Wideband Interference Research Articles

Experimental Evaluations on Learning-Based Inter-Radar Wideband Interference Mitigation Method

Experimental Evaluations on Learning-Based Inter-Radar Wideband Interference Mitigation Method

Interference Suppression Algorithm Based on Short Time Fractional Fourier Transform.

Narrowband interference and wideband interference are both common jamming signals against synthetic aperture radar, which can degrade the signal severely. To suppress interference effectively, an interference suppression method based on short-time fractional Fourier transform (STFrFT) is proposed. After transforming the signal into the time-frequency domain through STFrFT, an adaptive gain coefficient is determined for the instantaneous frequency spectrum at every certain time. The gain coefficient can be preserved while suppressing the interference. Finally, we obtain the useful signal by inverse STFrFT. The simulation and performance analysis show the effectiveness and validity of the proposed algorithm for measured data.

WBIM-GAN: A Generative Adversarial Network Based Wideband Interference Mitigation Model for Synthetic Aperture Radar

Wideband interference (WBI) can significantly reduce the image quality and interpretation accuracy of synthetic aperture radar (SAR). To eliminate the negative effects of WBI on SAR, we propose a novel end-to-end data-driven approach to mitigate WBI. Specifically, the WBI is mitigated by an explicit function called WBI mitigation–generative adversarial network (WBIM-GAN), mapping from an input WBI-corrupted echo to its properly WBI-free echo. WBIM-GAN comprises a WBI mitigation network and a target echo discriminative network. The WBI mitigation network incorporates a deep residual network to enhance the performance of WBI mitigation while addressing the issue of gradient saturation in the deeper layers. Simultaneously, the class activation mapping technique fully demonstrates that the WBI mitigation network can localize the WBI region rather than the target echo. By utilizing the PatchGAN architecture, the target echo discriminative network can capture the local texture and statistical features of target echoes, thus improving the effectiveness of WBI mitigation. Before applying the WBIM-GAN, the short-time Fourier transform (STFT) converts SAR echoes into a time–frequency domain (TFD) to better characterize WBI features. Finally, by comparing different WBI mitigation methods applied to several real measured SAR data collected by the Sentinel-1 system, the efficiency and superiority of WBIM-GAN are proved sufficiently.

A Practical Solution to Reduce Interference from Led Lights

Abstract The study explores the detection of a harmful, wide-band interference signal, whose origin is a traditional desk LED (light-emitting diode) lamp. The interference signal was noticed on the sensitive solar spectrometer observing system, which was operating at a frequency range between 100 and 300 MHz. The interference signal was so strong and wide-band that it destroyed totally the solar observations. The study introduces two practical EMI (Electromagnetic Interference) reducing methods: ferrite cores and shielding (shielding effectiveness, S.E.). Their theoretical background is presented, and, in addition, these methods are tested in practice. The measurements and tests showed that even simple ferrite core was a very effective method to reduce interference effects. It is important that a suitable setup will be found: a single ferrite core cannot solve a whole problem. This interference problem is very demonstrative and it can be used in educational purposes at an undergraduate level at Metropolia University of Applied Sciences, Finland. This study reveals the fact that standard lamps, which are on the market, do not necessarily follow good EMC (Electromagnetic Compatibility) practices.

Wideband interference suppression for automotive mmWave CS radar: From algorithm-based to learning-based approaches

Wideband interference suppression for automotive mmWave CS radar: From algorithm-based to learning-based approaches

Modeling and analysis for group delay mismatch effect on wideband adaptive spatial interference cancellation

The adaptive interference cancellation technique has been widely utilized in radar, GPS, data link, etc., systems to address challenges from external interference, such as co-site and hostile interference. Since the anti-jamming performance of the adaptive interference cancellation technique is sensitive to group delay mismatch between channels, the group delay mismatch becomes one of the main factors that limit the system’s anti-jamming capability. However, the traditional adaptive interference cancellation system’s mathematical model cannot quantitatively characterize the group delay mismatch effect on the wideband interference cancellation performance. In this paper, the mathematical model of the wideband adaptive spatial interference cancellation (ASIC) system is established, which considers the group delay mismatch, to quantitatively analyze the impact of group delay mismatch on the hostile interference cancellation. The mathematical model utilizes the weighted multi-tone signals to fit the wideband interference, and then, delay differences are attached to each tone signal to simulate the group delay mismatch. Then, the analytic expressions of weight and interference cancellation ratio are derived, which consider the interference bandwidth and group delay mismatch, to quantitatively analyze the group delay mismatch effect on the anti-jamming performance of the wideband ASIC system. Simulation results indicate that the theoretical analysis based on the mathematical model of wideband ASIC system are accurate, which can achieve the quantitative analysis of the group delay mismatch effect on the WIC performance.

Wideband Interference Cancellation System Based on a Fast and Robust LMS Algorithm.

The interference cancellation ratio (ICR) is a key performance indicator of digital-to-analog hybrid radio frequency (RF) interference cancellation systems. Aiming at the low convergence speed of a digital-to-analog hybrid RF interference cancellation system based on a multi-tap structure (MDARFICS), a novel, fast, and robust variable-step-size least-mean-square (LMS) algorithm based on an improved hyperbolic tangent function (IHVSS-LMS) is proposed. The IHVSS-LMS algorithm adopts an improved hyperbolic tangent function and uses adjustable parameters and the iteration number to jointly adjust the step size, which improves the convergence speed and reduces the computational complexity. Moreover, by using the prior information of the input signal, the non-linear relationship between the step size and the input signal power is established, which enhances the robustness and the ability to suppress interference with mutable power. The IHVSS-LMS algorithm is applied to the MDARFICS. Through theoretical derivation, the convergence speed and the steady-state expressions of the interference cancellation ratio of the MDARFICS are obtained. The simulation results show that under the conditions of high and low signal-to-noise ratio (SNR), the robustness, convergence speed, and steady-state error performance of the IHVSS-LMS algorithm are better than the existing variable-step-size algorithm. The experimental results show that using the IHVSS-LMS algorithm, the MDARFICS can not only effectively accelerate the convergence speed by at least three times but can also improve the ICR by more than 3 dB.

Development of a single LMS loop three channels analog adaptive co-site interference cancelling system

Co-site interference is becoming prominent on some independent platforms (e.g., airplanes, satellites, space stations, and vessels). Although many digital multichannel cancellation algorithms have been investigated, the saturation problem of the receiver front-end caused by severe co-site interference should be addressed first with analog RF cancellation. Many studies are currently being conducted to develop an analog adaptive co-site interference cancellation system (AACICS). However, double LMS (Least Mean Square) loop in every channel raises the complexity and implemented difficulty. Above all, the interference cancellation in the scene of antenna swaying has received little attention, which severely limits the effective suppression of wideband interference. This study developed an analog 3-channel adaptive co-site wideband interference cancellation system (AACWICS-3ch) with one LMS loop in every channel and established the equivalent model of the AACWICS-3ch. The steady-state weight and interference cancellation ratio (ICR) were obtained by analyzing and solving the equivalent model. An in-depth analysis was conducted on the quantitative relationship correlations between the interference cancellation bandwidth, ICR, system gain, and antenna swing amplitude. Results reveal that AACWICS-3ch can greatly enhance the interference cancellation performance compared to 2-channel analog adaptive co-site interference cancellation system (AACICS-2ch). The maximum improved ICR is greater than 30 dB, and it overcomes the complexity of double LMS loop cancellation system with the increasing of channel. Finally, simulations and experiments validated the improvement of interference cancellation performance in AACWICS-3ch.

Low-Complexity Wideband Interference Mitigation for UWB ToA Estimation.

Reliable time of arrival (ToA) estimation in dense multipath (DM) environments is a difficult task, especially when strong interference is present. The increasing number of multiple services in a shared spectrum comes with the demand for interference mitigation techniques. Multiple receiver elements, even in low-energy devices, allow for interference mitigation by processing coherent signals, but computational complexity has to be kept at a minimum. We propose a low-complexity, linearly constrained minimum variance (LCMV) interference mitigation approach in combination with a detection-based ToA estimator. The performance of the method within a realistic multipath and interference environment is evaluated based on measurements and simulations. A statistical analysis of the ToA estimation error is provided in terms of the mean absolute error (MAE), and the results are compared to those of a band-stop filter-based interference blocking approach. While the focus is on receivers with only two elements, an extension to multiple elements is discussed as well. Results show that the influence of strong interference can be drastically reduced, even when the interference bandwidth exceeds 60% of the signal bandwidth. Moreover, the algorithm is robust to uncertainties in the angle of arrival (AoA) of the desired signal. Based on these results, the proposed mitigation method is well suited when the interference bandwidth is large and when computational power is a critical resource.

Characterizing Transient Radio-Frequency Interference From Motors for the Square Kilometer Array Radio Telescopes

This paper considers the characterisation of wideband radio frequency interference generated by motors, diesel generators as well as fans for the Square Kilometre Array radio telescopes. The transient and/or impulsive nature of the emissions from the equipment, required as part of the telescope or ancillary hardware designs, can have a detrimental impact on highly time-sensitive scientific observations like pulsar science or gravitational wave detection. Wideband interference from pulses generated by servo motors with pulse-width modulation drivers, diesel generators and compressor alternating current fans are presented.

Multioctave Interference Detectors With Sub-Microsecond Response

High-power interferers are one of the main hurdles in wideband communication channels. To that end, this article presents a wideband interferer detection method. The presented technique operates by sampling the incoming signal as an input, and produces the frequency and the power readings of the detected interferer. The detection method relies on driving an open circuit stub, where the voltage is proportional to the power of the interferer, and the standing wave pattern is an indicator of its frequency. This approach is feasible over multioctave bandwidth with a wide power dynamic range. The concept is analyzed for design and optimization, and a prototype is built for a proof-of-concept. The measured results demonstrate the ability to detect an interferer within the 1–16 GHz frequency range, with a power dynamic range between <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$-$</tex-math> </inline-formula> 20 and 20 dBm. The detection concept is also fit with different types of tunable bandstop filters (BSFs) for automatic detection and suppression of the interferer if its power exceeds a programmable threshold. With a measured response time of 500 ns, the presented method is a technology enabler for wideband receivers.

Cognitive Sparse Imaging Method for MIMO Radar under Wideband Interference

Target three-dimensional (3D) high-resolution imaging via multiple-input multiple-output (MIMO) radar may suffer from a heavy sampling burden and complicated radio frequency interferences. Considering a collocated two-dimensional wideband MIMO radar under dynamic wideband interference (WBI), this paper proposes a cognitive method to achieve a 3D high-resolution target image with a reduced sampling cost. Firstly, based on the known knowledge of the target and WBI, provided by previous measurements, optimal sparse sampling in the 3D signal domain is conducted to reduce the number of sub-pulses and transceiving antennas by solving an optimization problem. Then, the detection and removal of the interfered signal components are conducted to provide the WBI information for following measurements and the interference-free signal cube for the target imaging process. Finally, by using the tensor-based smoothed L0 algorithm, the 3D high-resolution image of the target is obtained, providing the target information for the next measurement. Based on these three steps, a cognitive sparse imaging loop is formed for MIMO radar under WBI situations. The simulation and experiment results demonstrate the effectiveness and advantage of the proposed methods.

Non-linear photonic loop mirror based co-site interference canceller

Full duplex-in band (FDIB) is a well-established solution for increasing the data rate and spreading the link range for future communication systems. FDIB systems need no additional bandwidth requirement. However, they are confronted with a major interference challenge on the same site, called co-site interference (CSI). Long-established co-site interference cancellation (CSIC) methods achieve a cancellation depth upto 35 dB, conversely it has space containments, manufacturing imperfections, induces noise penalties and limits isolation bandwidth. To overcome these problems, RF photonic CSIC methods have been developed, which have produced 30 dB wide-band interference suppression. They also increase bandwidth, have a flexible structure, minimize losses and prevent periodic power fading. But these systems have a problem of inherent DC drift, low maintenance of coherence, and low isolation at low transmission power. Thus, there is a high need for photonic CSIC designs of FDIB systems that operate over wider bandwidths and at higher transmission powers. Here, a newfangled CSIC system based on a non-linear photonic loop and frequency down-conversion is proposed. It shows excellent CSIC suppression of greater than 61 dB, for a single frequency signal of interest (SOI) with maximum RF power of 13 dBm. Without frequency down-conversion, the system maintains an average cancellation depth of 62.541 dB for single frequency SOI. After frequency down conversion, the system maintains an average cancellation depth of 61.208 dB for narrow band SOI. The system attains 18% error vector magnitude at −20 dB RF output power, which confirms the comprehensive quality of the system.

Anti-Jamming Method and Implementation for GNSS Receiver Based on Array Antenna Rotation

Global navigation satellite system (GNSS) array antenna receivers are effective for suppressing wideband jamming. However, its anti-jamming performance decreases sharply when the number of wideband interference surpasses the number of array elements. Since a large number of jammers are often used in navigation countermeasures, it is crucial to keep array antenna receivers available in such conditions. Aiming at this issue, two main tasks were performed in this research and are presented in this paper: Firstly, the direction sensitivity of the sup-freedom anti-jamming performance is revealed and an anti-jamming method for array antenna receivers based on antenna rotation is proposed. Secondly, in order to determine the optimal rotation angle rapidly, a variable-step iteration algorithm based on gradient descent is proposed. Theoretical analysis and simulation show the effectiveness of the proposed anti-jamming method and the efficiency of the implementation algorithm. In a typical airborne scenario with a maximum azimuth difference of 90°, the anti-jamming ability of the proposed method improved by 21~26 dB and 5~10 dB for arrays adopting the PI (power inversion) and MVDR (minimum variance distortionless response) algorithms, respectively. The iterative efficiency improved by 78.35–99.63% in comparison with a traversal of 0.1° search resolution. The proposed method and algorithm are not limited to airborne scenarios and they might be influential to anti-jamming algorithms in the data domain.

Extension and Evaluation of SSC for Removing Wideband RFI in SLC SAR Images

Synthetic aperture radar (SAR), as a wideband radar system, is easily contaminated by radio frequency interference (RFI), which affects the imaging quality of SAR. The subband spectral cancellation (SSC) method and its modifications utilize the SAR single-look complex (SLC) image to realize RFI extraction and mitigation by subtracting between sub-images, which are robust and efficient for engineering applications. In the past, the traditional SSC was often applied to narrowband interference (NBI) mitigation. However, when it was used for wideband interference (WBI) mitigation, it would cause the mitigated image to lose much of its useful information. In contrast, this paper proposes an improved SSC method based on successive cancellation and data accumulation (SSC-SCDA) for WBI mitigation. First, the fast Fourier transform (FFT) is used to characterize the SAR SLC data in the frequency domain, and the average range spectrum algorithm is used to detect whether there are interference components in the SAR SLC data. Then, according to the carrier frequency and bandwidth of the RFI in the frequency domain, the subbands are divided, and a cancellation strategy is formulated. Finally, based on the successive cancellation and data accumulation technology, WBIs can be removed by using only a small percentage of the clean subbands. Based on the simulated experiments, the interference mitigation performance of the proposed method is analyzed when the interference-to-signal bandwidth ratio (ISBR) varies from 20% to 80% under different signal-to-interference-to-noise ratios (SINR). The experimental results based on WBI-contaminated European Space Agency (ESA) Sentinel-1A SAR SLC data demonstrate the effectiveness of the proposed method in WBI mitigation.

MIMO Radar Sparse Recovery Imaging with Wideband Interference Prediction

Multiple-input multiple-output (MIMO) radar three-dimensional (3D) imaging is widely applied in military and civil fields. However, MIMO is easily affected by wideband interference (WBI). To solve this problem, in this study, we propose a sparse recovery imaging method with WBI prediction based on the predictive recurrent neural network (PredRNN) and the tensor-based smooth L0 (TSL0) algorithm. Firstly, we extract the time-frequency (TF) feature of the historical measured WBI via the short-time Fourier transform (STFT) operation. In this way, we can use PredRNN to exploit the spatiotemporal correlation of the WBI in the TF domain to predict the TF feature of the WBI in the future. Then, we adaptively design the random sparse stepped frequency waveform by selecting non-overlapped frequencies with the WBI according to the predicted WBI TF feature. Finally, we apply the TSL0 algorithm to reconstruct the 3D high-resolution target image from the sparse signal cube. Simulation results show the high performance and robustness of the proposed imaging method in the presence of different WBIs.

Wideband interference mitigation for synthetic aperture radar based on the variational Bayesian method

Wideband interference (WBI) seriously detracts from synthetic aperture radar (SAR) imaging quality and hinders the subsequent interpretation of images. Meanwhile, the large bandwidth and complex modulation of WBI necessitates the development of mitigation algorithms with strong adaptability and robustness that are lacking in existing algorithms based on filtering and model analysis. The present work addresses this issue by proposing a WBI mitigation algorithm based on variational Bayesian inference (VBI). Firstly, the WBI-contaminated echo signal is identified in the time–frequency (TF) domain through an adaptive statistical detection method. Then, a low-rank matrix factorization is formulated according to the low-rank characteristics of the WBI and the Laplace distribution assumption of the target echo signal in the TF domain. Finally, the WBI component is accurately reconstructed using a mean-field VBI method, and then eliminated from the original SAR echo signal to recover the target echo signal. The effectiveness and robustness of the proposed WBI mitigation algorithm are demonstrated based on its application to simulated and measured SAR data.

Radio Frequency Interference Detection Using Nonnegative Matrix Factorization

This article proposes a new precorrelation interference detection technique based on the nonnegative matrix factorization (NMF) for global navigation satellite system (GNSS) signals. The proposed technique uses the NMF to extract the time and frequency properties of the received signal from its spectrogram. The estimated spectral shape is then compared with the spectrogram’s time slices by means of a similarity function to detect the presence of radio frequency interference (RFI). In the presence of RFI, the NMF estimated spectral shape tends to be well-defined, resulting in high similarity levels. In contrast, in the absence of RFI, the received signal is solely comprised of noise and GNSS signals resulting in a noise like spectral shape estimate, leading to considerably reduced similarity levels. The proposal exploits these different similarity levels to detect the presence of interference. Simulation results indicate that the proposed technique yields increased detection capability with low false alarm rate even in low jammer-to-noise ratio environments for both narrow and wideband interference sources without requiring fine tuning of parameters for specific RFI types. In addition, the proposal has reduced computational complexity, when compared with an existing statistical-based detector.

Wide-Band Interference Mitigation in GNSS Receivers Using Sub-Band Automatic Gain Control.

The performance of global navigation satellite system (GNSS) receivers is significantly affected by interference signals. For this reason, several research groups have proposed methods to mitigate the effect of different kinds of jammers. One effective method for wide-band interference mitigation (IM) is the high-rate DFT-based data manipulator (HDDM) pulse blanker (PB). It provides good performance to pulsed and frequency sparse interference. However, it and many other methods have poor performance against wide-band noise signals, which are not frequency-sparse. This article proposes to include automatic gain control (AGC) in the HDDM structure to attenuate the signal instead of removing it: the HDDM-AGC. It overcomes the wide-band noise limitation for IM at the cost of limiting mitigation capability to other signals. Previous studies with this approach were limited to only measuring the carrier-to-noise density ratio () performance of tracking, but this article extends the analysis to include the impact of the HDDM-AGC algorithm on the position, velocity, and time (PVT) solution. It allows an end-to-end evaluation and impact assessment of mitigation to a GNSS receiver. This study compares two commercial receivers: one high-end and one low-cost, with and without HDDM IM against laboratory-generated interference signals. The results show that the HDDM-AGC provides a PVT availability and precision comparable to high-end commercial receivers with integrated mitigation for most interference types. For pulse interferences, its performance is superior. Further, it is shown that degradation is minimized against wide-band noise interferences. Regarding low-cost receivers, the PVT availability can be increased up to 40% by applying an external HDDM-AGC.

Design of Dual-Band Notched UWB Antenna Loaded with Split Ring Resonators for Wide Band Rejection

ABSTRACT Nowadays, the design of a miniaturised ultra-wideband (UWB) antenna with wide dual band-notched characteristics gained widespread demand in wireless communications to reduce interference. The design of a planar CPW-fed circular UWB antenna loaded with split ring resonators and stubs is presented to eliminate two frequency bands. Two symmetrical circular split ring resonators are etched below the CPW feed at the backside of a circular UWB monopole antenna to suppress 3.61 GHz–5.57 GHz (sub-6 GHz band) wideband interference, whereas the 7.06 GHz–8.79 GHz (X-band uplinks and downlinks) band is suppressed by loading two L-shaped stubs. Slots are also made on the patch and ground to enhance impedance matching at a lower resonance frequency. The proposed notch band antenna has a compact size of 38 × 32 × 1.6 mm3 and has the highest gain of 5.75 dB at a frequency of 9 GHz. The parametric analysis has been performed to obtain optimised dimensions for better performance. The designed antenna is simulated, prototyped and tested to validate the antenna design.