Jamming Suppression Research Articles

Radar Anti-Jamming Decision-Making Method Based on DDPG-MADDPG Algorithm

In the face of smart and varied jamming, intelligent radar anti-jamming technologies are urgently needed. Due to the variety of radar electronic counter-countermeasures (ECCMs), it is necessary to efficiently optimize ECCMs in the high-dimensional knowledge base to ensure that the radar achieves the optimal anti-jamming effect. Therefore, an intelligent radar anti-jamming decision-making method based on the deep deterministic policy gradient (DDPG) and the multi-agent deep deterministic policy gradient (MADDPG) (DDPG-MADDPG) algorithm is proposed. Firstly, by establishing a typical working scenario of radar and jamming, we designed the intelligent radar anti-jamming decision-making model, and the anti-jamming decision-making process was formulated. Then, aiming at different jamming modes, we designed the anti-jamming improvement factor and the correlation matrix of jamming and ECCM. They were used to evaluate the jamming suppression performance of ECCMs and to provide feedback for the decision-making algorithm. The decision-making constraints and four different decision-making objectives were designed to verify the performance of the decision-making algorithm. Finally, we designed a DDPG-MADDPG algorithm to generate the anti-jamming strategy. The simulation results showed that the proposed method has excellent robustness and generalization performance. At the same time, it has a shorter convergence time and higher anti-jamming decision making accuracy.

Monopulse Parameter Estimation for FDA-MIMO Radar under Mainlobe Deception Jamming

Multiple input multiple output with frequency diversity array (FDA-MIMO) radar has unique advantages in mainlobe deception jamming suppression and target location. However, if the training sample contains the target signal, it will lead to poor jamming suppression performance and large target measurement error. To deal with the problem, a method of coarse target location in the time domain is proposed based on the cumulative sampling analysis. Taking full advantages of the strongest correlation characteristic between the expected steering vector and the true target, the feature vector and feature value corresponding to the true target are found after feature decomposition. The time domain location of the target is roughly estimated during the cumulative sampling analysis from near to far. Then, a pure jamming training sample can be obtained by avoiding the location. Noise subspace projection algorithm is used to measure the angle and range of the target while suppressing mainlobe jamming. The simulation results show that the proposed method can roughly estimate the target location in the time domain when the mainlobe deception jamming completely covers the target. Compared with conventional methods, the performance of jamming suppression and target localization error are closer to the performance of ideal sampling.

Mainlobe Jamming Suppression With Space–Time Multichannel via Blind Source Separation

Mainlobe Jamming Suppression With Space–Time Multichannel via Blind Source Separation

Analysis of Characteristics and Suppression Methods for Self-Defense Smart Noise Jamming

Self-defense smart noise jamming can automatically aim a signal frequency and obtain antenna gain and matching filtering processing gain, posing a huge threat to the normal performance of radar. In response to this situation, this article conducts an in-depth analysis of two typical smart noise jamming methods: noise convolution jamming methods and noise product jamming methods. The distribution characteristics of the two jamming methods in both time–frequency dimensions and their internal time–frequency relationships are analyzed. Based on this, a self-defense smart noise jamming suppression method based on pulse frequency stepping is proposed. This method obtains the true distance information of the target based on the phase difference caused by frequency stepping between adjacent pulses and uses this information to construct a filter to filter the radar echo, achieving jamming suppression. Simulation experiments have verified the effectiveness of this method.

Overview of Jamming Technology for Satellite Navigation

The Global Navigation Satellite System (GNSS) has been applied to all aspects of social livelihood and military applications and has become an important part of national infrastructure construction. However, due to the vulnerability of GNSS, satellite navigation jamming technology can pose a serious threat to GNSS security applications, and this has become a research hotspot in the field of navigation countermeasures. In this paper, satellite navigation jamming technologies are divided into suppression jamming and deception jamming, and the research status of satellite navigation suppression jamming and deception jamming technologies are sorted by three aspects: jamming technology classification, jamming efficiency evaluation, and jamming source deployment. Finally, the future development trend of satellite navigation jamming technology is summarized.

DRFM Repeater Jamming Suppression Method Based on Joint Range-Angle Sparse Recovery and Beamforming for Distributed Array Radar

Distributed array radar achieves high angular resolution and measurement accuracy, which could provide a solution to suppress digital radio frequency memory (DRFM) repeater jamming. However, owing to the large aperture of a distributed radar, the far-field plane wave assumption is no longer satisfied. Consequently, traditional adaptive beamforming methods cannot work effectively due to mismatched steering vectors. To address this issue, a DRFM repeater jamming suppression method based on joint range-angle sparse recovery and beamforming for distributed array radar is proposed in this paper. First, the steering vectors of the distributed array are reconstructed according to the spherical wave model under near-field conditions. Then, a joint range-angle sparse dictionary is generated using reconstructed steering vectors, and the range-angle position of jamming is estimated using the weighted L1-norm singular value decomposition (W-L1-SVD) algorithm. Finally, beamforming with joint range-angle nulling is implemented based on the linear constrained minimum variance (LCMV) algorithm for jamming suppression. The performance and effectiveness of proposed method is validated by simulations and experiments on an actual ground-based distributed array radar system.

An Anti-Jamming Method of UWB Ranging Sensor Based on Equivalent Sampling and Coupled Chaotic Oscillator

Electromagnetic threats the carrier-free ultrawideband (UWB) sensors face cannot be ignored. However, it is difficult to tackle various jamming signals well by using one type of jamming suppression algorithm with the development of jamming technology. To solve this issue, an anti-jamming model based on equivalent sampling and coupled chaotic oscillator is proposed in this letter. First, the echo data is collected by equivalent sampling, which can destroy the jamming features in the time domain. Therefore, it does not require extra attention to the initial jamming form during the signal process. Then an improved coupled chaotic model is used to detect the weak impulses after sampling. The advantage is that it reduces the sample rate and can destroy the original features of the jamming. Higher precision and outstanding robustness are proven according to our experiments.

Joint Polarization-Space-Time Processing for Mainlobe Jamming via CP Decomposition

This paper deals with the problem of mainlobe jamming suppression for polarization sensitive phased-array radar system via a joint polarization-space-time processing method resorting to tensor decomposition. Firstly, a radar model accounting for one target and multiple mainlobe jammers in the far field is considered, which is equipped with a polarized transmitted antenna and a uniform linear dual-polarization receiving array. Then, exploiting the polarization-space-time characteristics, tensor CANDECOMP/PARAFAC (CP) decomposition is introduced to recast the received signal as a third order tensor consisting of three factor matrices. Further, the target echo and the jamming signal can be obtained via minimizing the Frobenius norm of the approximation error between the tensor and the outer product of the factor matrices. Finally, the effectiveness of the proposed method by numerical simulation is verified, showing its capability to combat various types of mainlobe jamming as well as their compound forms compared with the art competing method.

Suppression of Mainlobe Jammers with Quadratic Element Pulse Coding in MIMO Radar

The problem of suppressing mainlobe deceptive jammers, which spoof radar systems by generating multiple false targets, has attracted widespread attention. To tackle this problem, in this paper, the multiple-input multiple-output (MIMO) radar system was utilized by applying a quadratic element phase code (QEPC) to the transmitted pulses of different elements. In the receiver, by utilizing the spatial frequency and Doppler frequency offset generated after decoding, the jammers were equivalently distributed in the sidelobes of the joint Doppler-transmit-receive domain and were distinguishable from the true target. Then, further spatial frequency compensation and Doppler compensation were performed to align the true target to the zero point in the transmit spatial and Doppler domains. Moreover, by designing appropriate coding coefficients, the jammers were suppressed by data-independent Doppler-transmit-receive three-dimensional beamforming. However, the beamforming performance was sensitive to angular estimation mismatches, resulting in performance degradation of jammer suppression. To this end, a center-boundary null-broadening control (CBNBC) approach was used to broaden the nulls in the equivalent beampattern by generating multiple artificial jammers with preset powers around the nulls. Thus, the false targets (FTs) with deviations were sufficiently suppressed in the broadened notches. Numerical simulations and theoretical analysis demonstrated the performance of the developed jammer suppression method.

SMSP Mainlobe Jamming Suppression with FDA-MIMO Radar Based on FastICA Algorithm

In the electronic warfare environment, the performance of ground-based radar target search is seriously degraded due to the existence of smeared spectrum (SMSP) jamming. SMSP jamming is generated by the self-defense jammer on the platform, playing an important role in electronic warfare, making traditional radars based on linear frequency modulation (LFM) waveforms face great challenges in searching for targets. To solve this problem, an SMSP mainlobe jamming suppression method based on a frequency diverse array (FDA) multiple-input multiple-output (MIMO) radar is proposed. The proposed method first uses the maximum entropy algorithm to estimate the target angle and eliminate the interference signals from the sidelobe. Then, the range-angle dependence of the FDA-MIMO radar signal is utilized, and the blind source separation (BSS) algorithm is used to separate the mainlobe interference signal and the target signal, avoiding the impact of mainlobe interference on target search. The simulation verifies that the target echo signal can be effectively separated, the similarity coefficient can reach more than 90% and the detection probability of the radar is significantly enhanced at a low signal-to-noise ratio.

An Anti-Intermittent Sampling Jamming Technique Utilizing the OTSU Algorithm of Random Orthogonal Sub-Pulses

The utilization of intermittent sampling jamming can engender a lofty verisimilitude false target cluster that exhibits coherence with the transmitted signal. Such an assemblage bears the hallmarks of both suppression jamming and deceitful jamming, capable of inflicting substantial impairment upon the radar, potentially leading to its profound incapacitation. Henceforth, the precise discernment of the target and various forms of intermittent sampling jamming emerges as a novel endeavor. In response to this predicament, this paper posits a pulsed radar waveform featuring intra-pulse random orthogonal frequency modulation (FM) and inter-pulse phase coherence. This innovative approach not only presents formidable challenges for the jammer in acquiring radar waveform parameters, but also bolsters the radar’s low probability of intercept (LPI), while maintaining the phase coherence of sub-pulses between pulses. Furthermore, based on this waveform, the characteristics of the intermittent sampling jamming signal and its differences from the target echo signal are analyzed in the time domain, frequency domain, time-frequency domain, and pulse compression domain. Building upon these findings, this paper proposes the sub-division algorithms for typical types of intermittent sampling jamming under this waveform: the full-pulses multi-level maximum inter-class variance and sub-pulses multi-level maximum inter-class variance anti-intermittent sampling jamming algorithms. Simulation analysis demonstrates that this waveform and the anti-jamming algorithms can accurately identify and effectively counteract different types of intermittent sampling jamming in typical scenarios.

Research on Radar Jamming for Detection Performance

Radar jamming plays an important role in modern military affairs. The current radar jamming technology is mainly divided into two parts: suppressive jamming and deceptive jamming. This paper applies the jamming effect of multi-false target jamming in deceptive jamming and noise AM jamming, noise FM jamming, and noise PM jamming in suppressive jamming to the radar’s echo signal. Besides, this paper studies their influences from the aspect of target detection results through MTI and the influence of these jamming methods on the radar detection probability through CFAR. The experimental results can directly show the influence of interference measures on detection results and detection probability, and prove the effectiveness of these interference methods.

Phase response similarity based waveform design for FDA-MIMO radar

The transmit degrees-of-freedom (DOFs) of multiple-input multiple-output (MIMO) radar depend on the orthogonality of transmit waveforms. However, ideal orthogonal waveforms are unrealistic because existing waveforms cannot avoid influence of cross-correlation sidelobes. In this paper, a waveform design algorithm is proposed by introducing the phase response similarity (PRS) concept. The PRS enables consistency of spatial steering vectors for different time instance. In this case, the spatial power spectrum of signal in the transmit spatial domain will be well-focused, which is the desired property for the jammer suppression application. Moreover, we further explore the combination of correlation amplitude and phase response as the objective function, which improves the anti-jammer performance. Simulation examples are conducted to verify the effectiveness and performance gains of the proposed method.

Interrupted-sampling repeater jamming suppression based on iterative decomposition

Interrupted-sampling repeater jamming (ISRJ) is a type of intra-pulse coherent interference. The classical ISRJ model has constraints on forwarding strategies. We generalize the classical ISRJ model. The entire ISRJ is viewed as the sum of multiple sub-interference signals corresponding to different sampling sequences. Based on the general model, an iterative decomposition method is proposed. The received signal is decomposed into several sub-signals. In each iteration, the processes of extraction, estimation, smoothing, identification and cancellation are finished. First, the signal sample corresponding to the current target is extracted. Then we use the amplitude information of the main peak to establish the objective function. The sample points that contribute to the amplitude are selected during optimization and the corresponding sampling sequence can be estimated. Finally, the attribution of the current target is determined by the characteristic value, and the corresponding sub-signal is eliminated from the original echo. The processes are repeated until all sub-signals are eliminated. Simulation experiments show that the proposed method has excellent recognition and suppression performance for direct forwarding, repeated forwarding, and periodic forwarding ISRJ.

Energy function‐guided histogram analysis for interrupted sampling repeater jamming suppression

AbstractInterrupted sampling repeater jamming (ISRJ) is a novel intra‐pulse coherent jamming based on digital radio frequency memory (DRFM). By repeatedly sampling and retransmitting the radar transmitting signal fragments, a series of false targets can be formed after pulse compression (PC), posing a severe threat to modern radar systems. Inspired by the energy function method and histogram analysis in image processing, an adaptive time‐frequency (TF) filtering method is proposed in this letter. The ISRJ‐contaminated regions can be accurately determined in the TF image after histogram analysis and subsequent energy accumulation. Guided by the energy function, the proposed method can automatically adjust the intensity threshold in TF image histogram analysis and therefore reveals better robustness compared with other competing methods. Simulations have verified the effectiveness and robustness of the proposed method against ISRJ under various circumstances.

DRFM-Based Repeater Jamming Reconstruction and Cancellation Method with Accurate Edge Detection

Digital radio frequency memory (DRFM) based repeater jamming can create false targets, which can lead to a loss of situational awareness, misidentification of targets, and decreased overall performance of the radar system. Traditional jamming suppression methods do not give due importance to the accurate estimation of the jamming edge, resulting in jamming residual and poor anti-jamming performance. To tackle this issue, this paper explores the reason and impact of inaccurate jamming edge estimation and proposes a DRFM-based repeater jamming reconstruction and cancellation method with accurate edge detection. In the proposed method, firstly, multiple jamming parameters are obtained by computing the short-time fractional Fourier transformation (STFRFT) spectrogram of the received signal. To avoid jamming residue, the proposed method estimates the accurate jamming edges by the joint use of the difference of box (DOB) filters and time domain deconvolution (TDDC) curves. Numerical simulations and experiments are conducted to evaluate the algorithm’s effectiveness in countering smeared spectrum (SMSP) and interrupted sampling repeater jamming (ISRJ). The results demonstrate its superior jamming reconstruction and suppression performance than other methods.

A Self-Supervised Method Based on CV-MUNet++ for Active Jamming Suppression in SAR Images

Synthetic aperture radar (SAR) system is susceptible to electromagnetic jamming during imaging, which seriously affects the subsequent interpretation of SAR images. Aiming at the problem of active suppressive jamming, this paper proposes a suppression method of SAR suppressive jamming based on self-supervised complex-valued deep learning, which consists of a novel complex-valued jamming suppression network CV-MUNet++ and a self-supervised training strategy. CV-MUNet++ could fully use the amplitude and phase information of complex-valued SAR images. The network’s weights, activation functions, and convolution operations are designed for complex domain processing. The different information representations of target and jamming in amplitude and phase in SAR images are mined to achieve jamming suppression. The self-supervised training strategy is proposed to solve the problem of relying heavily on manually labeled samples in the traditional network training process and is suitable for application scenarios where ground truth is difficult to obtain under complex jamming. The experimental results show that the proposed method could effectively suppress the active jamming of complex backgrounds and has the ability to self-supervised intelligent jamming suppression.

Range-angle-dependent beamforming for FDA radar with Hamming interelement spacing and sinusoidal multicarrier approach

By employing a tiny frequency offset across the array elements, a frequency diverse array (FDA) produces a beampattern with the property of being range-angle-dependent. However, the beampattern of a traditional FDA has many maxima at undesired range-angle couples, which is unfavorable for target localization and jamming suppression. In this paper, a novel FDA scheme with Hamming interelement spacing, namely, the HIS-FDA, is proposed. By adopting Hamming window weighted interelement spacing and frequency offsets optimized by the genetic algorithm, the HIS-FDA produces a dot-shaped well-performed beampattern, which has superior performance over the existing FDA systems, especially in the angle dimension. The multiple input multiple output technique and multiple matched filters are employed at the receiver to solve the time-varying problem. A new multicarrier (MC) technique termed the sinusoidal MC approach is also presented to improve the beampattern performance, especially in the range dimension. Our proposed scheme outperforms the existing FDA systems in terms of the mainlobe width in the range and angle profiles, the sidelobe level, and the range-angle spatial region of the mainlobe. Comparison results are provided to validate the superiority of the proposed scheme.

A Radar Waveform Design of MCPC Method for Interrupted Sampling Repeater Jamming Suppression via Fractional Fourier Transform

A Radar Waveform Design of MCPC Method for Interrupted Sampling Repeater Jamming Suppression via Fractional Fourier Transform

Joint Radio Frequency Interference and Deceptive Jamming Suppression Method for Single-Channel SAR via Subpulse Coding

The radio frequency interference (RFI) and deceptive jamming (DJ), as two major external threats to synthetic aperture radar (SAR) systems, can greatly reduce the readability and veracity of the obtained SAR images. Current interference suppression methods have no capability to suppress both of them. In this article, a subpulse coding (SPC)-based joint RFI and DJ suppression method for single-channel SAR systems is proposed. By making full use of the elaborate coding scheme and subpulse transmitting mode, SPC can effectively suppress RFIs in the Doppler domain. On the other hand, after the decoding process, by utilizing the subpulse digital beamforming (DBF) technology with the well-designed DBF weight vectors, DJs can also be suppressed greatly. Numerical experiments verify the effectiveness of the proposed method.