High-Sensitivity Acquisition of Ultrahigh Dynamic Direct Sequence Spread Spectrum Signals in Space Communications

According to the requirements of the high-sensitivity acquisition of Direct Sequence Spread Spectrum(DSSS) signals under ultrahigh dynamic environments in space communications, a three-dimensional joint search of the phase of Pseudo-Noise-code(PN-code),Doppler frequency and its rate-of-change is presented to achieve high sensitivity in sensing high-frequency dynamics. By eliminating the correlation peak loss caused by ultrahigh Doppler frequency and its rate-of-change offset,the proposed method improves the acquisition sensitivity by increasing the non-coherent accumulation time. The validity of the algorithm is proved by theoretical analysis and simulation results. It is shown that signals with a carrier- to-noise ratio as low as 39 dBHz can be captured with high performance when the Doppler frequency is up to ±1 MHz and its rate-of-change is up to ±200 kHz/s.

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.

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).

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.

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.

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.

Rake接收中信号幅度估计算法及误差影响分析

针对直接扩频通信系统Rake接收中信号幅度估计的问题,分析了幅度估计误差对信号信噪比恶化的影响,得出归一化幅度估计方差与两路信号合并之后的信号信噪比恶化的关系公式;对典型的信号幅度估计算法进行分析,提出了一种基于辅助通道的幅度估计算法,可以在低信噪比且无数据辅助的情况下获得更好的估计性能;对于QPSK调制,两路信号信噪比分别为snr1和snr2,且snr1≥snr2,snr2≥-10 dB,的条件下,取观测长度为2048,采用基于辅助通道的幅度估计算法进行信号幅度估计,实验结果表明,幅度估计误差导致的性能恶化小于0.01 dB,达到了抑制多径干扰、提高通信系统性能的效果。

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.

A novel M-ary modulation technique based on optimal chirp signal design

A novel M-ary chirp modulation technique based on an optimal chirp signal design is proposed in this paper to offer higher data rate for an indoor wireless chirp spread spectrum communication system. Both linear chirp signals and combined chirp signals are used in this system to reduce the effect of the cross correlation, and simplify the complexity of the system. The optimal scheme of de- signing both linear chirp signals and combined chirp signals is discussed to minimize the value of the cross correlation and obtain a better system performance. Simulation results show that, compared with the binary orthogonal chirp modulation technique, the M-ary chirp modulation technique based on an optimal chirp signal set has a higher data rate with a reasonable bit-error rate （BER） perform- ance under both additive white gaussian noise （AWGN） channel and indoor wireless channel.

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。

带残余频偏的软扩频信号伪码序列盲估计

针对带残余频偏的软扩频信号伪码序列盲估计难的问题,提出一种奇异值分解(singular value decomposition,SVD)结合全数字锁相环(digital phase locked loop,DPLL)的方法。所提方法首先对待处理信号通过不重叠分段生成数据矩阵,每段信号长度为一倍伪码周期;然后利用其自相关矩阵的右上角元素估计失步点进行同步,并且在重新计算自相关矩阵后根据较大特征值个数估计进制数;最后通过多次快速SVD算法结合DPLL最终实现伪码序列的盲估计。仿真结果显示,所提方法在低信噪比条件下可以有效估计出带残余频偏的软扩频信号的伪码序列,并且性能优于其他对比方法。

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。

基于信号分离的扩展频谱时域反射法盲区消除研究

扩展频谱时域反射法进行线缆故障检测时,因检测盲区的存在而难以对近距离故障有效识别,这不仅减小了检测范围,也限制了其在实际应用中的广泛性。本文针对该方法中的盲区问题,深入分析盲区产生的机理,提出了一种基于信号分离的盲区消除方法。该方法基于入射信号与反射信号线性叠加的特性,通过数字信号处理中的减法运算,有效地实现了两者的分离,使得在盲区内准确地识别反射信号,提取故障信息。本方法通过数字信号处理技术来消除盲区,避免了硬件平台的改动,算法简单,易实现,适应场景广泛。实验结果显示,在中心频率为62.5 MHz的检测系统中,使用本方法进行开路和短路故障在线检测,其最大绝对误差仅为0.16 m,充分验证了所提方法的有效性和实用性。

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。

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。

扩频通信信号多分辨重叠正交变换抗干扰仿真

为了提高扩频通信安全性能,提出一种基于滤波器的扩频通信信号抗干扰方法。分析扩频通信信号多分辨重叠的变化特点,针对变化特点利用综合滤波器倒转通信信号的冲激响应时间,并通过滤波器分解扩频通信信号。分析扩频通信信号有源干扰机理,实现噪声干扰辨别,获取多分辨变换域矢量条件。在此基础上,基于滤波器的输入状态和输出状态得出扩频通信信号的估计误差,对接收信号的矢量进行多分辨重叠正交变换,并修正信号的子带能量估计结果。最后引入前向纠错编码方法提高扩频通信信号在弱信号环境中的抗干扰性能,确保通信信号可靠传输。通过实验验证在不同参数条件下所提方法的抗干扰效果,通过对比结果证明上述方法能有效地实现扩频通信信号抗干扰。

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。

Chirp-DS-BPSK雷达通信一体化波形设计

针对线性调频-二进制相移键控(Chirp-Binary Phase Shift Keying,Chirp-BPSK)雷达通信一体化信号存在模糊函数受通信数据严重影响的问题,分析了传统周期扩频、混沌序列扩频及Logistic映射混沌序列的自相关性能,设计了一种扩频信号与线性调频脉冲相结合的雷达通信一体化共用波形,即Chirp-DS-BPSK一体化信号。该一体化波形分别采用混沌序列和BPSK方式对通信数据进行直接序列扩频与调制,以线性调频信号作为载波,并采用脉冲成型滤波器来提高频谱利用率,降低脉压旁瓣。最后,通过仿真分析证明了所提波形具有良好的模糊函数特性和误码率性能。在扩频比为7的条件下,与传统的Chirp-BPSK波形相比,Chirp-DS-BPSK波形的脉压峰值旁瓣比降低了约2.69 dB,通信误码率下降约8.45 dB,表明Chirp-DS-BPSK比Chirp-BPSK更适合作为雷达通信一体化共用波形。