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.

Combinatory Spread－Spectrum Multiple－Access Based on Residue Number System：System and Performance

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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.

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.

New acquisition decision algorithm for multiple access interference suppression in DSSS system

For decreasing the multiple access interference of weaker signal acquisition in direct sequence spread spectrum（DSSS） systems,a new single decision algorithm is presented.The maximum value of correlation results is conventionally detected.However,there may be not only one strong peak among correlation results when the cross-correlation noise is strong enough to affect the correlation results.The proposed algorithm decreases the false alarm probability through the decision of the ratio of the maximum value and the second maximum value of the correlation results.Theoretical analysis and simulation results indicate that the proposed algorithm effectively suppresses the acquisition problem of multiple access interference in DSSS system.

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.

Frequency Hopping Spread Spectrum Security Improvement with Encrypted Spreading Codes in a Partial Band Noise Jamming Environment

Frequency Hopping Spread Spectrum (FHSS) system is often deployed to protect wireless communication from jamming or to preclude undesired reception of the signal. Such themes can only be achieved if the jammer or undesired receiver does not have the knowledge of the spreading code. For this reason, unencrypted M-sequences are a deficient choice for the spreading code when a high level of security is required. The primary objective of this paper is to analyze vulnerability of linear feedback shift register (LFSRs) codes. Then, a new method based on encryption algorithm applied over spreading codes, named hidden frequency hopping is proposed to improve the security of FHSS. The proposed encryption security algorithm is highly reliable, and can be applied to all existing data communication systems based on spread spectrum techniques. Since the multi-user detection is an inherent characteristic for FHSS, the multi-user interference must be studied carefully. Hence, a new method called optimum pair “key-input” selection is proposed which reduces interference below the desired constant threshold.

An underwater acoustic direct sequence spread spectrum communication system using dual spread spectrum code

With the goal of achieving high stability and reliability to support underwater point-to-point communications and code division multiple access(CDMA) based underwater networks, a direct sequence spread spectrum based underwater acoustic communication system using dual spread spectrum code is proposed. To solve the contradictions between the information data rate and the accuracy of Doppler estimation, channel estimation, and frame synchronization, a data frame structure based on dual spread spectrum code is designed. A long spread spectrum code is used as the training sequence, which can be used for data frame detection and synchronization, Doppler estimation, and channel estimation. A short spread spectrum code is used to modulate the effective information data. A delay cross-correlation algorithm is used for Doppler estimation, and a correlation algorithm is used for channel estimation. For underwater networking, each user is assigned a different pair of spread spectrum codes. Simulation results show that the system has a good anti-multipath, anti-interference, and anti-Doppler performance, the bit error rate can be smaller than 10^(-6) when the signal-to-noise ratio is larger than-10 dB, the data rate can be as high as 355 bits/s, and the system can be used in the downlink of CDMA based networks.

Subspace decomposition-based correlation matrix multiplication

The correlation matrix, which is widely used in eigenvalue decomposition （EVD） or singular value decomposition （SVD）, usually can be denoted by R = E[yiy＇i]. A novel method for constructing the correlation matrix R is proposed. The proposed algorithm can improve the resolving power of the signal eigenvalues and overcomes the shortcomings of the traditional subspace methods, which cannot be applied to low SNR. Then the proposed method is applied to the direct sequence spread spectrum （DSSS） signal＇s signature sequence estimation. The performance of the proposed algorithm is analyzed, and some illustrative simulation results are presented.

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。

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。

一种基于CRDSA的VDE-SAT随机接入方法

甚高频数据交换-卫星部分(VHF Data Exchange-Satellite,VDE-SAT)是下一代海事通讯系统甚高频数据交换系统(VHF Data Exchange System,VDES)的关键组成部分,用于实现航海船站与海事卫星以及航海船站间的相互通信和数据传输,其链路层接入性能对于VDES的实际应用效果有着重要影响。针对当前实际应用中航海船站随机接入VDES系统容易出现峰值吞吐量较低和线性工作区较短的问题,该文在深入分析国际电信联盟制定的ITU-R M.2092标准规范和航海船站接入VDE-SAT的技术特性,以及现有无线网络随机接入协议的基础上,提出一种适用于VDE-SAT的基于功率分集和直接序列扩频的竞争解决分集时隙ALOHA(Power Diversity and Direct Sequence Spread Spectrum CRDSA,PD-DS-CRDSA)方法。该方法在传统无线网络竞争解决分集时隙ALOHA(Contention Resolution Diversity Slotted ALOHA,CRDSA)算法的基础上,通过采用多副本技术和连续干扰消除技术提高数据包成功解码率,同时引入功率分集和直接序列扩频技术,在一定程度上消除了传统CRDSA算法容易出现的“环路”问题。实验仿真结果表明,该方法在提高VDE-SAT随机接入的峰值吞吐量,延长线性工作区和降低数据包碰撞率等方面有较好表现。

一种干扰环境下基于决策树的直扩信号检测算法及试验验证

针对传统的直接序列扩频(Direct Sequence Spread Spectrum,DSSS)信号检测方法在干扰环境下检测性能急剧下降的问题,论文提出了一种基于决策树的直扩信号检测算法。该方法首先提取信号的倒谱和时域互相关特征作为检测统计量,然后通过网格搜索法寻找最优门限,之后将检测统计量与门限进行比较,并利用决策树进行检测判决,最后对所提检测算法进行仿真分析与实验验证。仿真结果表明,所提方法具有良好的检测性能,检测率在干信比小于7 dB时,检测率大于98%。实验结果表明,所提算法与时域互相关检测法相比,正确率提高了1.46%。

低信噪比长伪码直扩信号伪码周期的估计方法

针对低信噪比长伪码调制直扩(DS-SS)信号的伪码(PN码)周期参数估计的难题,提出了一类基于信号功率谱二次处理的新方法。该方法首先对信号的功率谱进行估计,接着将估计出的功率谱作为输入信号再来求取功率谱,最后得到的二次谱就会在长伪码调制DS-SS信号PN码周期的整数倍处得到一列尖锐的二次谱线,通过估计这些谱线的间距就可以获得其PN码的周期估计。为了在低信噪比情况下增强二次谱线和估计效果,采用了由多个接收信号矢量计算得到的二次谱结果进行平均累积的办法。理论分析和计算机模拟表明,该类方法在较低的输入信噪比条件下能良好地工作。

一种基于循环统计量的直扩信号检测与参数估计方法

本文利用循环统计量检测循环平稳性的特性,将渐近最优2χ检验方法推广到直扩信号的盲检测,提出了一种基于循环统计量的直扩信号检测方案;理论上推导了直扩信号二阶循环统计量的表达式,分析了时间间隔的选取对从二阶循环统计量估计循环频率的影响,据此提出了基于循环统计量的直扩信号载频和chip速率等参数的估计新方法.该方法避免了多维搜索,且不需要信号的伪码序列和各频率参数等先验信息,可实现信号的“盲”检测和“盲”参数估计.仿真实验证明了本文方法的有效性.

基于四阶累积量的DSSS/QPSK信号检测方法研究

根据高斯白噪声的四阶累积量恒为零这一特性,研究了DSSS/QPSK信号的四阶累积量,提出了基于四阶累积量不同切片c4x(0,0,0)、c4x(τ,τ,τ)、c4x(0,τ,τ)和c4x(0,0,τ)的时域和频域检测方法.仿真结果表明,频域检测方法性能优于时域检测方法;综合考虑检测性能和实现难度,基于c4x(0,0,τ)的频域检测方法最好,在虚警概率为1%,信噪比为-11dB时,检测概率仍可达到50%以上.没有引入大规模的矩阵运算,运算量小,易于实现.

DSSS信号的扩频序列估计

提出了一个在非协作通信中对直接扩频序列(Direct Spread Spectrum Sequence,DSSS)信号的扩频序列进行估计的简单而有效的算法。在算法中我们提出了两个测度函数,一个用于搜索扩频序列在接收信号中的起始位置,另一个用于序列中的逐码片(chip)估计。理论分析和计算机仿真表明了此算法的有效性。