tail in front-end electronics. This effect needs to be elucidated and quantified before the baseline shift can be estimated and removed from the captured signal. Therefore, the effect of baseline shift on the discrimination performance of neutrons and ~ rays with organic scintillation detectors using FGA is investigated in this paper. The relationship between the baseline shift and discrimination parameters of FGA is derived and verified by an experimental system consisting of an americium-beryllium source, a BC501A liquid scintillator detector, and a 5 GSample/s 8-bit oscilloscope. The theoretical and experimental results both show that the estimation of the baseline shift is necessary, and the removal of baseline drift from the pulse shapes can improve the discrimination performance of FGA.

中药溻渍“表里共治”联合疗法治疗腰椎退行性病变临床观察

目的:观察中药溻渍“表里共治”联合疗法,即中药塌渍联合中频脉冲电治疗腰椎退行性病变的临床疗效。方法:将60例腰椎退行性病变患者随机分为对照组和观察组,每组30例。对照组给予中频脉冲电治疗,观察组在对照组基础上给予中药溻渍治疗,连续治疗10 d。观察治疗后视觉模拟评分法(Visual Analogue Scale,VAS)评分、日本骨科协会评估治疗分数(Japanese Orthopaedic Association Scores,JOA)评分以及临床疗效,观察并记录两组患者在治疗过程中不良反应的发生情况。结果:观察组治疗后VAS评分低于对照组,差异具有统计学意义(P <0.05)。观察组治疗后JOA评分高于对照组,差异具有统计学意义(P <0.05)。观察组临床治疗总有效率显著高于对照组,差异有统计学意义(P <0.05)。两组治疗过程中均未发生明显不良反应。结论:“表里共治”思想指导下的中药溻渍联合中频脉冲电治疗腰椎退行性病变能减轻患者疼痛、改善腰椎功能,无明显不良反应,且使用方便、患者接受度高,特别适合作为基层中医适宜技术进行推广。

脉冲计数式鉴频器鉴频特性及其仿真研究

脉冲计数式鉴频器是适用于相对频偏较大的调频波的解调电路。它由带通滤波器、电压比较器和低通滤波器3部分组成。带通滤波器滤除调频信号中混杂的噪声信号,电压比较器电路将调频信号转换为调频脉冲序列,低通滤波器对调频脉冲序列进行滤波,得到调制信号。分析了脉冲计数式鉴频器的电路原理与组成;利用Multisim仿真软件,对脉冲计数式鉴频电路进行了构建和仿真。仿真结果表明,脉冲计数式鉴频器具有良好的线性特征,频带较宽,电路结构简单,适用于不同载波频率、频偏相对较大的调频信号的解调。

星载测风激光雷达355 nm光学鉴频器及闭环控制系统

三通道355 nm光学鉴频器广泛应用在星载测风激光雷达回波信号鉴频过程中,是实现双边缘风速多普勒鉴频的核心元件,其指标与可靠性决定了系统的探测精度。研制了基于压电换能器(piezo-electric transducer,PZT)调谐的355 nm三通道标准具鉴频模块,模块有效口径35 mm,峰值透过率75%,自由光谱范围12.5 GHz,半高宽1.7 GHz。通过三通道测试系统对自由光谱范围、半高宽、峰值透过率、调谐系数等指标进行了测试。结果表明:当外部驱动电压为75 V时,峰值透过率分别为0.859、0.878和0.735,半高全宽分别为1.843 GHz、1.882 GHz和1.611 GHz,调谐系数为1.96 GHz/V、1.93 GHz/V和1.88 GHz/V。针对光学鉴频模块3个通道PZT调谐系数不一致的情况,分析出对风速误差的影响范围为±0.1 m/s。通过对闭环控制系统进行测试,该系统可实现对355 nm激光发射频率的实时锁定,解决了光学鉴频模块每次工作状态初始位置不一致带来的问题,提高了风速鉴频精度,可实现锁定时间长达30 min以上,满足了星载测风激光雷达的应用需求。另外,仿真研究表明:当三通道光学鉴频模块间隔变化0.08 nm时,引起的风速误差为1 m/s。

一种基于CORDIC算法的数字鉴频方法

本文提出了一种基于CORDIC (Coordinate Rotation Digital Computer)算法的数字鉴频方法。首先给出了基于CORDIC算法的鉴相原理,讨论了CORDIC算法的鉴相范围;然后讨论了差分鉴频的方法,特别是对低数据率情况下的差分鉴频进行了探讨,并给出了一种实用的数字鉴频结构。计算机仿真结果和FPGA仿真结果表明,基于CORDIC算法流水结构和一阶差分结构实现的数字鉴频方法是可行的,而且是高效的。

FFT谱连续细化分析的富里叶变换法

本文提出了利用富里叶交换对ＦＦＴ谱的局部进行细化分析的方法．在细化频谱分析时，可以得到某个主要频率成份频率、幅值、相位的精确值，极大地提高了频率分辨力，对瞬态及恒定采样长度信号的频率细化分析十分有效。