DSC based Dual-Resunet for radio frequency interference identification

Radio frequency interference(RFI)will pollute the weak astronomical signals received by radio telescopes,which in return will seriously affect the time-domain astronomical observation and research.In this paper,we use a deep learning method to identify RFI in frequency spectrum data,and propose a neural network based on Unet that combines the principles of depthwise separable convolution and residual,named DSC Based Dual-Resunet.Compared with the existing Unet network,DSC Based Dual-Resunet performs better in terms of accuracy,F1 score,and MIoU,and is also better in terms of computation cost where the model size and parameter amount are 12.5%of Unet and the amount of computation is 38%of Unet.The experimental results show that the proposed network is a high-performance and lightweight network,and it is hopeful to be applied to RFI identification of radio telescopes on a large scale.

Multi-Frequency Interference Detection and Mitigation Using Multiple Adaptive IIR Notch Filter with Lattice Structure

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 Hl(z) and the adaptive IIR notch filter HN(z), 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 (w(0)) 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 HN(z) 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 (kN=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.

Detection of radio-frequency interference signals from AMSR-E data over the United States with snow cover

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.

RFI Detection for Multichannel HRWS SAR System Based on Spatial Cross Correlation

Multichannel high-resolution and wide-swath(HRWS)imaging is an advanced digital beamforming technique for future synthetic aperture radar(SAR)systems.However,radio frequency interference(RFI)is a critical concern for HRWS SAR missions,which distorts measure-ments and produces image artifacts.In this paper,the spatial cross-correlation coefficients of multichannel HRWS SAR signals are investigated for RFI detection.It is found when the two channels are correlated,RFI-polluted areas present lower coherence values than non-polluted areas in the same scenarios,which makes previous methods fail.Further,this paper studies the case of two fully decorrelated channels to maximize the coherence difference among RFI and target echoes,and RFI detection is realized by exploiting the anomaly value of coherence.Experimental results of real air-borne multichannel SAR data demonstrate that the RFI can be detected successfully.

Satellite RFI mitigation on FAST

As the most sensitive single-dish radio telescope,the Five-hundred Aperture Spherical radio Telescope(FAST)is very susceptive to radio frequency interference(RFI)from active radio services.Moreover,due to the rapid development of space applications and research,satellite interference has become one of the main RFI sources for FAST,particularly at the L band.Therefore,we have developed several measures to mitigate satellite RFI.On the one hand,an antenna with 4.5-meter diameter has been constructed and installed at the FAST site to detect the satellite interference in the frequency band between 1 to 5 GHz.Meanwhile,we have developed a satellite RFI database based on the FAST sky coverage,the observing frequency bands,and known satellite systems.By combining the satellite RFI monitoring antenna and the database,we have established a satellite RFI mitigation system.With this system,we can not only track satellites to collect their characteristics and update the database but also help the observer to program the observing plan by predicting satellite interference.During the practical observation of FAST at the L band,the feasibility of this system to mitigate satellite RFI has been proved.In particular,the system effectively avoids strong satellite interference from entering the main beam of the telescope and causing receiver saturation.

RFI measurements and mitigation for FAST

Radio Frequency Interference(RFI)mitigation is essential for supporting the science output of Five-hundred-meter Aperture Spherical radio Telescope(FAST)due to its high sensitivity.In order to protect FAST from RFI,an Electromagnetic Compatibility(EMC)study has been carried out and the operation of a Radio Quiet Zone(RQZ)is ongoing.RFI measurements of the telescope instruments and monitoring of the active radio services outside the site have revealed the radiation properties of the RFI sources.Based on the measurement results and theoretical analysis,various EMC methods have been implemented for the telescope to decrease the RFIs.Meanwhile,the main RFI sources in the FAST RQZ,such as mobile stations,broadcast stations and navigation instruments,have been identified,and the technical measures have been adopted to protect the quiet radio environment around the site.The early science outputs of FAST have demonstrated the efficiency of RFI mitigation methods.

Detection and suppression of narrow band RFI for synthetic aperture radar imaging

Radio frequency interference（RFI） is becoming more and more frequently, which makes it an important issue in SAR imaging.RFI presented in synthetic aperture radar either on purpose or inadvertent will distort the useful SAR echoes, thus degrade the SAR image quality.To resolve this issue, a long time study was carried out to study the characteristic of the RFI through the RFIaffected spaceborne and airborne SAR data.Based on the narrow band nature of RFI, this paper proposes a new process which contains both RFI detection and RFI suppression.A useful subband spectral kurtosis detector is first used to detect RFI, and then its results are used for RFI suppression.The proposed process has two advantages： one is the economization on the compute time for unnecessary interference suppression when no RFI existed; the other is improving the performance of the suppression method with knowing the exact position where RFI is.Moreover, the previous RFI suppression method––subband spectral cancelation（SSC） is supplemented and perfected.The subband division step is also elaborated detail in this paper.The experiment results show that the subband spectral kurtosis detector exhibits good performance in recognizing both weak and narrow-band RFI.In addition, the validity of the SSC method with subband spectral kurtosis detector is also validated on the real SAR echoes.

Preprocessing of ionospheric echo Doppler spectra

The real-time information of the distant ionosphere can be acquired by using the Wuhan ionospheric oblique backscattering sounding system(WIOBSS),which adopts a discontinuous wave mechanism.After the characteristics of the ionospheric echo Doppler spectra were analyzed,the signal preprocessing was developed in this paper,which aimed at improving the Doppler spectra.The results indicate that the preprocessing not only makes the system acquire a higher ability of target detection but also suppresses the radio frequency interference by 6-7 dB.