Narrow-band interference excision in spread-spectrum systems using new N-sigma algorithm based on fuzzy threshold

The key to narrow-band interference excision in frequency domain is to determine the excision thresh- old in direct-sequence spread-spectrum （DS-SS） systems. The excision threshold is a non-linear function related to the number and the power of interference, and attempting to get the exact relation of threshold related to the number and the power of interference is almost impossible. The N-sigma algorithm determines the excision threshold using subsection function; however, the excision threshold determined by this method is not exact. A new method to determine the threshold of N-sigma algorithm is proposed. The new method modifies the scale factor N by use of the membership function. The threshold determined by this method is consecutive and smooth, and it is closer to the fact than that of the initial N-sigma algorithm. The GPS signal and single-tone （CW） interference （that is, typical narrow-band interference） are implemented in the simulation, and the results are presented to demonstrate the validity of the new algorithm.

Non-Supervised Learning for Spread Spectrum Signal Pseudo-Noise Sequence Acquisition

An idea of estimating the direct sequence spread spectrum（DSSS） signal pseudo-noise（PN） sequence is presented. Without the apriority knowledge about the DSSS signal in the non-cooperation condition, we propose a self-organizing feature map（SOFM） neural network algorithm to detect and identify the PN sequence. A non-supervised learning algorithm is proposed according the Kohonen rule in SOFM. The blind algorithm can also estimate the PN sequence in a low signal-to-noise（SNR） and computer simulation demonstrates that the algorithm is effective. Compared with the traditional correlation algorithm based on slip-correlation, the proposed algorithm＇s bit error rate（BER） and complexity are lower.

Neural network approach to blindestimation of PN spreading sequence in lower SNR DS/SS signals

An approach based on discrete Karhunen-Loeve transformation of the DS/SS signals is proposed to estimate PN sequence in lower S/N ratio DS/SS signals. Characteristics of self-organization and principle components extraction of unsupervised neural networks are exploited adequately. Theoretical analysis and experimental results are provided to show that this approach can work well on the lower S/N ratio input signals.

Fast method for spreading sequence estimation of DSSS signal based on maximum likelihood function

To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. By simplifying the objective function of maximum likelihood estimation, the algorithm can realize sequence synchronization and sequence estimation via adaptive iteration and sliding window. Since it avoids the correlation matrix computation, the algorithm significantly reduces the storage requirement and the computation complexity. Simulations show that it is a fast convergent algorithm, and can perform well in low signal to noise ratio (SNR).

A Neural Network Approach to Blind Estimation of PN Spreading Sequence in DS/SS Signals

In this paper, a new approach is proposed to estimate pseudo noise(PN) sequence in the lower SNR DS/SS signals blindly. This method utilizes the characteristics of self-organization, principal components analysis and extraction of unsupervised neural networks adequately, in addition to its higher-speed operation ability, successfully solve the difficult problem about PN sequence blind estimation. The theoretic analysis and experimental results show that this approach can work very well on lower SNR input signals.

基于LoRa通信的无线发射台信号智能监测技术研究

为实现大面积无线发射台信号覆盖监测,有效地抵御监测过程中多径干扰和频率选择性衰减等干扰因素的影响,研究基于LoRa通信的无线发射台信号智能监测技术。在无线发射台发出信号后,转换成数字信号进行对比,识别出有效发射台信号后,通过级联型LoRa组网方式以及LoRa通信技术,将数据发送到服务器中存储,实现无线发射台信号的传输。利用循环位移因子对基带产生的Chirp信号完成调频扩频调制,扩展信号频谱,增强信号抗干扰能力以及传输可靠性,增强信号监测的效果。实验结果表明:该方法能够在距离LoRa终端设备2.5 km处依旧接收到发射台信号,丢包率为12%,能够准确地监测到无线发射台是否存在发射信号。

基于SVD-K-means算法的软扩频信号伪码序列盲估计

针对通信中软扩频信号伪码序列盲估计困难的问题,提出一种奇异值分解(singular value decomposition,SVD)和K-means聚类相结合的方法。该方法先对接收信号按照一倍伪码周期进行不重叠分段构造数据矩阵。其次对数据矩阵和相似性矩阵分别进行SVD完成对伪码序列集合规模数的估计、数据降噪、粗分类以及初始聚类中心的选取。最后通过K-means算法优化分类结果,得到伪码序列的估计值。该算法在聚类之前事先确定聚类数目,大大减少了迭代次数。同时实验结果表明,该算法在信息码元分组小于5 bit,信噪比大于-10 dB时可以准确估计出软扩频信号的伪码序列,性能较同类算法有所提升。

多途混响环境中声扩频信号线性与相关性分析

为分析浅海多途信道中声扩频信号的相关性和线性,建立了计入频率衰减与海底损耗的浅海Pekeris波导虚源法计算模型;对浅海中的脉冲信号与扩频信号进行了仿真计算,通过混响室试验初步研究了多途混响环境中扩频信号的线性。仿真结果显示:虚源法和简正波法的频域解一致,得到了与简正波理论相同的低频模式频散现象,验证了虚源法适用于浅海理想波导、Pekeris波导中的低频问题;当发生模式频散,低频扩频信号的相关性能强于同扩频参数的高频信号。试验结果表明:低频脉冲的时域波形发生畸变、展宽时,同频率的扩频信号能准确测出反射信号的几何时延,证明了低频多途效果仍可看作每个“路径”信号的线性叠加。

基于圆周相关扩频信号的快速捕获改进方法

针对大多普勒频偏、低信噪比条件下长周期伪码的扩频信号捕获问题,提出了一种基于圆周相关扩频信号的快速捕获改进方法。该算法对圆周相关后的结果利用快速傅里叶变换(FFT)进行频率估计,扩大了传统圆周相关法的扫频步进,使扫频步进不再受跟踪环路带宽的限制。理论分析及仿真结果表明,在信噪比为-34 dB、多普勒频率为500 kHz条件下算法可以正确地估计出伪码相位和多普勒频偏。在达到相同的灵敏度条件下,所提算法的平均捕获时间与传统的圆周相关法相比缩短了约47%,与基于FFT的并行频率搜索法相比缩短了约88%。另外,用于频率估计的FFT点数仅占圆周相关点数的1%,故额外增加的硬件资源很少。算法逻辑控制简单,尤其适用于大多普勒频偏、低信噪比及长周期伪码的卫星通信系统。

低载噪比突发扩频信号的快速捕获设计

突发扩频信号是卫星无线电测定业务的一种扩频调制信号,针对传统突发扩频信号,即入站信号,对快速捕获灵敏度要求越来越高的需求,提出了一种低载噪比突发扩频信号的快速捕获硬件设计实现方法。利用同步头加Walsh码基于快速傅里叶变换(Fast Fourier Transform,FFT)的突发扩频信号全并行处理的方法,入站信号快捕接收的积分时长能够达到15 ms,相较于传统的捕获算法,性能实现了约2 dB的提升。仿真验证及工程实现结果表明,该方案载噪比可达到37.5 dBHz,为未来全球化小型化通用化接收终端提供了改进方向。

50GHz~110GHz宽带信号下变频技术

矢量信号分析仪作为传统扫频式频谱仪与快速傅里叶变换技术的结合,能够对信号进行数字化处理,分析各种调制信号,同时获得测量信号的幅度和相位信息,对于现代通信意义重大。随着电磁波的应用频率扩展到毫米波乃至太赫兹波段,矢量信号分析仪的测量频率也急需拓展到更高频段,在系统前端搭载下变频器可实现这一目的。基于50GHz~110GHz宽带信号的下变频技术开展研究,研制了变频系统中多个关键器件,包括频分50GHz~110GHz信号的宽带开关、抑制镜频信号的宽阻带波导滤波器以及基于倍频放大模块的本振,同时搭建了50GHz~110GHz宽带信号下变频系统,将50GHz~110GHz宽带信号下变频到4.6GHz~39.6GHz。实验表明,下变频后的信号在任意2GHz内平坦度小于±3.5dB,对镜频信号的抑制大于60dBc,输出杂散抑制度大于40dBc,本振泄漏抑制大于70dBc,满足系统指标要求。

一种非相干扩频信号跟踪中HPK-P位同步捕获法

星载非相干扩频应答机在接收非相干扩频信号时,特别是在低信噪比条件下,信号跟踪环路中积分结果会因比特翻转而衰减严重,从而影响跟踪环路性能。针对上述问题,提出了一种HPK-P(Half-period Kokkonen-Pietila)位同步捕获法,将位同步时钟捕获精度缩短至半个伪码周期长,降低积分值衰减量,提高了跟踪前期的环路性能。仿真结果表明,与K-P法、半周期直方图法相比,HPK-P法更适合-24 dB低信噪比下的环路跟踪。在现场可编程门阵列(Field Programmable Gate Array,FPGA)上对HPK-P法进行测试,在信噪比为-24 dB,多普勒频偏范围为±1.5 kHz,多普勒加速度为+2.5 kHz/s条件下验证了该设计的可行性。

基于扩展频域时域反射法的在线光伏阵列故障检测信号特性研究

基于扩展频域时域反射法(Spread Spectral Time Domain Reflectometry,SSTDR)的光伏阵列故障诊断方法存在检测盲区和衰减特性,有必要研究检测信号的性质以提高故障检测性能。首先,对检测信号在光伏阵列中的传输行为进行研究,探究不同信号参数对检测范围和精度的影响;其次,根据光伏电池的动态模型和排布规律,搭建光伏阵列故障检测仿真平台,通过断路故障仿真实验对结果进行验证,结果表明,改善信号能有效增强相关峰辨识能力,使光伏组件检测数量增加4块;最后,综合考虑检测盲区和衰减特性对检测性能的影响,提出基于SSTDR的光伏阵列故障检测信号选择策略,用以确定测距范围和最优信号参数。

高动态短猝发扩频自适应信号快捕系统设计

在高动态环境下,短猝发信号传输过程中往往会产生普勒频偏,增加扩频信号的捕获时间,甚至降低信号捕获信噪比,为实现对扩频自适应信号的快速、有效捕获,设计高动态短猝发扩频自适应信号快捕系统;系统硬件采用模块化设计方式,改装信号接收模块和滤波模块,从信号缓存和锁相环两个方面调整系统电路;在硬件系统支持下,通过扩频过程的模拟确定高动态短猝发扩频信号特征,通过特征匹配实现对高动态环境中短猝发扩频信号的自适应搜索;计算捕获长度、频率、门限等参数,实现系统的短猝发扩频自适应信号快速捕获功能;实验结果表明,在无噪声条件下,优化设计系统输出扩频信号信噪比的平均值为141.6,捕获时间平均为8 s,捕获面积平均为90 km^(2);在有噪声条件下,系统输出扩频信号信噪比的平均值为121.8,捕获时间为10 s,捕获面积为130 km^(2)。

面向卫星通信的混合多址通信接收方案研究

卫星通信场景中,随着卫星通信的发展,频谱资源日益紧缺,利用率过低。卫星信道的开放性且过长的卫星链路使得卫星传输隐蔽性差,难以保证信号的安全传输。为了应对频谱资源紧张与安全传输的需求,借鉴非正交多址(Non Orthogonal Multiple Access,NOMA)的思想,叠加传输扩频信号与非扩频信号,在接收端设计分离方案,并设计循环迭代消除流程。仿真表明,所提方案可以保证信息的安全传输,且分离后的误码率损失可以通过循环迭代改善,符合实际应用。

强信号全覆盖环境高精密传感器微弱信号调制设计

在强信号的存在下,传感器微弱信号会被干扰、淹没或认为噪声,导致信号无法准确读取影响传感器的性能。为了解决这个问题,提出了一种强信号全覆盖环境高精密传感器微弱信号调制设计方法。该方法利用压缩感知技术重构完整的高精密传感器微弱信号集,通过自适应滤波器进行滤波以降低噪声,提高微弱信号的信噪比。利用基于正弦载波的扩频调制技术对微弱信号展开调制,将微弱信号扩展到宽频带中,以提高微弱信号的抗干扰能力和传输效率。实验结果表明,所提方法的信号重构精度高,能够有效滤除信号中的噪声,提高信号的抗噪声能力。并且信号调制性能好、抗干扰能力强。

Approach to blind estimation of the PN sequence in DS-SS signals with residual carrier

This paper presents an approach of singular value de- composition plus digital phase lock loop to solve the difficult problem of blind pseudo-noise （PN） sequence estimation in low signal to noise ratios （SNR） direct sequence spread spectrum （DS-SS） signals with residual carrier. This approach needs some given parameters, such as the period and code rate of PN sequence. The received signal is firstly sampled and divided into non-overlapping signal vectors according to a temporal window, whose duration is two periods of PN sequence. An autocorrelation matrix is then computed and accumulated by those signal vectors one by one. The PN sequence with residual carrier can be estimated by the principal eigenvector of the autocorrelation matrix. Further more, a digital phase lock loop is used to process the estimated PN sequence, it estimates and tracks the residual carrier and removes the residual carrier in the end. Theory analysis and computer simulation results show that this approach can effectively realize the PN sequence blind estimation from the input DS-SS signals with residual carrier in lower SNR.

基于GAN的直扩信号生成算法

将深度学习模型应用至电子干扰技术来生成干扰信号具有重要的现实意义。将生成对抗网络(generative adversarial network,GAN)应用于信号生成领域,对电磁扩频信号频谱数据的分布进行深度学习,并生成与其相干的干扰信号。在实验中GAN的生成器和判别器互相博弈训练,通过自适应矩估计(adaptive moment estimation,Adam)进行优化,最终训练出良好的模型,可以生成所需信号。实验结果表明,基于GAN的信号生成算法生成的数据分布已基本具备真实数据分布普遍具有的特点,对同一信噪比的电磁频谱数据进行深度学习后,生成数据能够较为准确地学习到不同信噪比电磁频谱数据的不同特点。

基于周期插值的自编码扩频系统自干扰抑制

针对自编码扩频系统存在误码传递产生的自干扰问题,本文提出了基于伪随机序列周期插值的自编码扩频系统,该方法采用周期的插入伪随机序列,改变自编码扩频通信系统的扩频序列的产生方式,隔断在接收端采用恢复的信息码元作为解扩序列对接收到的序列进行解扩产生的误码传递。本文构建了基于伪随机序列周期插值的自编码扩频系统,推导了基于伪随机序列周期插值的自编码扩频系统的理论表达式。理论分析与仿真结果表明:在高斯白噪声信道与瑞利信道情况下均可改善系统在低信噪比时的误码性能;通过倒谱分析表明基于伪随机序列周期插值的自编码扩频系统无周期性,未改变系统的隐蔽性能。