Analysis and Compensation of Frequency Offset in Co-Site Adjacent Channel Interference Suppression

Due to the mismatch of the circuit oscillators,there will always be a frequency offset between the transmitter and the receiver.In the adjacent channel interference(ACI)suppression system using the reconstruction and cancellation method,the frequency offset decreases the accuracy of the reconstructed signal and introduces a time-varying term in the interference cancellation,resulting in poor performance of the ACI suppression.In this paper,the relationship between the normalized frequency offset,signal-to-noise ratio and the loss of interference suppression capability is analyzed through formula derivation and simulation.The validity of the frequency offset compensation method based on the pilot sequence is verified,and the relationship between the sequence length and the estimation accuracy is given.This paper provides necessary method reference and data support for the engineering of ACI suppression.

A Novel Clutter Suppression Algorithm for Low-Slow-Small Targets Detecting Based on Sparse Adaptive Filtering

Passive detection of low-slow-small(LSS)targets is easily interfered by direct signal and multipath clutter,and the traditional clutter suppression method has the contradiction between step size and convergence rate.In this paper,a frequency domain clutter suppression algorithm based on sparse adaptive filtering is proposed.The pulse compression operation between the error signal and the input reference signal is added to the cost function as a sparsity constraint,and the criterion for filter weight updating is improved to obtain a purer echo signal.At the same time,the step size and penalty factor are brought into the adaptive iteration process,and the input data is used to drive the adaptive changes of parameters such as step size.The proposed algorithm has a small amount of calculation,which improves the robustness to parameters such as step size,reduces the weight error of the filter and has a good clutter suppression performance.

FM interference suppression for PRC-CW radar based on adaptive STFT and time-varying filtering

The influence of frequency modulation （FM） interfer- ence on correlation detection performance of the pseudo random code continuous wave （PRC-CW） radar is analyzed. It is found that the correlation output deteriorates greatly when the FM inter- ference power exceeds the anti-jamming limit of the radar. Accord- ing to the fact that the PRC-CW radar echo is a wideband pseudo random signal occupying the whole TF plane, while the FM in- terference only concentrates in a small portion, a new method is proposed based on adaptive short-time Fourier transform （STFT） and time-varying filtering for FM interference suppression. This method filters the received signal by using a binary mask to excise only the portion of the TF plane corrupted by the interference. Two types of interference, linear FM （LFM） and sinusoidal FM （SFM）, under different signal-to-jamming ratio （S JR） are studied. It is shown that the proposed method can effectively suppress the FM interference and improve the performance of target detection.

Multiple interferences suppression with space-polarization null-decoupling for polarimetric array

The adaptive digital beamforming technique in the space-polarization domain suppresses the interference with forming the coupling nulls of space and polarization domain.When there is the interference in mainlobe,it will cause serious mainlobe distortion,that the target detection suffers from.To overcome this problem and make radar cope with the complex multiple interferences scenarios,we propose a multiple mainlobe and/or sidelobe interferences suppression method for dual polarization array radar.Specifically,the proposed method consists of a signal preprocessing based on the proposed angle estimation with degree of polarization(DoP),and a filtering criterion based on the proposed linear constraint.The signal preprocessing provides the accurate estimated parameters of the interference,which contributes to the criterion for null-decoupling in the space-polarization domain of mainlobe.The proposed method can reduce the mainlobe distortion in the space-polarization domain while suppressing the multiple mainlobe and/or sidelobe interferences.The effectiveness of the proposed method is verified by simulations.

An interference suppression algorithm for cognitive bistatic airborne radars

Interference suppression is a challenge for radar researchers, especially when mainlobe and sidelobe interference coexist. We present a comprehensive anti-interference approach based on a cognitive bistatic airborne radar. The risk of interception is reduced by lowering the launch energy of the radar transmitting terminal in the direction of interference;main lobe and sidelobe interferences are suppressed via cooperation between the two radars. The interference received by a single radar is extracted from the overall radar signal using multiple signal classification(MUSIC), and the interference is cross-located using two different azimuthal angles. Neural networks allowing good, non-linear nonparametric approximations are used to predict the location of interference, and this information is then used to preset the transmitting notch antenna to reduce the likelihood of interception. To simultaneously suppress mainlobe and sidelobe interferences, a blocking matrix is used to mask mainlobe interference based on azimuthal information, and an adaptive process is used to suppress sidelobe interference. Mainlobe interference is eliminated using the data received by the two radars. Simulation verifies the performance of the model.

Improved DSE-CMA Error Function for Blind Multiuser Interference Suppression in DS/CDMA Systems

This paper presents an improved error function of dithered signed-error constant modulus algorithm （IDSE-CMA） for blind multiuser interference suppression in DS/CDMA systems. It uses a different error function to replace the former one in sign operation of the DSE-CMA and compares their performance in multiple access interference （MAI） suppression ability. Simulations indicate that the new algorithm has better performance than the similar CMA in terms of convergence speed and steady-state performance：

An Intelligent Optimization Approach to Non-stationary Interference Suppression for Wireless Networks

In this paper, we propose a new technique to effectively suppress non-stationary interference signal for wireless networks. This technique combines a new scheme of interference signal estimation with the intelligent optimization projection. In order to capture interference signal's subspace, a time-varying method is used to estimate the non-stationary interference.Orthogonal polynomials are used for the basis function instead of the power of the time to reduce the computational complexity.The interference is then removed from the corrupted signal by subspace projection, resulting in less distortion to the desired signal. The performance of this approach is validated by computer simulation.

SUBSET PARALLEL VOLTERRA FILTER FOR NARROWBAND INTERFERENCE SUPPRESSION IN DSSS COMMUNICATIONS

Subset Parallel Adaptive Volterra Filter (SPAVF) design algorithm is proposed in this letter. Contri-bution factor is introduced in SPAVF, and it can get rid of redundant elements efficiently in the extended input vector. Computational weight can be reduced largely, and BER performance of SPAVF can be improved by getting rid of the influence of redundant elements in the input vector. Simulation result proves its advantage compared to AVF and PSVF.

An ISS-OFDM based adaptive filtering mechanism for interference suppression in wireless multi-hop communication network

The negative impact on communication performance in wireless multi-hop communication net-work caused by limited bandwidth,high bit eror rate （BER）,fading,noise and interference is alleviated by an adaptive filtering game based on frequency subbands selection and predetemined threshold.Such threshold is being obtained in Gaussian and multipath fading channel according to the frequency-matching principle and BER performance.The dynamic selection of subbands will obtain high use efficiency without the help of frequency hopping,and propound a new thought to improve band limited communication for wireless multi-hop communication network.The effectiveness of the adaptive filtering method has been verified by interleaving spread spectrum orthogonal frequency division multiplexing （ISS-OFDM） in different interference conditions,and the simulating results based on network simulator 2 （NS2） indicate that system BER can be improved greatly.

Suppression to the cross-channel interference based on the short time Fourier transform

A new cross-channel interference suppression method is proposed to decrease the cross-channel interference in beat signals based on the short time Fourier transform （STY3＂） and the inverse short time Fourier transform （ISTFT） when the dual-orthogonal polarimetric frequency-modulated continu- ous wave （FMCW） radar adopts the opposite-slope linear frequency modulation signal pair in the simultaneous measurement mode. The STFT is applied only on the signals in the cross-interference intervals in the four polarimetric channels to decrease the computation complexity. A mask matrix for suppressing the interference is constructed using the constant false alarm ratio （CFAR） detection on the spectrograms by the STFY. The simulative results show that the cross-channel interference is effi- ciently suppressed by the proposed method. The comparison between the proposed method and the rejection method verifies the improved performance of the proposed method.

谐波干扰抑制下的低压配电网母线电压自动控制系统

母线电压的平稳程度,直接影响低压配电网的运行安全,因此设计谐波干扰抑制下的低压配电网母线电压自动控制系统。该系统以配电网调度系统的控制需求为前提,在系统无功补偿层引入抗谐波干扰无功发生器获取母线电压的无功补偿量,母线无功控制需求整定层依据该计算结果和母线电压控制指令,结合母线实时运行电压结果,对比判断母线实际电压结果和参考电压之间的差距,确定母线电压所需的无功补偿量,完成电压控制。测试结果显示:该系统能够有效控制母线电压谐波,谐波畸变率低于4.4%;能够保证电压的稳定,电压控制的偏差结果均在±1.5 V之间,母线在相位阶跃和稳态两种情况下的相位误差结果均低于0.075。

基于遗传算法优化BP神经网络的GNSS干扰源定位技术

全球导航卫星系统(GNSS)应用已全面深入到国家安全和国民经济当中,但由于GNSS信号到达地面后信号强度很弱,极易受到无意或有意的人为干扰。当出现压制干扰时会影响接收机正常工作,从而导致某一区域导航定位效果受到影响,因此对干扰源的排查和消除十分重要。针对上述压制干扰,通过在监测区域分布一定数量低成本接收机,利用其接收的载噪比数据特征实现干扰源的位置估计。考虑到信号传播过程中的衰减模型是非线性的,提出了基于遗传算法(Genetic Algorithm,GA)优化反向传播(Back Propagation,BP)神经网络的干扰源定位方法,通过神经网络学习得到监测区域载噪比特征的复杂非线性关系,GA对神经网络的初始权值和阈值进行优化,最终在监测区域通过梯度下降法搜索出干扰源位置。结果表明,GA优化后的网络预测误差更小,能够初步定位干扰源位置且平均定位误差率(Average Localization Error Rate,ALER)约为0.23%,验证了模型的合理性和有效性。

微光数字观瞄镜的强杂光抑制技术研究

针对观瞄镜强杂光干扰问题,提出一套完整的强杂光抑制技术方案。首先,对物镜内表面采用绒布消光;然后,在软件图像处理上结合使用相邻图像累加积分、直方图统计和宽动态灰度增强等算法完成强杂光抑制;在天空照度为1×10^(-3)lx以下的野外暗夜环境下,加入强杂光干扰后进行实验测试。实验结果表明,该技术方案能有效完成强杂光抑制和图像细节增强,提升图像质量。软件算法在FPGA(Field Programmable Gate Array)平台上运行,2 ms内完成图像处理工作,满足实时性要求。

基于遗传模糊PID算法的倒立摆稳摆抑噪抗扰实验与分析

倒立摆稳摆控制原理应用的实际工程需求牵引,使倒立摆成为检验各类控制算法的理想替代实验研究平台。因此,将倒立摆摆杆的姿态稳定控制和抑噪抗扰作为研究内容,以理论分析、编程实现、仿真实验和实物实验验证作为研究手段,聚焦控制器设计的优化。首先,引入模糊控制对PID参数调节进行优化,改固定参数调节为在线参数调节,旨在提高系统的鲁棒性与抗扰性;然后,运用遗传算法的量化因子和比例因子完成调节参数的在线寻优,通过设计适应度函数和选择算子,经过选择、交叉、变异不断演化迭代,最终获取最佳适应度个体、找到最优解,通过仿真验证遗传模糊PID算法突出的抑噪抗扰优势;最后,基于该控制策略进行倒立摆实物实验,验证了其指令跟踪有效性的结论。该研究表明:遗传模糊PID算法具有良好的指令跟踪和抑噪抗扰性能,具有一定的工程应用价值。

考虑电磁干扰的差动式电容力矩传感器动态校准方法

在差动式电容力矩传感器校准过程中,受设备电磁干扰的影响,造成校准结果存在较大偏差。为解决这一问题,在考虑电磁干扰的前提下,提出差动式电容力矩传感器动态校准方法。在差动式电容力矩传感器存在电磁干扰的情况下,采用小波变换方法抑制传感器中的电磁干扰。通过差动式电容力矩传感器的组成结构构建参数化数学模型,获取动态激励和结构响应两者之间的频域传递关系,利用最小二乘法分析传递函数的频域几何关系式,对传感器展开动态解耦和动态补偿。通过冲击剪断装置形成的力矩信号对传感器动态标定,利用检测电路测量阶跃信号对标定结果校准,完成差动式电容力矩传感器动态校准。实验测试结果表明,所提方法可以获取满意的动态校准结果。

局部鲁棒预处理的DME干扰抑制方法

全球定位系统(Global Positioning System, GPS) L5/北斗B2/Galilea E5是全球卫星导航系统(Global Navigation Satellite System, GNSS)的重要组成部分,为民用航空提供与生命安全相关的应用服务.然而L5/B2/E5信号处于受保护的航空无线电导航服务(Aeronautical Radio Navigation Service, ARNS)频段内(962~1213 MHz),同时工作在该频段内的还有民用航空导航系统测距机(Distance Measuring Equipment, DME)等. DME发射的大功率脉冲信号会对L5/B2/E5等卫星导航信号造成干扰,使得接收机无法正常捕获卫星信号或导致跟踪环路失锁.传统的DME干扰抑制方法通过在干扰稀疏域,如时域、频域和时频混合域进行DME干扰置零,这会在抑制干扰的同时完全消除与干扰重叠的卫星信号.为了降低DME干扰抑制对卫星信号的损失,本文提出基于鲁棒统计理论的局部鲁棒预处理的DME干扰抑制方法,根据DME干扰所在的稀疏域特性提取出存在干扰的信号片段后,应用非高斯分布下的鲁棒统计理论对提取出的数据样本进行鲁棒预处理,从而在抑制干扰的同时降低对卫星信号的影响.实验结果表明本文所提出的稀疏域局部鲁棒预处理的DME干扰抑制方法的性能优于相应的传统稀疏域方法,输出捕获因子比传统稀疏域方法提高1~2 dB.

基于线性自抗扰控制的柔性多状态开关直流电压控制策略

为提高柔性多状态开关(flexible multi-state switch,FMSS)的抗干扰能力,以保证在系统干扰的情况下维持直流电压稳定,该文提出一种基于线性自抗扰控制(linear active disturbance rejection control,LADRC)的FMSS直流电压控制策略,其控制策略可以将作用于研究对象的不确定因素整合成系统总扰动,并对扰动进行实时跟踪估计和补偿,以此抑制系统干扰。通过Matlab/Simulink对FMSS建模,并设计线性自抗扰控制器模块来替换电压外环和电流内环中的PI控制器模块。在系统干扰的情况下,对FMSS的抗干扰能力进行实验验证。仿真结果表明,与传统PI双环控制策略相比,基于LADRC的控制策略能更好地应对系统干扰,能有效提高系统干扰抑制的能力,维持FMSS直流电压稳定。

基于改进奇异谱分析的毫米波生物雷达干扰抑制方法

针对毫米波雷达间的互扰会造成生物雷达获取的微弱生命体征信号被淹没,导致无法准确测量呼吸心跳的问题,本文提出基于改进奇异谱分析的方法抑制雷达间互扰,通过相关性计算从受扰信号中选取目标差拍信号重构以抑制干扰和消除背景噪声。进一步提出基于信息熵的集合经验模态分解方法消除差拍信号残留的相位噪声,通过信息熵计算从集合经验模态分解后的固有模态函数分量中选择呼吸和心跳信号以抑制残留噪声。实验结果表明,所提出的方法能有效地从受干扰的信号中恢复呼吸和心跳信号,提高呼吸和心跳的信噪比。因此,本文所提方法提高了生物雷达的抗干扰能力,增强了生物雷达的实用性。

一种适用于卫星通信的自适应窄带干扰抑制方法

针对卫星通信系统中的抗干扰问题,提出一种能够根据干扰变化自适应调整策略的干扰抑制方法。该方法通过子带分割、按功率排序、依次陷波等方式进行陷波,然后对比陷波前后信号信噪比的增益,从而确定信噪比增益最大时所对应的子带陷波个数,最终得到信噪比增益最高也即性能最优的陷波方式。该方法不需要预先进行干扰检测,也不需要寻找和设置门限阈值,就可以对多种类型干扰进行自适应陷波,从而达到有效抑制包含单音、窄带、梳状或部分频带等不同干扰的目的,能够显著改善链路的通信性能,提高通信系统的抗干扰能力。

相位感知的水下平台背景宽带噪声干扰抑制

针对水下航行器等平台存在宽带背景噪声干扰导致目标检测能力下降问题,提出一种适用于多通道水听器阵列的深度学习宽带背景噪声干扰抑制方法。该方法通过含干扰信号的多通道频域特征级联保留了相位信息,使用深度复数神经网络建立了一个估计纯净目标信号频谱特征的学习模型实现干扰抑制,再利用常规波束形成方法实现目标检测与跟踪。仿真结果表明,在信干比为-15 dB,-20 dB,-25 dB的双目标信号条件下,所提干扰抑制方法可以有效减少近场干扰影响,提高了常规波束形成的检测能力。湖试结果表明,该方法能够自适应地实现平台宽带背景噪声干扰抑制,有效提升目标检测和跟踪性能。