一种改进的盲自适应窄带干扰抑制方法

为有效抑制直接序列扩频通信中的窄带干扰,论文提出了一种改进的盲自适应窄带干扰抑制方法.该方法在盲自适应滤波器的基础上,通过引入非线性预测算法对接收信号进行处理,提高了滤波器的干扰抑制性能.计算机仿真结果验证了文中方法的有效性.     

改进的抗窄带干扰非线性预测方法

为了有效抑制直接序列扩频通信中的窄带干扰,提出了2种改进的非线性预测方法（NLMSN和LNLMSN）。NLMSN是在原非线性预测方法的基础上,针对NLMS算法在强干扰条件下抑制性能不理想的缺点,运用修正LMS Newton算法对其进行改进而得到的方法。LNLMSN是在NLMSN的基础上,引入Laguerre时延单元,使得这两种方法在取得相同信噪比改善量的同时,减少了滤波器阶数,降低了方法实现的复杂度。仿真结果表明,与原方法相比,改进方法的抗干扰性能有了较大提高。     

自适应滤波技术在扩频通信系统抗窄带干扰中的应用

自适应滤波技术在扩频通信窄带干扰抑制的应用中,需要一种快速收敛的自适应算法以便能跟踪快速变化的干扰信号。文章提出将基于LSL自适应算法的格型滤波器应用于直接序列扩频通信系统中。仿真结果表明,LSL自适应算法在线性预测中具有快速收敛特性,并且在收敛过程中具有数值稳定性,从而显著改善了系统的抗窄带干扰能力。     

直接序列扩频系统中强窄带干扰抑制的一种非线性自适应抑制快速算法

本文将一种改进的非线性自适应抑制快速算法应用于直接序列扩频通信的强窄带干扰抑制中,并将其与其它时域自适应抑制算法进行仿真比较,在收敛速度和收敛精度相当的情况下,该算法结构简单、计算量适中且误码率小,特别是相对于其它算法,其对窄带干扰的抑制深度具有明显的优势。     

IIR自适应滤波器抑制PN扩频的窄带干扰

本文叙述了IIR自适应滤波器用于抑制PN扩频通信系统的窄带干扰的原理,推导出输出信噪比的表达式,最后运用计算机进行仿真,得出IIR自适应滤波器优于FIR自适应滤波器的结论。     

基于RLS算法的直接序列扩频抗窄带干扰技术

在敌方有意的窄带强干扰下,扩频通信系统可以利用时域自适应滤波算法来抑制干扰。介绍了基于时域预测的自适应滤波RLS算法,仿真结果表明其对DSSS系统中的窄带干扰有较好地抑制效果。     

直接序列扩频通信中基于循环平稳特性的抗窄带干扰算法研究

从扩频通信接收机等效基带信号的模型出发，分析了接收信号中扩频信号分量和窄带干扰分量的循环平稳性以及接收信号的波特率谱相关性与采样之间的关系，并给出基于频移滤波器窄带干扰抑制接收机的自适应实现结构，理论分析和仿真结果表明，使用频移滤波器的接收机抗窄带干扰性能优于基于线性时不变滤波器的接收机。     

全相位数字滤波

本文提出全相位DFT数字滤波器,全相位FIR滤波器及全相位FFT频谱分析.全相位数字滤波器它有良好的滤波器频率特性,适用於频谱分析,多路复用和扩频通信中窄带干扰抑制等频域自适应滤波器.     

窄带抑制在抗干扰卫星通信中的应用

采用扩频技术的卫星通信具有较好的低截获概率和抗干扰性。由于带宽和设备复杂性的限制，直接序列扩频通信系统的扩频增益受限，大功率的窄带干扰对其性能的影响较大，本文采用了基于时域预测的自适应滤波器对其进行抑制，仿真结果表明抑制效果明显，极大地提高了整个卫星通信系统的抗干扰能力。     

一种用于抑制直扩通信中窄带干扰的非线性自适应方法

在分析线性自适应滤波抑制单频干扰、自回归过程窄带干扰和窄带BPSK调制信号干扰的性能的基础上,提出了一种非线性自适应波抑制方法.在对窄带干扰进行预测前,通过对扩谱信号的估计,使得窄带干扰预测的背景噪声由非高斯转变为高斯,并消除扩谱信号对干扰估计的影响,再通过NLMS和RLS自适应算法进行干扰抑制.理论分析和仿真试验结果表明,这种改进方法对于系统性能的改善效果,明显优于常规自适应滤波抑制方法.     

一种改进的基于ATF算法的直扩通信干扰抑制技术

提出了直扩通信中一种改进的基于ATF（自适应时频）算法的干扰抑制方法。对原有算法进行了优化并给出了相应的自适应去干扰算法。采用自适应滤波技术取代子带剔除法,自适应地跟踪窄带干扰,改善了有用信号的丢弃情况,有效地抑制了窄带干扰。分析和仿真结果表明,基于ATF算法的自适应小波包时频干扰抑制方法比传统的子带剔除法在性能上更为优越,干扰定位速度也较快,干扰抑制能力强。     

Frequency shift keyed narrowband interference rejection: optimal exponential weighting factor for the RLS algorithm

Cochannel narrowband interference can limit the performance of direct sequence spread spectrum (DSSS) and high frequency (HF) systems. Narrowband interference (NBI) can be single tone, chirped or frequency shift keyed (FSK) in nature and numerous techniques for its removal have been proposed. Linear adaptive prediction filters based on autoregressive modelling have been suggested owing to their ability to perform in a non-stationary environment. In the FSK narrowband interference case, adaptive filters are susceptible to excess residual errors owing to instantaneous frequency step changes and the finite convergence time required for the filter to adapt to a new interference frequency. The signal degradation owing to this type of interference becomes greater in high SNR regimes and has been found to be a function of the frequency parameters of the FSK interference signal. The paper discusses the convergence and frequency tracking properties of the recursive least squares (RLS) adaptive lattice filter using a posteriori estimation errors in the presence of FSK narrowband interference. An optimal exponential weighting factor that balances convergence time and steady state error is derived for this case of NBI. Results are compared to those of a previously proposed fast converging minimum frequency error (FCMFE) RLS lattice filter.     

直扩通信中基于ATF算法的窄带干扰抑制技术优化

提出了一种直扩通信中基于ATF算法的窄带干扰抑制技术的优化方法.采用自适应滤波技术取代子带剔除法,自适应地跟踪窄带干扰,改善了有用信号的丢弃情况,有效地抑制了窄带干扰.仿真结果表明,该算法在性能上更优越,干扰定位速度更快,干扰抑制能力得到较大提高.     

基于自适应IIR陷波滤波器的窄带干扰抑制技术

在存在窄带干扰时，扩频通信系统的性能可以通过使用各种不同的抗干扰滤波器来进一步提高。文中研究了二阶自适应格型IIR陷波滤波器在直扩通信中抗窄带干扰的应用，推导了系统信噪比改善因子和误比特率的闭合表达式。计算机仿真表明了该分析结果的正确性。     

直扩系统中IIR格型滤波器抑制窄带干扰新方法与性能分析

该文提出一种直扩系统中基于IIR格型陷波器时域频域相结合的窄带干扰抑制新方法,该方法采用时域频域并行处理的结构,通过最优加窗和频谱校正技术在频域精确估计出干扰信号的频率,根据频率估计误差和干信比求出最优陷波带宽,由此自适应地调整时域IIR格型陷波器的参数。分析和实验表明,该方法较传统的自适应IIR窄带干扰抑制方法不仅具有更高的稳定性和实时性,而且在干扰得到有效抑制的情况下使有用信号的损失达到最小。     

基于IIR滤波器的窄带干扰抑制技术仿真与实现

研究了直扩通信中二阶自适应格型IIR陷波滤波器在抗窄带干扰中的应用,推导了系统信噪比改善因子和误比特率的闭合表达式,分析了算法的性能,并进行了MATLAB仿真。基础上,设计了FPGA可实现的自适应解扩重扩滤波器,该滤波器实现简单,硬件测试表明,滤波器达到了预期的性能指标,有效可抗窄带干扰在大约21dB。     

Performance of direct-sequence spread-spectrum receiver usingdecision feedback and transversal filters for combatting narrowbandinterference

A direct-sequence spread-spectrum (DSSS) receiver using both decision feedback (DFB) and two-sided transversal filters for combatting narrowband interference (NBI) is proposed. The receiver is made up of two branches. In the first branch, the conventional demodulator is followed by a DFB filter, while in the second, auxiliary branch, a demodulator with the carrier in quadrature is followed by a two-sided adaptive transversal (AT) filter. Performance of this receiver was analyzed on the basis of the calculated mean-square error and the probability of error at the output of the receiver. Special attention was paid to the effects caused by the propagation of errors in the DFB filter. The results obtained show that NBI rejection is fairly high and practically does not depend upon the difference of frequencies of the desired and interfering carriers or upon the interfering carrier level     

Narrow-band interference rejection in DS/CDMA systems using adaptive (QRD-LSL)-based nonlinear ACM interpolators

An Mth order adaptive lattice filter automatically generates all M of the outputs that would be provided by M separate transversal filters. This feature may effectively suppress narrow-band interference (NBI) of either unknown or time-varying bandwidth (or number of frequency bands) in direct-sequence code-division multiple access systems for which the order of the interference rejection filter that achieves the optimal performance is unknown or constantly changing. Moreover, a lattice filter may significantly outperform its transversal counterpart in complex jamming environments in which the adaptive lattice filter must suppress multiple jammers, since each stage of a lattice filter adapts to suppress an orthogonal component of the NBI. The paper develops a computationally efficient and numerically stable adaptive QR-decomposition-based least squares lattice (QRD-LSL)-based nonlinear approximate conditional mean interpolator to suppress NBI effectively. Simulation results demonstrate that both the signal-to-noise ratio improvement and the convergence rate achieved by the proposed interpolators outperform those of other existing prediction-based techniques.     

基于信息辅助块稀疏贝叶斯学习的直扩通信窄带干扰抑制

现有基于Nyquist-Shannon采样定理的窄带干扰(Narrowband Interference,NBI)抑制方法存在应用受限于采样率较高的问题。应用压缩感知(Compressive Sensing,CS)理论解决上述问题,利用NBI在频域表现出的块稀疏特性以及直接序列扩频(Direct Sequence Spread Spectrum,DSSS)信号的类噪声特性,提出了基于块稀疏贝叶斯学习(Block Sparse Bayesian Learning,BSBL)框架的DSSS通信NBI抑制模型。实现干扰抑制后,利用传统的CS重构算法实现DSSS信号的压缩域解调。为进一步提高算法性能,将NBI稀疏分块的块内自相关矩阵建模为单位矩阵,提出了信息辅助BSBL(Aid BSBL,ABSBL)算法,设计了基于ABSBL的DSSS通信NBI抑制算法。该算法在保持较好NBI抑制性能的条件下,提高了运算效率并且不依赖NBI的稀疏结构。仿真验证和对比分析结果表明,所提方法能够有效抑制DSSS通信中的NBI,在干扰强度相同的条件下,NBI带宽越小、压缩率越大,算法对NBI的抑制性能越好。