Digital Radio Frequency Memory Research Articles

Photonics-based wideband multi-format tunable radar jamming signal generator

A photonics-based radar jamming signal generator is proposed in this paper. By adjusting a polarization controller, interrupted-sampling repeater jamming (ISRJ), comb spectrum modulation jamming (CSMJ), ISRJ and CSMJ composite jamming can be respectively generated after photoelectric conversion. We have experimentally verified the generation of ISRJ signals with duty cycles of 50% and 25%, the generation of CSMJ signals with comb spectrum frequency intervals of 5 MHz and 10 MHz, and the generation of their composite jamming signals in the Ku band. Additionally, the ISRJ and CSMJ composite jamming effect of radar signals in the Ka band has been tested. After matched filtering processing, multiple false targets are produced and the total number of jamming targets can be up to 25, demonstrating significant jamming effects. The proposed structure can generate multi-format jamming signals without using digital radio frequency memory, which is suitable for producing high-frequency and large-bandwidth jamming signals. It can be applied in electronic countermeasure systems.

Optimal Design of Group Orthogonal Phase-Coded Waveforms for MIMO Radar

Digital radio frequency memory (DRFM) has emerged as an advanced technique to achieve a range of jamming signals, due to its capability to intercept waveforms within a short time. multiple-input multiple-output (MIMO) radars can transmit agile orthogonal waveform sets for different pulses to combat DRFM-based jamming, where any two groups of waveform sets are also orthogonal. In this article, a group orthogonal waveform optimal design model is formulated in order to combat DRFM-based jamming by flexibly designing waveforms for MIMO radars. Aiming at balancing the intra- and intergroup orthogonal performances, the objective function is defined as the weighted sum of the intra- and intergroup orthogonal performance metrics. To solve the formulated model, in this article, a group orthogonal waveform design algorithm is proposed. Based on a primal-dual-type method and proper relaxations, the proposed algorithm transforms the original problem into a series of simple subproblems. Numerical results demonstrate that the obtained group orthogonal waveforms have the ability to flexibly suppress DRFM-based deceptive jamming, which is not achievable using p-majorization–minimization (p-MM) and primal-dual, two of the most advanced orthogonal waveform design algorithms.

Deep Learning-Based Active Jamming Suppression for Radar Main Lobe

Due to the development of digital radio frequency memory (DRFM), active jamming against the main lobe of the radar has become mainstream in electronic warfare. The jamming infiltrates the radar receiver via the main lobe, covering up the target echo information. This greatly affects the detection, tracking, and localization of targets by radar. In this study, we consider jamming suppression based on the independence of RF features. First, two stacked sparse auto-encoders (SSAEs) are built to extract the RF characteristics and signal features carried out by the actual radar signal for subsequent jamming suppression. This method can effectively separate RF features from signal features, making the extracted RF features more efficient and accurate. Then, an SSAE-based jamming suppression auto-encoder (JSAE) is proposed; the mixed signal, including the radar signal, jamming signal, and noise, is input to JSAE for dimensionality reduction. Therefore, the radar signal and RF features, extracted by the two SSAEs in the previous step, are used to constrain the features of the reduced mixed signal. Moreover, we integrate the feature level and signal level to jointly achieve jamming suppression. The original radar signal is used to assist the radar signal reconstructed by the decoder. By first filtering out interference-related features and then reconstructing the signal, we can achieve better jamming suppression performance. Finally, the effectiveness of the proposed method is verified by simulating the actual collected data.

Interrupted‐sampling repeater jamming suppression based on block sparse recovery and random phase encoding

AbstractThe interrupted‐sampling repeater jamming (ISRJ) is an effective kind of intro‐pulse coherent jamming based on digital radio frequency memory. It appears as a group of false targets that are difficult to distinguish on the range profile after pulse compression, which seriously affects the target identification and tracking. According to the coherence between ISRJ and real target echo and the waveform discontinuity caused by intermittent interception, a new method is proposed for ISRJ parameter estimation and jamming suppression based on block sparse recovery. To ensure the effectiveness of sparse recovery, the transmitted signal is divided into several random phase‐encoded sub‐pulses. Firstly, the pulse‐number and time‐delay of the received echo are estimated by block orthogonal matching pursuit. Then, the jamming slices are identified based on the sampling duty ratio and the Doppler frequency is estimated through matching. Finally, according to the parameter estimation results, the jamming slices are reconstructed to eliminate ISRJ. Numerical experiments in two typical scenarios have shown that this method can effectively suppress ISRJ. Especially in the scenario of high jamming duty ratio, this method exhibits good anti‐jamming performance.

A Multiple-False-Target ISAR Shape Deception Jamming Method Based on Improved Template Multiplication Modulated Time-Delay Algorithm and Sub-Nyquist Sampling

In recent decades, the deception jamming approach based on digital radio frequency memory (DRFM) for inverse synthetic aperture radar (ISAR) has been a well-researched topic. Various types of jamming signals based on interrupted-sampling repeater jamming (ISRJ) can induce one-dimensional multiple high-resolution range profile (HRRP) false targets or two-dimensional realistic multiple ISAR false targets for deception. However, these existing methods generate false targets that are identical to the real target. The ISRJ false target also generates a main false target whose energy is much higher than other sub-false targets. Thus, it is easy to discover that the radar has suffered jamming. In order to generate better, more confusing jamming signals, this paper proposes a jamming method based on sub-Nyquist sampling jamming to induce realistic, multiple false targets on ISAR images. It improves a template multiplication modulated time-delay method to eliminate and add scatterers on the selected false target to change its ISAR shape. The frequency-shift parameters of the template jamming signal are analyzed and derived in detail for eliminating and adding scatterers at the specified location. Thus, multiple false targets with different ISAR shapes and similar energy are generated, which can create better deception effects. Meanwhile, this method can adjust the number of false targets and the location of changed-shape false targets. Furthermore, the resolution of the false target can adaptively change with the radar pulse width and the accumulated pulse number. The simulation results show that the proposed deception jamming strategy works.

Compound radar jamming recognition based on signal source separation

To deal with various jamming signals based on digital radio frequency memories, a compound jamming signal recognition method based on source signal separation is proposed. In order to overcome label limitation of the supervised learning method in the recognition process, this paper puts forward "Separation + Recognition" strategy. Firstly, the received signals of multiple channels are preprocessed, and the number of signal sources is analyzed through the single-source detection algorithm. Then the received compound jamming signals are processed by source separation, and the independent single jamming signals can be obtained. On this basis, a fast signal compensation algorithm is added to compensate different source signals at overlapping time-frequency points, which effectively increases the integrity of the separated signals. The separated jamming signals are then put into the convolutional neural network for recognition, and the specific jamming types in the compound jamming signals can be obtained. It has been proved that the recognition accuracy of five kinds of compound jamming exceeds 90% when the jamming-to-noise ratio is 0 dB.

Jamming Recognition Algorithm Based on Variational Mode Decomposition

Aiming to address the issue of deception jamming generated by digital radio frequency memories (DRFM), this study proposes a feature extraction algorithm based on variational mode decomposition (VMD) for deception jamming recognition and composite deception jamming recognition. Firstly, models are constructed for the real echo (RE) and the deception jamming signals. Subsequently, the variational mode decomposition is conducted. Thirdly, the features are extracted from the decomposed intrinsic mode function (IMF) and fed into the support vector machine (SVM) for classification and recognition. To mitigate the challenge of high dimensionality and reduce the complexity of the learning task, mode selection and interclass divisibility of feature selection methods are employed. The effectiveness of the proposed algorithm is verified through simulations. Prior to feature selection, a signal-to-noise ratio (SNR) of 0 dB results in a jamming recognition accuracy exceeding 95%. After feature selection, the recognition accuracy remains largely unchanged, while the recognition speed significantly improves. Compared with other methods in the same field, the recognition accuracy shows a notable improvement. Furthermore, the proposed method is evaluated for its effectiveness in recognizing composite deception jamming, and simulation results validate its performance.

A Sorting Method for Radar Echo Extraction Based on Observation Submatrix

AbstractWith the advancement of active jamming technology, a variety of new types of coherent jamming based on digital radio frequency memory have been proposed and implemented in practice, posing serious threats to modern radar systems due to their flexibility, suppression, and deception characteristics. Hence the research on radar echo extraction is necessary and challenging. In this paper, we focus on removing interference from received time‐frequency overlapping signals,and the anti‐jamming problem is transformed into one linear underdetermined blind source separation model in a dual‐channel receiving scenario. The feasible solution is found by utilizing the observation submatrices to convert the observed signal features to a new representation, which originates from sparse component analysis. Simulations demonstrate that the developed technique outperforms standard interference countermeasures in terms of signal‐to‐interference ratio and target identification performance, which are critical for anti‐jamming.

Metasurfaces and Blinking Jamming: Convergent Study, Comparative Analysis, and Challenges.

Blinking jamming is an active self-screening technique performed by at least two aircraft to tackle monopulse radars and all complexity related thereto. Nowadays, the technique can be performed with digital radiofrequency memories (DRFMs), which are cumbersome, complex, expensive, need a dedicated compartment and antenna, and introduce spurs in the signals. In this paper, we propose an alternative to the implementation of blinking jamming with DRFMs, namely with reconfigurable metasurfaces. By covering the aircraft parts that most contribute to the radar cross-section (RCS), reconfigurable metasurfaces can interchangeably absorb or amplify impinging waves, making the aircraft 'blink' from the radar perspective. To validate the feasibility, simulations accounting for realistic phenomena are conducted. It is seen that, if the aircraft RCS can be varied in a ratio of 10:1, either with absorptive or power-amplifying metasurfaces, a performance similar to that of the DRFM is achieved. Furthermore, a ratio of 2:1 is sufficient to make the radar antenna system movements exceed the angular range of the formation. We also anticipate our work to be a starting point for completely new ways of countering radars, e.g., with countless small drones performing passive or active stand-off blinking jamming.

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.

ECCM Scheme for Countering Main-Lobe Interrupted Sampling Repeater Jamming via Signal Reconstruction and Mismatched Filtering

Digital radio frequency memory (DRFM)-based main-lobe interrupted sampling repeater jamming (ISRJ) can achieve the effects of both deception and suppression, which cause serious performance degradation in modern radar systems. In this article, we propose an electronic counter-countermeasure (ECCM) scheme based on signal reconstruction and mismatched filtering (SC-MMF). The ECCM scheme consists of two steps: time-domain signal reconstruction and mismatched filter (MMF) design. First, the time-domain signal without noise is reconstructed using the provided jamming perception information. Then, an MMF corresponding to the reconstructed signal is designed to suppress ISRJ targets. The MMF design problem is formulated as a problem of minimizing the peak false target level (PFTL) and is solved with an improved alternating projection algorithm. After mismatched filtering, ISRJ targets are suppressed. Numerical simulations validate the effectiveness of the proposed method and explore the impacts of various parameters on its performance. Moreover, results obtained on measured data show that the proposed method has practical value in engineering applications.

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.

DRFM-Based Jamming Signal Recognition Method Guided by Target Detection

Digital radio frequency memory (DRFM) based jammer equipped on target can generate multiple false targets by intercepting and forwarding the signal transmitted by radar, which lead to a serious threat to the performance of a radar system. Therefore, the recognition of radar jamming signal type is a key step of radar countermeasure. The existing jamming recognition methods do not take into account the factor of real-time performance. Since it uses the raw time-domain signals and complex network structures, which incurs dense computational complexity. To tackle this problem, this paper analyzes the time-frequency distribution maps of jamming signals after signal processing, and proposes a radar jamming recognition method based on the guidance of target detection. In the proposed method, firstly, based on the target detection information, the time-frequency image of the jamming region is obtained by performing short-time Fourier transformation (STFT); Secondly, a lightweight convolutional neural network (CNN) model was constructed to achieve jamming recognition. Finally, effectiveness of this method was evaluated using the simulated datasets with six typical radar jamming signals. The results show that the proposed method performed well in accuracy and efficiency, which is practical for real-time anti-jamming.

A Novel Countermeasure Method for Radar Coherent Jamming Based on Signal Feature Transformation

With the advancement of active jamming technology, a variety of new types of coherent jamming based on digital radio frequency memory (DFRM) have been proposed and implemented in practice, posing serious threats to modern radar systems due to their flexibility, suppression, and deception characteristics. Hence, the research on relevant countermeasures is necessary and challenging. In this paper, we take a fresh look at the problem and present a method for removing interference from received time-frequency overlapping signals based on signal feature modification (SFT). The antijamming problem is transformed into one linear underdetermined blind source separation (UBSS) model in a dual-channel receiving scenario using sparse component analysis, and the feasible solution is found by transforming the observed signal features to a new time-frequency domain representation. Simulations demonstrate that the developed technique outperforms standard interference countermeasures in terms of signal-to-interference ratio (SIR) and target identification performance, which are critical for antijamming.

Improved MUSIC Method against Range Dimension Deceptive Jamming Based on FDA-MIMO

Frequency diverse array-multiple-input multiple-output (FDA-MIMO) radar makes it transmit beam range–angle two-dimensional freedom by attaching a small frequency offset increment between the array elements. With the widespread use of digital radio frequency memory (DRFM) technology, it is able to delay the false target to any range bin and doppler unit by delaying and forwarding the radar transmits signals, resulting in the deceptive jamming effect of range dimension. To this end, based on the research of the existing main-lobe deceptive interference methods, this paper proposes a new improved MUSIC method based on the FDA-MIMO radar against deceptive jamming in the range dimension. Firstly, the range information of target and jamming is determined through spatial spectrum search by using the mismatch of jamming in the airspace position and range bin position, and then the process of range dimension deceptive jamming suppression is given. The simulation analysis results show that the proposed anti-jamming method can effectively mitigate against range dimension deceptive jamming.

A Novel Interrupted-Sampling Repeater Jamming Suppression Method Based on Time-Frequency Analysis and Target Sparse Reconstruction

Interrupted-sampling repeater jamming (ISRJ) is a new kind of coherent jamming for linear frequency modulation (LFM) signals. Based on digital radio frequency memory (DRFM), ISRJ can generate multiple false target groups by intercepting, storing, and retransmitting radar signal fragments, which significantly affects the postprocessing results of radar systems. Furthermore, due to the fragment interception of ISRJ, ISRJ false targets present a regular and discontinuous time-frequency (TF) distribution in contrast with real targets. Considering this intrinsic property and the coherent nature of ISRJ, this study proposes a new method based on TF analysis and target sparse reconstruction to address the ISRJ suppression issue. In this method, the echo signal is first sparsely represented to obtain both the real and false target positions. Then, according to the acquired target positions, information entropy features of targets are extracted in TF data for subsequent target identification. Finally, guided by the identification result, the real targets can be retained and reconstructed by adaptive filtering in the sparse domain to realize ISRJ suppression. Simulations have validated the effectiveness of the proposed method under various situations.

Interrupted-Sampling Repeater Jamming-Suppression Method Based on a Multi-Stages Multi-Domains Joint Anti-Jamming Depth Network

Jamming will seriously affect the detection ability of radar, so it is essential to suppress the jamming of radar echoes. Interrupted-sampling repeater jamming (ISRJ) based on a digital-radio-frequency-memory (DRFM) device can generate false targets at the victim radar by the interception and repeating of the radar transmission signal, which is highly correlated with the true target signal. ISRJ can achieve main lobe jamming and has both deception and oppressive jamming effects, so it is difficult for the existing methods to suppress this jamming effectively. In this paper, we propose a deep-learning-based anti-jamming network, named MSMD-net (Multi-stage Multi-domain joint anti-jamming depth network), for suppressing ISRJ main lobe jamming in the radar echo. In the first stage of MSMD-net, considering that the target signal is difficult to detect under a high jamming-to-signal ratio (JSR), we propose a preprocessing method of limiting filtering on the time-frequency domain to reduce the JSR using the auxiliary knowledge of radar. In the second stage, taking advantage of the discontinuity of the jamming in the time domain, we propose a UT-net network that combines the U-net structure and the transformer module. The UT-net performs target feature extraction and signal reconstruction in the signal time-frequency domain and preliminarily realizes the suppression of the jamming component. In the third stage, combined with phase information, a one-dimensional complex residual convolution U-net network (ResCU-net) is constructed in the time domain to realize jamming filtering and signal recovery further. The experimental results show that MSMD-net can obtain the best jamming suppression effect under different transmitted signals, different jamming modes, and different jamming parameters.

An Improved Sliding Matched Filter Method for Interrupted Sampling Repeater Jamming Suppression Based on Jamming Reconstruction

The development of the digital radio frequency memory (DRFM) has led to the interrupted sampling repeater jamming (ISRJ) becoming increasingly popular in electronic countermeasure (ECM). It is coherent with the emitted signal and extremely limits radar target detection which significantly obstructs radar electronic countercountermeasure (ECCM). In this paper, we study the ISRJ suppression for pseudo random code continuous wave (PRC-CW) radars. First, the relationship between the ISRJ and the radar waveform is obtained by analyzing the ISRJ principle. Second, the intermittent feature of the ISRJ with matched filter sliding is discussed and used to determine the retransmitted sampled slices (RSS). Third, the jamming signal is reconstructed using the minimum residual criterion and excluded from the echo signal. In the proposed method, we make the most of the information of the jamming signal for improving the anti-ISRJ performance in the low SNR regimes. This information pertains to the amplitude of the jamming signal being considerably higher than that of the real target signal. Fourth, utilizing this characteristic of the jamming signal, we propose an improved sliding matched filter method based on the RSS reconstruction. Last, numerical simulations illustrate the effectiveness of the proposed method and validation of the theoretical analysis.

Тестирование радиолокаторов с синтезированной апертурой антенны при помощи DRFM

The aim of this work is the practical development of the technology for synthetic aperture radars (SAR) testing using Digital Radio-Frequency Memory (DRFM). In this work, the methods of numerical mathematical modeling of interacting radio frequency systems in MATLAB and the methods for prototyping these systems using modular equipment from Keysight Technologies were used. And also, real manufactured devices (DRFM module) were used. In this work, the technology of synthetic aperture radars (SAR) testing using DRFM are discussed. The SAR prototype, built on the basis of modular equipment from Keysight Technologies and running under the MATLAB control is described. The structural and functional diagrams of the SAR model are considered, its operating modes are listed. A DRFM device, made on the basis of a VPX module with an FPGA and creating several arbitrary located simulated point targets on the SAR image is described. The structure of this DRFM is given. As a result of the work, a test radar image, formed by the SAR model as a result of processing synthesized in DRFM a digital radio-hologram (DRH), was obtained.