False Targets Research Articles

A method for active deception jamming discrimination based on frequency response

There are many types of radar active deception false target jamming that are highly correlated with the real target. Recognizing the real and false targets under a low Signal-to-Noise Ratio (SNR) is difficult. To solve the above problem, this article proposes a real/false target recognition method based on the features of multi-pulse joint frequency response by analyzing the differences in the scattering characteristics and modeling real target echoes as a synthesis of multi-scattering center echoes. Firstly, in the range-doppler domain, the real and false targets are truncated along the range dimension, and a fast Fourier transform is performed to extract the features of multi-pulse joint frequency response. Then, a two-channel feature fusion network is designed for real and false target recognition. Finally, a Multi-Coherent Processing Interval Joint Decision Method (M−CPIJDM) based on temporal information is proposed to improve the recognition performance. Experiments using the measured data show that the proposed method can well recognize real and false target signals under four jamming backgrounds: distance false target, velocity false target, distance-velocity composite false target, and forwarding dense false target.

A Photonics-Assisted Wideband Radar Jamming Signal Generator With Flexible Tunability and Multidimensional Optimization

In this article, a wideband radar jamming signal generator with flexible tunability and multidimensional optimization is proposed based on a dual-polarization Mach–Zehnder modulator (DPol-MZM) cascaded with a phase modulator (PM). Interrupted-sampling jamming is achieved with a sampling frequency of 1 MHz and duty cycles of 50% and 25%. Cross-cosinusoidal phase-modulated jamming with frequencies of 2 and 4 MHz is also built. A compound jamming signal that combines interrupted-sampling jamming and cross-cosinusoidal phase-modulated jamming is generated. The jamming effectiveness of the above schemes is evaluated, and multiple false targets are obtained after cross correlation with the original radar signal. The number of generated false targets can reach 12. The jamming mechanism of the proposed scheme is discussed, and the jamming effectiveness in radar imaging is also analyzed. The proposed scheme has a stable, compact, and efficient structure and meets the requirements of the electronic warfare system, which will get potential applications in future electronic warfare systems.

STLAR: A localization and authenticity recognition method for specific targets based on land‐based hyperspectral images

AbstractIn traditional two‐dimensional space object detection, it is believed that ‘objects with similar shapes belong to the same type’, making it difficult to distinguish true and false targets. In order to improve the efficiency of real object localization and detection, a specific target localization and authenticity recognition method (STLAR) based on joint spatial and spectral information is proposed. Firstly, the ground imaging spectrometer is utilized to obtain hyperspectral image data of the area to be measured. Then use a spatial object detection model to frame specific targets. Finally, compare the similarity between specific targets detected in space and prior spectral information. The experimental results successfully completed the task of target localization and recognition of authenticity. The proposed method can simultaneously solve the problems of spectral dimension detection or spatial dimension detection, providing new ideas for future rapid localization and recognition of specific targets.

Dense False Target Jamming Recognition Based on Fast–Slow Time Domain Joint Frequency Response Features

Dense False Target Jamming Recognition Based on Fast–Slow Time Domain Joint Frequency Response Features

Experimental study of underwater operation scene with target perception framework

This paper presents a target perception framework aimed at enhancing diver safety and facilitating underwater operations by extracting critical information from underwater scenes. The framework employs a layered processing approach, which encompasses water column imaging, constant false alarm rate detection, and local feature analysis. To simulate the diver's underwater environment, we conducted experiments with three distinct fields of view: fixed down-looking, fixed front-looking, and mobile side-looking perspectives. Our experimental findings demonstrate the framework's ability to accurately differentiate between false targets, stationary targets, and moving targets within the underwater scenes, as well as to capture the motion trajectories of dynamic targets. Furthermore, the application of 3D reconstruction techniques to underwater scene data enables the generation of approximate stereoscopic representations of divers and bubble groups.

Time-Domain Measurement Data Accumulation for Slow Moving Point Target Detection in Heavily Cluttered Environments Using CNN

In modern radars, the target detection probability is increased by lowering the detection threshold via signal processing to detect a point target with a small radar cross-section value. However, a lower threshold increases the number of false targets. In the conventional tracking method, which uses a general tracking filter, the measurement data between scans should be compared. Therefore, for a large amount of acquired measurement data, the computational complexity can be reduced by accumulating the acquired measurement data over time, recognizing the target movement as a pattern, and training a convolutional neural network (CNN) model. Here, we propose a method to create a desired target scenario by transfer learning and estimate the target position using the activation map of a binary detector CNN model. The model can detect a target using the actual acquired radar data, and the processing time remains constant, regardless of the number of false alarms.

Flexible Conformal Multifunctional Time‐Varying Phase‐Modulated Metasurface with Polarization Control for Radar Feature Transformation

AbstractReconfigurable metasurfaces have shown unprecedented capabilities in controlling electromagnetic (EM) waves in recent years and play an essential role in information manipulation. However, most research on reconfigurable metasurfaces is limited to planar rigid structures, with only one control function and suitable for specific single polarization. Achieving simultaneous control of phase, polarization, and frequency in the conformal structure has significant practical implications in many applications, but remains obviously challenging. In this paper, a flexible multifunctional time‐varying phase‐modulated metasurface (MTPM) with orthogonal polarization control is proposed for conformal applications to manipulate the spectrum distribution. It enables time encoding capability in controlling the phase characteristics of x‐ and y‐polarized EM waves individually by switching the bias voltage of the PIN diode in two directions. Discrete harmonic spectrum and continuous Doppler frequency shifts are implemented separately on two orthogonal polarizations by applying different time coding sequences. As a practical application, a conformal MTPM for radar feature transformation is explored. Multiple discrete false targets and defocusing phenomena can be realized respectively for x‐ and y‐polarized waves. Both simulated and measured results verify the validity of the proposed method and prototype.

Shadow-Based False Target Identification for SAR Images

In radar electronic countermeasures, as the difference between jamming and targets continues to decrease, traditional methods that are implemented based on classical features are currently unable to meet the requirements of jamming detection. Compared with classical features such as texture, scale, and shape, shadow has better discernability and separability. In this paper, target shadow is investigated and applied to detect jamming in Synthetic Aperture Radar (SAR) images, and a SAR false target identification method based on shadow features is proposed. First, a difference image is generated by change detection, which can extract the shadow region in single-time SAR images. Then, a three-step differentiation condition is proposed, which can distinguish false targets from real targets. Simulated experimental results show that the proposed method can effectively extract the shadow region in SAR images and accurately distinguishreal and false targets. Furthermore, the potential of shadow in SAR image interpretation and electronic countermeasures is also demonstrated.

Tunable radar compound coherent jamming signal generation based on microwave photonics.

A photonic-assisted scheme to generate radar compound coherent jamming signals based on a dual-parallel Mach-Zehnder modulator (DP-MZM) is proposed and experimentally demonstrated. The received linear frequency-modulated (LFM) signal is interrupted sampled and comb spectrum modulated by a DP-MZM. After photoelectric conversion, the compound coherent jamming signal, which combines the comb spectrum modulation jamming (CSMJ) and interrupted sampling repeater jamming (ISRJ), is generated. In the experiment, the generated coherent jamming signals have a 1-GHz bandwidth centered at 8 GHz and 18 GHz, respectively. The tunability of the frequency interval for CSMJ, the duty cycle, and the sampling frequency for ISRJ are verified. After pulse compression (PC), 10 false target groups are evenly distributed over a radial distance of 120 m, and the total number of false targets reaches to 50. The jamming effectiveness in radar imaging is also demonstrated. To the best of our knowledge, photonic-assisted CSMJ and ISRJ compound jamming generation is proposed for the first time. The proposed scheme is compact, wideband, and tunable, which shows a good potential application in the future electronic warfare system.

Adaptive optimization technology of segmented reconstruction signal based on genetic algorithm for enhancing radar jamming effect

Given the improved capabilities of radar systems, addressing unfamiliar signals presents a challenge for radar jamming technology. To tackle this issue, this study proposes an adaptive technique for optimizing jamming waveforms to suppress multiple false targets in escort jamming scenarios. The objective is to minimize the detectability of false targets by fine-tuning phase modulation and individual waveform parameters. The optimization model adjusts the energy and delay of jamming waveform segments using intercepted radar signal phase modulation and direct forwarding. Real-time adaptation is achieved through the utilization of a genetic algorithm and radar constant false alarm rate detection based on received emissions. The key findings highlight the advantages of adaptivity in effectively suppressing false targets under diverse conditions. The technique successfully learns efficient waveforms through feedback, even without specific knowledge of the radar system. The optimized waveforms maintain consistent jamming impact across different constant false alarm rate settings, surpassing the limitations associated with fixed assumptions. The introduction of phase modulation enhances the resilience of false targets by creating noise-like characteristics. Remarkably, robust jamming is achieved with only 12 false targets, reducing complexity. The unified waveform design is particularly suitable for single platform jamming, eliminating the need for multiple jammers. Furthermore, the optimized waveforms demonstrate improved coverage of real targets under position errors. As a result, the approach exhibits versatility across various signals, processing methods, and scenarios. This study suggests that increased adaptability and the incorporation of machine learning techniques contribute to the advancement of radar jamming capabilities. By optimizing jamming waveforms, the adaptive approach presented in this study may enhance the effectiveness of countering advanced radar systems.

Reconfigurable Intelligent Surface-Assisted Radar Deception Electronic Counter-Countermeasures

A reconfigurable intelligent surface (RIS) is a promising technology for wireless communication and radar detection, owing to its superior ability to realize smart radio environments. Inspired by previous studies on RISs, this study deals with the use of RISs for radar electronic counter-countermeasures (ECCMs) in deception jamming scenarios. At first, a RIS was applied to a monostatic radar, constructing a virtual multi-radar system combined with multi-beam receiving technology. Then, a data-fusion-based deception ECCM method for the proposed virtual multi-radar system was studied to discriminate the active false targets generated by deception jamming. A theoretical analysis of the target discrimination probability was derived. Because the location of RISs is the key to determining the target discrimination ability, the location optimization of the RIS was considered based on the theoretical analysis. Simulation results corroborate the deception ECCM ability of the proposed RIS-assisted virtual multi-radar system, enhancing the survivability of a radar system in a complex electromagnetic environment.

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.

Use of Stepped Carrier Frequency in Fast Scan Mode to Detect Small Targets on the Sea Surface

To detect a small target on the sea surface, we propose a detection algorithm that operates in three steps: (1) representation of three-dimensional complex cube in the (radial range, pulse time, scan time) domain by using stepped carrier frequency in fast scan mode; (2) intrascan integration to transform complex cube from the pulse time domain to the radial velocity domain by using Fourier transform; and (3) interscan integration to detect a small target by using a conventional optimal coherent detector with a Fourier relationship between stepped carrier frequency and initial radial range, and a discriminator between a true target and false targets. The proposed method improves the ability to detect of a small target, and reduces the sensitivity to sea clutter despite relatively low radial range resolution. In experiments, our proposed method could perform accurate and robust detection of a small target.

A Method for Recognizing Full Forwarding Dense False Target Jamming in the Absence of Label Information

A Method for Recognizing Full Forwarding Dense False Target Jamming in the Absence of Label Information

A Method to Suppress Interferences Based on Secondary Compensation with QPC-FDA-MIMO Radar

The traditional phased array radar is unable to distinguish mainlobe deceptive interference from the true target when they share an identical angle. To address this issue, a method is developed to suppress the interference in the joint transmit–receive–Doppler frequency domain, using secondary compensation and quadratic phase code (QPC) with the frequency diversity array multiple-input multiple-output (FDA-MIMO) radar. The QPC technique is employed by encoding the transmitted pulses in various spatial channels, which extends the degrees-of-freedom (DOFs) of the system. To distinguish and suppress the false targets behind the true target by at least one pulse, Doppler compensation is performed and Doppler filters are employed. To distinguish the fast-generated false targets, which are located in the same pulse with the true target, the spatial frequency compensation is implemented, which equivalently relocates the mainlobe interference to the sidelobes. Via the singular spectrum analysis (SSA) technique and the data-dependent beamforming, the interferences within the ambiguity region are suppressed. Simulation results verify the effectiveness of the method.

An Information Recognition and Time Extraction Method of Tracking a Flying Target with a Sky Screen Sensor Based on Wavelet Modulus Maxima Theory

Aiming at the problems of big noise, lots of false targets, and accurate time extraction while tracking a flying target in the signal from a sky screen sensor, a flying target recognition and time extraction method is proposed, based on wavelet transformation. The noisy signal output by the sky screen sensor is filtered with wavelet transformation to filter out some high-frequency components; the filter is designed to handle the signal time frequency characteristics of the flying target and noise. To improve the recognition efficiency of whether the signal includes tracking of the flight target, based on a two-class discriminant model, the wavelet Fisher discriminant method is used to construct the feature vector of the false target and the flying target signal, and the recognition method of the flying target signal is studied. According to the wavelet modulus maxima theory, the single target signal is isolated, and the time moment of the flying target passing through the detection screen is calculated. The velocities calculated based on the flying target signal recognition method proposed in this paper and based on the least-mean-squares algorithm of the traditional sky screen sensor velocity measurement system are compared with the net target velocity measurement system. The results show that the velocity data obtained by the method in this paper are closer to the true value of the target flight velocity, and the average error between the velocity value obtained by the method in this paper and the standard net target velocity measurement system is less than 0.954 m/s, which verifies the superiority of the method proposed in this paper.

Advancing Stepped-Waveform Radar Jamming Techniques for Robust False-Target Generation against LFM-CFAR Systems.

This study investigates the utilization of a stepped wave frequency modulation jamming technique in radar systems. The objective is to enhance the effectiveness and robustness of false target jamming in the presence of linear frequency modulation (LFM) radars employing constant false alarm rate (CFAR) detection. The proposed method combines stepped frequency modulation with full pulse delay/sum repeat jamming to enhance resilience against uncertainties in target parameters. Theoretical analysis and simulation experiments are conducted to establish relationships between key jammer parameters, such as frequency slope and power compensation, and performance metrics, like false target distribution and CFAR masking. The results demonstrate that the proposed technique effectively maintains a dense distribution of false targets surrounding the protected target, even in the presence of uncertainties in position and signal-to-noise ratio. In comparison to existing methods, the utilization of stepped-waveform modulation enables improved control over target distribution and CFAR masking. Adaptive power allocation compensates for parameter errors, thereby enhancing robustness. Simulation results reveal that the proposed approach significantly reduces the probability of detecting the true target by over 95% under uncertain conditions, while previous methods experienced degradation. The integration of stepped waveforms optimizes false target jamming, thereby advancing electronic warfare capabilities in countering advanced radar threats. This study establishes design principles for resilient jamming architectures and supports enhanced survivability against radars employing pulse compression and CFAR detection. Moreover, the concepts proposed in this study have the potential for extension to emerging radar waveforms.

Anti‐interrupted sampling repeater jamming method for random pulse repetition interval and intra‐pulse frequency agile radar

AbstractInterrupted sampling repeater jamming can produce numerous active false targets with high fidelity, which is a significant challenge for coherent pulse radar. This poses a threat to the effectiveness of anti‐jamming technology, such as time‐frequency analysis and frequency agility for conventional constant pulse repetition interval (PRI) radar, which will render the radar inoperable to detect and track the actual target. A random PRI and intra‐pulse frequency agile radar waveform with low interception properties is proposed, which can effectively restrict the acquisition of radar waveform parameters by the jammer, destroy the coherence of jamming signals, and capture the range‐dimensional centroid feature of the echo. Accordingly, a jamming identification method based on the scale constrained Gaussian mixture model and an entity radar target energe recovery algorithm based on the neighbourhood weighted maximum entropy are proposed for target detection. Theoretical analysis and simulation experiments demonstrate the effectiveness of the proposal.

Phased Array Radar Resource Consumption Method Based on Phase-Switched Screen

The consumption of phased array radar (PAR) resources affects the accuracy of its multi-target searching and tracking abilities. The jamming methods aimed at PAR involve deceptive jamming and comprehensive jamming strategies, but have the disadvantages of high cost and complexity. Given this context, this paper proposes a PAR resource consumption method based on phase-switched screen (PSS), and derives a relationship between the targets and the evaluation indicators. By implementing periodic modulation of PSS, a controlled number of deceptive multiple false targets can be generated, thereby enticing the radar system to engage in activities such as searching and tracking targets. When the quantity of false targets is increased, the number of beam requests becomes five times higher than compared to the scenario without false targets. This has also led the margin of time resources to exceed 50%, successfully achieving the objective of consuming radar resources. Furthermore, this method offers straightforward manipulation, flexibility, and the potential to significantly consume radar resources. The efficacy of the proposed method is confirmed with the simulation outcomes.

Echo Preprocessing-Based Smeared Spectrum Interference Suppression

Self-protection deceptive interferences (SPDI) are widely used in electronic countermeasures. Smeared spectrum (SMSP) interference, as a typical SPDI, can form a large number of dense false targets at the receiver output to affect effective target detection. Therefore, the suppression of SMSP interference is a compelling issue. The existing SMSP interference suppression methods inevitably result in energy loss of the target due to signal processing. This paper proposes a novel interference suppression method based on echo preprocessing to address this problem. Firstly, the pulse compression (PC) and the coherent integration (CI) characteristics of SMSP interference in the pulse Doppler radar are obtained through the derivation of formulas. Then, echo preprocessing is introduced, and the steps of interference suppression are listed in detail. Finally, the SMSP interference is suppressed because the preprocessed interference forms a center-shifting and range-scaling in the distance dimension after PC, and CI gain cannot be further obtained. The proposed method does not lose the energy of the true target because it does not involve filtering and reconstruction processing. Simulations show that the target detection probability of the proposed method can reach 100% via peak search after the interference suppression when the signal-to-noise ratio is greater than −10 dB and the jamming-to-signal ratio (JSR) is less than 35 dB. Compared with three representative methods in the recent literature, the proposed method has better robustness and higher JSR tolerance.