Radio Frequency Interferences (RFI), such as strong Continuous Wave Interferences (CWI), can influence the Quality of Service (QoS) of communications, increasing the Bit Error Rate (BER) and decreasing the Signal-to-N...Radio Frequency Interferences (RFI), such as strong Continuous Wave Interferences (CWI), can influence the Quality of Service (QoS) of communications, increasing the Bit Error Rate (BER) and decreasing the Signal-to-Noise Ratio (SNR) in any wireless transmission, including in a Digital Video Broadcasting (DVB-S2) receiver. Therefore, this paper presents an algorithm for detecting and mitigating a Multi-tone Continuous Wave Interference (MCWI) using a Multiple Adaptive Notch Filter (MANF), based on the lattice form structure. The Adaptive Notch Filter (ANF) is constructed using the second-order IIR NF. The approach consists in developing a robust low-complexity algorithm for removing unknown MCWI. The MANF model is a multistage model, with each stage consisting of two ANFs: the adaptive IIR notch filter <i>H</i><i><sub>l</sub></i>(<i>z</i>) and the adaptive IIR notch filter <i>H</i><i><sub>N</sub></i>(<i>z</i>), which can detect and mitigate CWI. In this model, the ANF is used for estimating the Jamming-to-Signal Ratio (JSR) and the frequency of the interference (<i>w(0)</i>) by using an LMS-based algorithm. The depth of the notch is then adjusted based on the estimation of the JSR. In contrast, the ANF <i>H</i><i><sub>N</sub></i>(<i>z</i>) is used to mitigate the CW interference. Simulation results show that the proposed ANF is an effective method for eliminating/reducing the effects of MCWI, and yields better system performance than full suppression (<i>k<sub>N</sub></i>=1) for low JSR values, and mostly the same performance for high JSR values. Moreover, the proposed can detect low and high JSR and track hopping frequency interference and provides better Bit error ratio (BER) performance compared to the case without an IIR notch filter.展开更多
Radio frequency interference (RFI) is greatly harmful to Global Navigation Satellite System (GNSS) receivers. Sweep interference is one of the RFI for the GNSS receivers, which can degrade the performance of GNSS rece...Radio frequency interference (RFI) is greatly harmful to Global Navigation Satellite System (GNSS) receivers. Sweep interference is one of the RFI for the GNSS receivers, which can degrade the performance of GNSS receivers seriously. In this paper, the Fractional Fourier Transform (FrFT) of time-frequency analysis is proposed in the GNSS interference detection and suppression. The FrFT method is tested for detecting and suppressing sweep interference, which is generated by a GNSS jammer. In the simulation experiment, the GNSS signal affected by sweep frequency interference is successfully captured after interference suppression by using the proposed method, which shows its effectiveness. The interference detection performance of the FrFT method is compared with the conventional techniques such as Short-Time Fourier transform (STFT) and Wigner-Ville distribution (WVD). The detection performance is improved by about a least one order of magnitude. In the aspect of interference suppression, a threshold method based on detection probability is proposed, and the performance of the proposed threshold method is compared with the conventional threshold methods. In the result, the interference tolerance is increased by 5 dB compared with the mean threshold method, and by 9 dB compared with the fixed threshold.展开更多
随着无线电技术的发展,射频干扰(radio frequency interference,RFI)对射电天文观测的影响越来越大,尤其是周期性RFI对天文观测的影响越来越显著。本文围绕宽带、高时间分辨率频谱数据,采用阈值计算、噪声通道过滤、快速傅里叶变换、周...随着无线电技术的发展,射频干扰(radio frequency interference,RFI)对射电天文观测的影响越来越大,尤其是周期性RFI对天文观测的影响越来越显著。本文围绕宽带、高时间分辨率频谱数据,采用阈值计算、噪声通道过滤、快速傅里叶变换、周期计算、通道合并、来源分析和模板库建立等步骤,提出一种面向宽带频谱序列的周期RFI统计方法。将该方法应用于新疆天文台南山观测站26 m射电望远镜(Nan Shan 26 m Radio Telescope,NSRT)脉冲星观测终端数据,有效地检测并提取出了频谱序列中的周期性RFI,可为进一步电磁干扰缓解提供数据支撑。展开更多
针对射电天文观测过程中的射频干扰(Radio Frequency Interference, RFI)问题,详细分析了国内外台站射频干扰抑制策略。根据各天文台站实际观测过程中遇到的射频干扰问题,分别从主动预防阶段、预相关阶段、后相关阶段、机器学习和深度...针对射电天文观测过程中的射频干扰(Radio Frequency Interference, RFI)问题,详细分析了国内外台站射频干扰抑制策略。根据各天文台站实际观测过程中遇到的射频干扰问题,分别从主动预防阶段、预相关阶段、后相关阶段、机器学习和深度学习等方面研究了射频干扰的预防策略和抑制方法。详细分析了主动预防阶段可采取的方法,预相关阶段的自适应滤波和空间滤波方法,后相关阶段的VarThreshold, SumThreshold和奇异值分解等方法。探讨了基于机器学习的主成分分析、支持向量机、全卷积神经网络、卷积神经网络、U-Net等相关技术和方法在射频干扰信号处理方面的应用。展开更多
针对探地雷达(Ground Penetrating Radar,GPR)与移动通信系统终端存在的频谱共用的电磁兼容性问题,着重分析了GPR接收中随机性射频干扰(Radio Frequency Interference,RFI)的性质,以及该类RFI与GPR目标回波信号在小波多尺度分解中分布...针对探地雷达(Ground Penetrating Radar,GPR)与移动通信系统终端存在的频谱共用的电磁兼容性问题,着重分析了GPR接收中随机性射频干扰(Radio Frequency Interference,RFI)的性质,以及该类RFI与GPR目标回波信号在小波多尺度分解中分布的差异性,并基于此分析,提出了基于小波变换域的GPR随机RFI抑制算法,利用两种实测实验数据进行验证,结果表明,该方法能较好地抑制GPR的随机性RFI。展开更多
Radio-frequency interference （RFI） affects greatly the quality of the data and retrieval products from space-borne microwave radiometry. Analysis of the Advanced Microwave Scanning Radiometer on the Earth Observing ...Radio-frequency interference （RFI） affects greatly the quality of the data and retrieval products from space-borne microwave radiometry. Analysis of the Advanced Microwave Scanning Radiometer on the Earth Observing System （AMSR-E） Aqua satellite observations reveals very strong and widespread RFI contam- inations on the C- and X-band data. Fortunately, the strong and moderate RFI signals can be easily identified using an index on observed brightness temperature spectrum. It is the weak RFI that is diffi- cult to be separated from the nature surface emission. In this study, a new algorithm is proposed for RFI detection and correction. The simulated brightness temperature is used as a background signal （B） and a departure of the observation from the background （O–B） is utilized for detection of RFI. It is found that the O–B departure can result from either a natural event （e.g., precipitation or flooding） or an RFI signal. A separation between the nature event and RFI is further realized based on the scattering index （SI）. A positive SI index and low brightness temperatures at high frequencies indicate precipitation. In the RFI correction, a relationship between AMSR-E measurements at 10.65 GHz and those at 18.7 or 6.925 GHz is first developed using the AMSR-E training data sets under RFI-free conditions. Contamination of AMSR-E measurements at 10.65 GHz is then predicted from the RFI-free measurements at 18.7 or 6.925 GHz using this relationship. It is shown that AMSR-E measurements with the RFI-correction algorithm have better agreement with simulations in a variety of surface conditions.展开更多
Radio Frequency Interference （RFI） causes severe contamination to passive and active microwave sensing observations and corresponding retrieval products. RFI signals should be detected and filtered before applying t...Radio Frequency Interference （RFI） causes severe contamination to passive and active microwave sensing observations and corresponding retrieval products. RFI signals should be detected and filtered before applying the microwave data to retrieval and data assimilation. It is difficult to detect RFI over land surfaces covered by snow because of the scattering effect of snow surface. The double principal component analysis （DPCA） method is adopted in this study, and its ability in identifying RFI signals in AMSR-E data over snow covered regions is investigated. Results show that the DPCA method can detect RFI signals effectively in spite of the impact of snow scattering, and the detected RFI signals persistent over time. Compared to other methods, such as PCA and normalized PCA, DPCA is more robust and suitable for operational application.展开更多
Radio Frequency Interference (RFI) degrades the quality of focused Ultra-WideBand Syn- thetic Aperture Radar (UWB SAR) images. From both the theoretical analysis and real data valida- tion, it is concluded that target...Radio Frequency Interference (RFI) degrades the quality of focused Ultra-WideBand Syn- thetic Aperture Radar (UWB SAR) images. From both the theoretical analysis and real data valida- tion, it is concluded that target echo and RFI have different Region Of Support (ROS) in 2-D fast- time wavenumber and aperture wavenumber domain. Consequently, a novel adaptive filter is pro- posed according to the Wiener optimum criterion on the distinct ROS characteristics of target echo and RFI. Compared with the notch filter and the Least Mean Square (LMS) adaptive filter in previ- ous literatures, the proposed method is more computationally efficient with satisfactory suppression results. In terms of Signal-to-Interference Ratio Improvement (SIRI) and processing time, the per- formance of the proposed adaptive filter is verified with the field data collected with a UWB SAR system.展开更多
文摘Radio Frequency Interferences (RFI), such as strong Continuous Wave Interferences (CWI), can influence the Quality of Service (QoS) of communications, increasing the Bit Error Rate (BER) and decreasing the Signal-to-Noise Ratio (SNR) in any wireless transmission, including in a Digital Video Broadcasting (DVB-S2) receiver. Therefore, this paper presents an algorithm for detecting and mitigating a Multi-tone Continuous Wave Interference (MCWI) using a Multiple Adaptive Notch Filter (MANF), based on the lattice form structure. The Adaptive Notch Filter (ANF) is constructed using the second-order IIR NF. The approach consists in developing a robust low-complexity algorithm for removing unknown MCWI. The MANF model is a multistage model, with each stage consisting of two ANFs: the adaptive IIR notch filter <i>H</i><i><sub>l</sub></i>(<i>z</i>) and the adaptive IIR notch filter <i>H</i><i><sub>N</sub></i>(<i>z</i>), which can detect and mitigate CWI. In this model, the ANF is used for estimating the Jamming-to-Signal Ratio (JSR) and the frequency of the interference (<i>w(0)</i>) by using an LMS-based algorithm. The depth of the notch is then adjusted based on the estimation of the JSR. In contrast, the ANF <i>H</i><i><sub>N</sub></i>(<i>z</i>) is used to mitigate the CW interference. Simulation results show that the proposed ANF is an effective method for eliminating/reducing the effects of MCWI, and yields better system performance than full suppression (<i>k<sub>N</sub></i>=1) for low JSR values, and mostly the same performance for high JSR values. Moreover, the proposed can detect low and high JSR and track hopping frequency interference and provides better Bit error ratio (BER) performance compared to the case without an IIR notch filter.
文摘Radio frequency interference (RFI) is greatly harmful to Global Navigation Satellite System (GNSS) receivers. Sweep interference is one of the RFI for the GNSS receivers, which can degrade the performance of GNSS receivers seriously. In this paper, the Fractional Fourier Transform (FrFT) of time-frequency analysis is proposed in the GNSS interference detection and suppression. The FrFT method is tested for detecting and suppressing sweep interference, which is generated by a GNSS jammer. In the simulation experiment, the GNSS signal affected by sweep frequency interference is successfully captured after interference suppression by using the proposed method, which shows its effectiveness. The interference detection performance of the FrFT method is compared with the conventional techniques such as Short-Time Fourier transform (STFT) and Wigner-Ville distribution (WVD). The detection performance is improved by about a least one order of magnitude. In the aspect of interference suppression, a threshold method based on detection probability is proposed, and the performance of the proposed threshold method is compared with the conventional threshold methods. In the result, the interference tolerance is increased by 5 dB compared with the mean threshold method, and by 9 dB compared with the fixed threshold.
文摘随着无线电技术的发展,射频干扰(radio frequency interference,RFI)对射电天文观测的影响越来越大,尤其是周期性RFI对天文观测的影响越来越显著。本文围绕宽带、高时间分辨率频谱数据,采用阈值计算、噪声通道过滤、快速傅里叶变换、周期计算、通道合并、来源分析和模板库建立等步骤,提出一种面向宽带频谱序列的周期RFI统计方法。将该方法应用于新疆天文台南山观测站26 m射电望远镜(Nan Shan 26 m Radio Telescope,NSRT)脉冲星观测终端数据,有效地检测并提取出了频谱序列中的周期性RFI,可为进一步电磁干扰缓解提供数据支撑。
文摘针对射电天文观测过程中的射频干扰(Radio Frequency Interference, RFI)问题,详细分析了国内外台站射频干扰抑制策略。根据各天文台站实际观测过程中遇到的射频干扰问题,分别从主动预防阶段、预相关阶段、后相关阶段、机器学习和深度学习等方面研究了射频干扰的预防策略和抑制方法。详细分析了主动预防阶段可采取的方法,预相关阶段的自适应滤波和空间滤波方法,后相关阶段的VarThreshold, SumThreshold和奇异值分解等方法。探讨了基于机器学习的主成分分析、支持向量机、全卷积神经网络、卷积神经网络、U-Net等相关技术和方法在射频干扰信号处理方面的应用。
文摘针对探地雷达(Ground Penetrating Radar,GPR)与移动通信系统终端存在的频谱共用的电磁兼容性问题,着重分析了GPR接收中随机性射频干扰(Radio Frequency Interference,RFI)的性质,以及该类RFI与GPR目标回波信号在小波多尺度分解中分布的差异性,并基于此分析,提出了基于小波变换域的GPR随机RFI抑制算法,利用两种实测实验数据进行验证,结果表明,该方法能较好地抑制GPR的随机性RFI。
基金Supported by the National Key Basic Research and Development (973) Program of China(2010CB951600)National Natural Science Foundation of China(40875015,40875016,and40975019)+2 种基金Special Fund for University Doctoral Students of China(20060300002)Chinese Academy of Meteorological Sciences"Application of Meteorological Data in GRAPES-3DVar" ProgramNOAA/NESDIS/Center for Satellite Applications and Research (STAR) CalVal Program
文摘Radio-frequency interference （RFI） affects greatly the quality of the data and retrieval products from space-borne microwave radiometry. Analysis of the Advanced Microwave Scanning Radiometer on the Earth Observing System （AMSR-E） Aqua satellite observations reveals very strong and widespread RFI contam- inations on the C- and X-band data. Fortunately, the strong and moderate RFI signals can be easily identified using an index on observed brightness temperature spectrum. It is the weak RFI that is diffi- cult to be separated from the nature surface emission. In this study, a new algorithm is proposed for RFI detection and correction. The simulated brightness temperature is used as a background signal （B） and a departure of the observation from the background （O–B） is utilized for detection of RFI. It is found that the O–B departure can result from either a natural event （e.g., precipitation or flooding） or an RFI signal. A separation between the nature event and RFI is further realized based on the scattering index （SI）. A positive SI index and low brightness temperatures at high frequencies indicate precipitation. In the RFI correction, a relationship between AMSR-E measurements at 10.65 GHz and those at 18.7 or 6.925 GHz is first developed using the AMSR-E training data sets under RFI-free conditions. Contamination of AMSR-E measurements at 10.65 GHz is then predicted from the RFI-free measurements at 18.7 or 6.925 GHz using this relationship. It is shown that AMSR-E measurements with the RFI-correction algorithm have better agreement with simulations in a variety of surface conditions.
文摘Radio Frequency Interference （RFI） causes severe contamination to passive and active microwave sensing observations and corresponding retrieval products. RFI signals should be detected and filtered before applying the microwave data to retrieval and data assimilation. It is difficult to detect RFI over land surfaces covered by snow because of the scattering effect of snow surface. The double principal component analysis （DPCA） method is adopted in this study, and its ability in identifying RFI signals in AMSR-E data over snow covered regions is investigated. Results show that the DPCA method can detect RFI signals effectively in spite of the impact of snow scattering, and the detected RFI signals persistent over time. Compared to other methods, such as PCA and normalized PCA, DPCA is more robust and suitable for operational application.
文摘Radio Frequency Interference (RFI) degrades the quality of focused Ultra-WideBand Syn- thetic Aperture Radar (UWB SAR) images. From both the theoretical analysis and real data valida- tion, it is concluded that target echo and RFI have different Region Of Support (ROS) in 2-D fast- time wavenumber and aperture wavenumber domain. Consequently, a novel adaptive filter is pro- posed according to the Wiener optimum criterion on the distinct ROS characteristics of target echo and RFI. Compared with the notch filter and the Least Mean Square (LMS) adaptive filter in previ- ous literatures, the proposed method is more computationally efficient with satisfactory suppression results. In terms of Signal-to-Interference Ratio Improvement (SIRI) and processing time, the per- formance of the proposed adaptive filter is verified with the field data collected with a UWB SAR system.
