Radar Interference Research Articles

Method for dealing with non-stationary natural and simulating interference in intellectual surveillance radars

The article discusses a method for dealing with non-stationary natural and simulating interference in intelligent surveillance radars. When creating simulating marks, the introduction of amplitude modulation into the relayed radar sounding signal is used. As a result of the analysis, it was possible to find out that in the imitating noise, in this case, the so-called "intelligent" fluctuations of the burst structure of false marks appear, which differ from the fluctuations of the packs of real marks and can be easily detected by a human operator. The method is based on the definition of semantic components at the stage of formation and analysis of a symbolic model of amplitude fluctuations of a burst of signals from non-stationary natural and simulating interference and from real moving objects. In this case, the semantic features of amplitude fluctuations are determined by solving predicate equations for transforming these fluctuations into symbolic images of noise marks and real mobile aircraft. As a result of semantic analysis of the amplitude fluctuations of the burst in the time domain, classification distinctive features of fluctuations in the burst of signals from natural imitating noise and air objects were obtained. The semantic components of the decision-making algorithm are investigated, which are similar to the decision-making algorithms by a human operator. Process knowledge of transforming radar signals into symbolic images of amplitude fluctuations of a burst in the time domain is formalized. The formalization of the processing of symbolic images includes a system of predicate equations, by solving which the types of amplitude fluctuations of the burst are identified. Based on the results of experimental data, the transformations of real radar signals into symbolic images of burst fluctuations were carried out on the basis of the algebra of finite predicates. The authors also managed to propose these transformations to be used as the basis of an effective toolkit for obtaining classification distinctive features of packet fluctuations from interference and from aircraft.

Synchronization-Free RadChat for Automotive Radar Interference Mitigation

Automotive radar interference mitigation is expected to be inherent in all future ADAS and AD vehicles. Joint radar communications is a candidate technology for removing this interference by coordinating radar sensing through communication. Coordination of radars requires strict time synchronization among vehicles, and our formerly proposed protocol (RadChat) achieves this by a precise absolute time, provided by GPS clocks of vehicles. However, interference might appear if synchronization among vehicles is lost in case GPS is spoofed, satellites are blocked over short intervals, or GPS is restarted/updated. Here we present a synchronization-free version of RadChat (Sync-free RadChat), which relies on using the relative time for radar coordination, eliminating the dependency on the absolute time provided by GPS. Simulation results obtained for various use cases show that Sync-free RadChat is able to mitigate interference without degrading the radar performance.

Interference Analysis for mmWave Automotive Radar Considering Blockage Effect.

Due to the increasing number of vehicles equipped with millimeter wave (mmWave) radars, interference among automotive radars is becoming a major issue. This paper explores the automotive radar interference in both two-lane and multi-lane scenarios using stochastic geometry. We derive closed-form expressions for mean and variance of interference power considering directional antenna with constant and Gaussian decaying gains. In view of the sensitivity of mmWave radar signals to the blockages, we propose a blockage model including partially and completely blocking, and then calculate the effective number of the interferers. By means of modeling randomness for interferers and blockages as Poisson point process, we characterize the statistics of radar interference under different conditions. We further utilize the interference characterization to estimate the successful ranging probability of automotive radars. These theoretical analyses are verified by using Monte Carlo simulations. The results show that the increasing interfering density and ranging distance largely degrade the radar detection performance, whereas the interference levels decrease as blockage intensity increases.

Joint resource allocation and power control for radar interference mitigation in multi-UAV networks

Joint resource allocation and power control for radar interference mitigation in multi-UAV networks

Phenomenology of automotive radar interference

Mutual interference in automotive radar is expected to become a major issue owing to the rapid increase in the number of vehicles on the road equipped with radar. The phenomenology of interference in frequency modulated continuous wave radar is presented. Interference is empirically analysed at every signal processing stage in the victim radar by means of experimentally verified simulation modelling. Knowledge of how interference manifests in different domains provides a useful tool to develop algorithms for interference detection, mitigation and/or avoidance. The receiver's filter response is analysed to minimise the interference duration and increase the effectiveness of time-domain mitigation techniques. A innovative method of interference parameter extraction by using spectrograms is also introduced.

전파 간섭 환경 모의 방법 및 CFAR 알고리즘에 따른 레이다 성능 변화에 관한 연구

In radar operat양한 외부 원인에 의해 탐지 성능이 저하될 수 있다. 저하 원인으로는 대기 및 지형에 의한 손실뿐만 아니라, 간섭, 타 표적 등이 있다. 국내 운용 중인 레이ions, the detection performance is reduced owing to various external factors. These factors include interference and other targets, as well as losses from the atmosphere and terrain. Because of its geomorphic characteristics, radar operating in Korea is affected by interference, and its performance is degraded. This paper describes the simulation of the environment of near-radar interference and multiple targets. The modeling and simulation (M&S) tool was developed to predict and prevent the degradation in radar performance in advance. We validated existing constant false alarm rate (CFAR) detection algorithms by generating signals through the M&S tool and proposed a new CFAR algorithm to enhance the radar performance. Consequently, radar performance is enhanced by the new CFAR algorithm in radar interference and multiple target environments.

FMCW Radar Network: Multiple Access and Interference Mitigation

With the increasing proliferation of radars on vehicles, interference among vehicular radars is becoming a serious issue. In this work, we consider a frequency modulated continuous wave (FMCW) radar network with coherent radar interference where all radars adopt the same chirp slopes. Four asynchronous non-cooperative media access control (MAC) protocols are used for mutual radar interference mitigation. We propose two cross-layer performance metrics - multiple access capacity and probability of target misdetection to quantify the network performance under each MAC protocol. Based on our analysis and extensive simulations, we find the pure random access achieves a very poor trade-off between multiple access capacity and probability of target misdetection. However, such a trade-off can be significantly improved by frequency hopping and phase coding. This shows that proper MAC protocols can achieve very good performance even without synchronization and coordination. We describe new insights behind such gains that can be valuable for FMCW radar MAC design.

Optimized Precoders for Massive MIMO OFDM Dual Radar-Communication Systems

This paper considers the optimization of a dual-functional radar and communication (RadCom) system with the objective is to maximize its sum-rate (SR) and energy-efficiency (EE) while satisfying certain radar target detection and data rate per user requirements. To this end, novel RadCom precoder schemes that can exploit downlink radar interference are devised for massive multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. First, the communication capacity and radar detection performance metrics of these schemes are analytically evaluated. Then, using the derived results, optimum beam power allocation schemes are deduced to maximize SR and EE with modest computational complexity. The validity of the analytical results is confirmed via matching computer simulations. It is also shown that, compared to benchmark techniques, the devised precoders can achieve substantial improvements in terms of both SR and EE.

Interference‐to‐noise ratio estimation in long‐term evolution passive radar based on cyclic auto‐correlation

This letter considers the interference-to-noise ratio (INR) estimation problem in long-term evolution (LTE)-based passive bistatic radar. The INR is of great importance in the evaluation of interference level, the prediction of the target detection capability and the target parameter estimation. Traditional passive radar uses the cross-correlation function between the reference and surveillance signals to estimate the INR. This is not applicable to LTE-based passive radar due to the uncorrelation between the interference and reference signals in LTE-based passive radar. In this letter, we propose a cyclic auto-correlation method to estimate the INR. Simulation results show the effectiveness of the proposed method.

DOA Estimation Method Based on EMD and MUSIC for Mutual Interference in FMCW Automotive Radars

Mutual interference in automotive radar will reduce the signal-to-noise ratio (SNR) of the received signals. It is difficult to accurately distinguish the signal subspace and the noise subspace for low SNR signals, which will degrade the direction of arrival (DOA) estimation performance of the multiple signal classification (MUSIC) algorithm. To solve this problem, this letter proposes a DOA estimation method for automotive radar based on empirical mode decomposition (EMD) and MUSIC in the case of interference. In our method, the interference signals are suppressed before the DOA estimation. The received signals of the receiving antennas affected by the interference are decomposed into several components by using EMD, and then the interference signals in the interference components are suppressed. Finally, all the received signals are used for the DOA estimation. The results of the simulation and field experiments show that the proposed method can obtain an accurate DOA estimation when the received signals contain the interference signals, and the performance of the proposed method is better than the existing DOA estimation algorithms.

Snow Layer Detection by Pattern Matching in a Multipath Radar Interference Scenario

ABSTRACT Snowpack in sloped mountain terrain may present stratification in which layers of snow accumulate over a certain period. The loosely adhering layers in snowpack may exhibit a severe avalanche risk, and detecting such stratification phenomena is key to avalanche detection. The danger of manual, in-situ sampling calls for investigation of alternative approaches, including the use of in-situ radars. Considering a buried radar sensor, this manuscript analyses the impact of multipath phenomena on the results of the sensing operation. Multiple bounces in snow layers may degrade the received signal and corrupt the estimation results. Multipath phenomena are well known and analysed in communication systems, but snow layering measurement is a different problem, with little previous research done on related multipath phenomena. This paper analyses the problem with a multi-receiver radar architecture, investigating the impact of multi-path effects from layered snow on measurements carried out by a multi-static radar of Frequency-Modulated Continuous Wave (FMCW) type. A few simplifying assumptions are formulated, in order to make the problem manageable, and a possible approach for solving the related issues is proposed, using a robust algorithm based on pattern matching to detect snow layering in such a challenging environment. Results obtained from various simulations carried out with realistic environmental and geometrical parameters appear to support the effectiveness of the proposed method. Results show that with 3 metres of snow thickness, the probability of successfully detecting the correct numbers of layers exceeds 80%.

Estimating the Magnitude and Phase of Automotive Radar Signals Under Multiple Interference Sources With Fully Convolutional Networks

Radar sensors are gradually becoming a wide-spread equipment for road vehicles, playing a crucial role in autonomous driving and road safety. The broad adoption of radar sensors increases the chance of interference among sensors from different vehicles, generating corrupted range profiles and range-Doppler maps. In order to extract distance and velocity of multiple targets from range-Doppler maps, the interference affecting each range profile needs to be mitigated. In this paper, we propose a fully convolutional neural network for automotive radar interference mitigation. In order to train our network in a real-world scenario, we introduce a new data set of realistic automotive radar signals with multiple targets and multiple interferers. To our knowledge, we are the first to apply weight pruning in the automotive radar domain, obtaining superior results compared to the widely-used dropout. While most previous works successfully estimated the magnitude of automotive radar signals, we propose a deep learning model that can accurately estimate the phase. For instance, our novel approach reduces the phase estimation error with respect to the commonly-adopted zeroing technique by half, from 12.55 degrees to 6.58 degrees. Considering the lack of databases for automotive radar interference mitigation, we release as open source our large-scale data set that closely replicates the real-world automotive scenario for multiple interference cases, allowing others to objectively compare their future work in this domain. Our data set is available for download at: http://github.com/ristea/arim-v2.

Synthetic Aperture Radar Interference Based on Scene Fusion and Active Cancellation

Echo cancellation is used for eliminating echo signals by signal modulation in the frequency domain and time domain. However, it depends on the high accuracy of parameter estimation. In addition, it introduces an incompatible black mark in the synthetic aperture radar (SAR) image, which will be easily detected and inevitably degrades the deception performance. To address this problem, this article proposed a compound interference method that combines echo cancellation and deception jamming. In order to fuse the deception scene with the surrounding scene, the optimal deception template is generated by using the scene around the target of interest (TOI), and the deception template is used to modulate the coefficient of the original signal to generate the deception signal. Then, the deception signal is sent to the SAR platform together with the cancellation signal, which is generated by an active source. After the SAR process, the incompatible black mark in the image is replaced by a template with high similarity of surrounding scene, which effectively improves the deception performance. The proposed method can be used to cover the higher scattering characteristic of the TOI with the lower scattering characteristic of the deception template. Simulation results are provided and analyzed to validate the universality and the performance superiority of the proposed method.

ПОМЕХОЗАЩИТА РАДИОЛОКАТОРА С СИНТЕЗИРОВАННОЙ АПЕРТУРОЙ КОСМИЧЕСКОГО БАЗИРОВАНИЯ НА ОСНОВЕ ЦИФРОВОЙ АФАР

The article deals with General questions about the definition of parameters, the calculation of which is necessary for choosing a method for organizing interference protection of a synthetic aperture radar (RSA), analyzes and notes the features of the construction and functioning of the RSA. The features of noise protection on radars of various companies are considered: COSMO-SkyMed -4 (Constellation of Small Satellites for Mediterranean basin Observation) X-band (made in Italy), TerraSAR-X/TanDEM-X (Germany), “Kasatka-R” (Russia). The subject of the study is a synthetic aperture radar, which is a coherent radar system that uses the flight path of the platform to simulate extremely large obstacles or objects electronically, and which generates high-resolution remote sensing images. Over time, individual transmit / receive cycles are completed, and data for each cycle is stored electronically. When the signal processing uses the amplitude and phase of the received signals in successive pulses from elements of a synthetic aperture. After a set number of cycles, the stored data is re-combined (taking into account the Doppler Effect inherent in different transmitters for the target geometry in each subsequent cycle) to create a high-resolution image of the terrain over which the flight is performed. The analysis of the RSA parameters that affect the radar noise immunity is performed. Objective: to analyze the interference protection of a space-based synthetic aperture radar based on digital AFAR. It is necessary to identify the type of interference that has an effective interfering effect on the protected object and determine their degree of impact depending on the parameters of the interference source. Noise immunity refers to the ability of a radio system to resist interference. Radars from various manufacturers have differential methods for improving noise immunity. The calculation of the radar range is given for the purpose of detailed consideration of the parameters of the maximum range of radio interference. The paper focuses on the main radar interference and options for improving noise immunity for this type of radar. Methodology: analysis of existing literature, analysis of technical characteristics of radars from various manufacturers, modeling of possible types of interference, deduction, induction, comparison of used radars with synthesized aperture, formalization.

A Dual-Functional Massive MIMO OFDM Communication and Radar Transmitter Architecture

In this study, a dual-functional radar and communication (RadCom) system architecture is proposed for application at base-stations (BSs), or access points (APs), for simultaneously communicating with multiple user equipments (UEs) and sensing the environment. Specifically, massive multiple-input multiple-output (mMIMO) communication and orthogonal frequency-division multiplexing (OFDM)-based MIMO radar are considered with the objective to jointly utilize channel diversity and interference. The BS consists of a mMIMO antenna array, and radar transmit and receive antennas. Employing OFDM waveforms for the radar allows the BS to perform channel state information (CSI) estimation for the mMIMO and radar antennas simultaneously. The acquired CSI is then exploited to predict the radar signals received by the UEs. While the radar transmits an OFDM waveform for detecting possible targets in range, the communication system beamforms to the UEs by taking into account the predicted radar interference. To further enhance the capacity of the communication system, an optimum radar waveform is designed. Moreover, the network capacity is mathematically analyzed and verified by simulations. The results show that the proposed RadCom can achieve higher capacity than conventional mMIMO systems by utilizing the radar interference while simultaneously detecting targets.

Robust Interference Cancellation for Vehicular Communication and Radar Coexistence

Spectrum sharing of wireless vehicle-to-vehicle (V2V) communication and automotive radar in intelligent transportation systems (ITS) can provide higher spectrum utilization efficiency. However, spectrum sharing between two systems might bring severe interference, which needs to be well solved. To address the communication-radar spectrum sharing (CRSS) and inter-system interference issue, we first model the radar interference estimation as an off-grid compressed sensing problem. Then, we propose an interference cancellation algorithm based on the atomic norm (AN) minimization theory. Simulation results show that the proposed algorithm facilitates the coexistence between radar and communication and improves the V2V communication performance efficiently in the presence of automotive radar interference.

Study on the Early Warning Methods of Dynamic Landslides of Large Abandoned Rockfill Slopes

The excavation of large-scale underground projects produces a large amount of rubble waste material that is temporarily deposited near the project site, which forms a large-scale waste rockfill artificial slope. The slope has a granular structure, thus, during excavation and trans-shipment, surface shallow landslides may frequently occur. Existing contact monitoring methods such as buried sensors and GPS (Global Position System) are difficult to apply to the monitoring of rockfill landslides. Therefore, there are no appropriate early warning methods for waste rockfill slope landslides during dynamic transfer. Here, we used ground-based interferometric synthetic aperture radar to monitor the deformation of a rockfill slope during the excavation and transfer processes as a proposed method for the early warning against landslides on rockfill slopes during dynamic construction based on the radar interference measurement results. Through data cleaning and data interpolation, the line of equal displacement was generated, and the cross-sectional area of the equal displacement bodies of landslides was calculated. In addition, we established a four-level early warning grading standard, with the rate of change of the cross-sectional area of the equal displacement body as the early warning index, and realized real-time dynamic early warning of waste rockfill landslides during excavation and transportation. Finally, five landslide examples were used to verify the proposed warning method. The results show that the warning method can make an early warning 8–14 min before the occurrence of landslide, which can effectively avoid the appearance of catastrophic events.

Augmenting the signal processing–based mitigation techniques for removing wind turbine and radar interference

The interference between wind turbine generators and radar is now being considered as one of the major deterrents towards seeking clearance for new wind energy project. The windfarm developers have to seek clearance from Civil Air Traffic Control and Defence Department certifying that the windfarms will not create interference with radars. The tower of wind turbine generator along with blades presents a large radar cross section to radars, thus creating static clutter; moreover, rotation of wind turbine generator blades creates Doppler ambiguities which confuse radar operators. Many radar designers have proposed mitigation techniques to overcome this issue; however, each technique has its own limitation. The study takes a two-pronged approach to address the issue of wind turbine generator static clutter due to tower and blades and the resolution of Doppler ambiguities through signal processing–based mitigation techniques. In addition, the study also suggests the use of micro-Doppler techniques for signature identification of wind turbine generator blades for eliminating their effect during the radar signal processing. The article presents a step-by-step mitigation technique to resolve the wind turbine generator and radar interference issue.

Elimination of Interference in Through-Wall Radars

The fight against terrorist threats is highly relevant in the modern world. When developing devices for countering terrorism, their reliability and stability are very important. One such device is a device for detecting people behind optically opaque obstacles, which can detect the movement of people behind a wall and determine their number. However, the influence of interference effects that occur when summing up the reflected signals arriving by different propagation paths and, accordingly, having different phase shifts, leads to the fact that the observed image of the target can flicker and even disappear from the device screen for a considerable time, which is unacceptable in combat conditions. This article discusses various ways to eliminate interference, and on the basis of theoretical calculations, the most effective and cost-effective ways to eliminate the influence of interference effects in devices for detecting people behind optically opaque barriers are proposed. The obtained theoretical conclusions are confirmed experimentally.

Semi-Blind Post-Equalizer SINR Estimation and Dual CSI Feedback for Radar-Cellular Coexistence

Current cellular systems use pilot-aided statistical-channel state information (S-CSI) estimation and limited feedback schemes to aid in link adaptation and scheduling decisions. However, in the presence of pulsed radar signals, pilot-aided S-CSI is inaccurate since interference statistics on pilot and non-pilot resources can be different. Moreover, the channel will be bimodal as a result of the periodic interference. In this paper, we propose a max-min heuristic to estimate the post-equalizer SINR in the case of non-pilot pulsed radar interference, and characterize its distribution as a function of noise variance and interference power. We observe that the proposed heuristic incurs low computational complexity, and is robust beyond a certain SINR threshold for different modulation schemes, especially for QPSK. This enables us to develop a comprehensive semi-blind framework to estimate the wideband SINR metric that is commonly used for S-CSI quantization in 3GPP Long-Term Evolution (LTE) and New Radio (NR) networks. Finally, we propose dual CSI feedback for practical radar-cellular spectrum sharing, to enable accurate CSI acquisition in the bimodal channel. We demonstrate significant improvements in throughput, block error rate and retransmission-induced latency for LTE-Advanced Pro when compared to conventional pilot-aided S-CSI estimation and limited feedback schemes.