Search Results (19)

The prevalence of Low Probability of Interception (LPI) and Low Probability of Exploitation (LPE) radars in contemporary Electronic Warfare (EW) presents an ongoing challenge to defense mechanisms, compelling constant advances in protective strategies. Noise radars are examples of LPI and LPE systems that gained substantial prominence in the past decade despite exhibiting a common drawback of limited Doppler tolerance. The Advanced Pulse Compression Noise (APCN) waveform is a stochastic radar signal proposed to amalgamate the LPI and LPE attributes of a random waveform with the Doppler tolerance feature inherent to a linear frequency modulation. In the present work, we derive closed-form expressions describing the APCN signal’s ambiguity function and spectral containment that allow for a proper analysis of its detection performance and ability to remove range ambiguities as a function of its stochastic parameters. This paper also presents a more detailed address of the LPI/LPE characteristic of APCN signals claimed in previous works. We show that sophisticated Electronic Intelligence (ELINT) systems that employ Time Frequency Analysis (TFA) and image processing methods may intercept APCN and estimate important parameters of APCN waveforms, such as bandwidth, operating frequency, time duration, and pulse repetition interval. We also present a method designed to intercept and exploit the unique characteristics of the APCN waveform. Its performance is evaluated based on the probability of such an ELINT system detecting an APCN radar signal as a function of the Signal-to-Noise Ratio (SNR) in the ELINT system. We evaluated the accuracy and precision of the random variables characterizing the proposed estimators as a function of the SNR. Results indicate a probability of detection close to 1 and show good performance, even for scenarios with a SNR slightly less than $-10$ dB. The contributions in this work offer enhancements to noise radar capabilities while facilitating improvements in ESM systems. Full article

In the present study, a new structure (0.5–18 GHz) with excellent phase noise characteristics and a fast switching speed is proposed. Ultra-wideband synthesizers with low phase noises and less spurious signals have been developed to be used as local oscillators and for built-in test (BIT) functions in the field of electronic warfare systems (EW), in which synthesizers are installed at the front-end of devices; this is accomplished by applying an SMT process using a packaged-type device. This paper compares the advantages and disadvantages of PLVCO (old) and DDS reference sources (new) based on two types of frequency synthesizers. At this time, different frequencies can be output from the two ports by different FPGA coding of the internal frequency plan according to the operating frequency. The main RF line will be made a dielectric substrate, RO4350, with a relative dielectric constant of 3.38 and a dielectric thickness of 0.508 mm. In the ultra-broadband synthesizer module, the phase noise of the DDS output (1.25 GHz) was −131 dBc/Hz at 10 KHz offset. The phase noise in the 18 GHz output is expected to be −105.9 dBc/Hz at 1 KHz offset. In particular, by proposing a structure for obtaining a wideband frequency using a single source (DDS), the structure secures reliability from the point of view of a system operating for a long time by implementing a similar circuit within a predictable range. Full article

In future electronic warfare (EW), there will be many unmanned aerial vehicles (UAVs) equipped with electronic support measure (ESM) systems, which will often encounter the challenge of radar emitter identification (REI) with few labeled samples. To address this issue, we propose a novel deep learning network, IRelNet, which could be easily embedded in the computer system of a UAV. This network was designed with channel attention, spatial attention and skip-connect features, and meta-learning technology was applied to solve the REI problem. IRelNet was trained using simulated radar emitter signals and can effectively extract the essential features of samples in a new task, allowing it to accurately predict the class of the emitter to be identified. Furthermore, this work provides a detailed description of how IRelNet embedded in a UAV was applied in the EW scene and verified its effectiveness via experiments. When the signal-to-noise ratio (SNR) was 4 dB, IRelNet achieved an identification accuracy of greater than 90% on the samples in the test task. Full article

This article aims to propose an algorithm for the automatic recognition of selected radar signals. The algorithm can find application in areas such as Electronic Warfare (EW), where automatic recognition of the type of intra-pulse modulation or the type of emitter operation mode can aid the decision-making process. The simulations carried out included the analysis of the classification possibilities of linear frequency modulated pulsed waveform (LFMPW), stepped frequency modulated pulsed waveform (SFMPW), phase coded pulsed waveform (PCPW), rectangular pulsed waveforms (RPW), frequency modulated continuous wave (FMCW), continuous wave (CW), Stepped Frequency Continuous Wave SFCW) and Phase Coded Continuous Waveform (PCCW). The algorithm proposed in this paper is based on the use of continuous wavelet transform (CWT) coefficients and higher-order statistics (HOS) in the feature determination of selected signals. The Principal Component Analysis (PCA) method was used for dimensionality reduction. An artificial neural network was then used as a classifier. Simulation studies took into account the presence of noise interference with signal-to-noise ratio (SNR) in the range from −5 to 10 dB. Finally, the obtained classification efficiency is presented in the form of a confusion matrix. The simulation results show a high recognition test accuracy, above 99% with a signal-to-noise ratio greater than 0 dB. The article also deals with the selection of the type and parameters of the wavelet. The authors also point to the problems encountered during the research and examples of how to solve them. Full article

The increasing demand in the development of autonomous driving systems makes the employment of automotive radars unavoidable. Such a motivation for the demonstration of fully-autonomous vehicles brings the challenge of secure driving under high traffic jam conditions. In this paper, we present the investigation of Advanced Driver Assistance Systems (ADAS) radars from the perspective of electronic warfare (EW). Close to real life, four ADAS jamming scenarios have been defined. Considering these scenarios, the necessary jamming power to jam ADAS radars is calculated. The required jamming Effective Radiated Power (ERP) is −2 dBm to 40 dBm depending on the jamming scenario. These ERP values are very low and easily realizable. Moreover, the effect of the jamming has been investigated on the radar detection at radar Range Doppler Map (RDM) and 2-Dimensional Constant False Alarm Rate (2D-CFAR). Furthermore, the possible jamming system requirements have been investigated. It is noted that the required jamming system will not require high-end technology. It is concluded that for the security of automotive driving, the ADAS radar manufacturer should consider the intentional jamming and related Electronic Counter Countermeasures (ECCM) features in the design of ADAS radars. Full article

The antenna scanning period (ASP) of radar is a crucial parameter in electronic warfare (EW) which is used in many applications, such as radar work pattern recognition and emitter recognition. For antennas of radars and EW systems, which perform scanning circularly, the method based on threshold measurement is invalid. To overcome this shortcoming, this study proposes a method using the convolutional neural network (CNN) to recognize the ASP of radar under the condition that antennas of the radar and EW system both scan circularly. A system model is constructed, and factors affecting the received signal power are analyzed. A CNN model for rapid and accurate ASP radar classification is developed. A large number of received signal time–power images of three separate ASPs are used for the training and testing of the developed model under different experimental conditions. Numerical experiment results and performance comparison demonstrate high classification accuracy and effectiveness of the proposed method in the condition that antennas of radar and EW system are circular scan, where the average recognition accuracy for radar ASP is at least 90% when the signal to-noise ratio (SNR) is not less than 30 dB, which is significantly higher than the recognition accuracy of NAC and AFT methods based on adaptive threshold detection. Full article

Accurate recognition of radar modulation mode helps to better estimate radar echo parameters, thereby occupying an advantageous position in the radar electronic warfare (EW). However, under low signal-to-noise ratio environments, recent deep-learning-based radar signal recognition methods often perform poorly due to the unsuitable denoising preprocess. In this paper, a denoising-guided disentangled network based on an inception structure is proposed to simultaneously complete the denoising and recognition of radar signals in an end-to-end manner. The pure radar signal representation (PSR) is disentangled from the noise signal representation (NSR) through a feature disentangler and used to learn a radar signal modulation recognizer under low-SNR environments. Signal noise mutual information loss is proposed to enlarge the gap between the PSR and the NSR. Experimental results demonstrate that our method can obtain a recognition accuracy of 98.75% in the −8 dB SNR and 89.25% in the −10 dB environment of 12 modulation formats. Full article

In this work, a microwave down converter is proposed for nanosatellite electronic warfare applications. It provides high spurious suppression by exploiting a dual-conversion architecture and premium performance in terms of noise figure and linear dynamic range. The system design takes advantage of commercial off-the-shelf components, thus allowing for both fast and cost-effective prototyping, which are key requirements particularly concerning CubeSat systems. Since different military, commercial, radar and communication systems operate in the 2–18 GHz frequency band, the capability to integrate such kinds of receivers in CubeSats represents the new frontier of the electronic warfare systems. Moreover, due to the wide operating bandwidth, it can be successfully exploited as the receiver for different applications, e.g., satellite communication, radars, etc. Full article

Along with the development of electromagnetic weapons, Electronic Warfare (EW) has been rising as the future form of war. Especially in the area of wireless communications, high security defense systems such as Low Probability of Detection (LPD), Low Probability of Interception (LPI), and Low Probability of Exploitation (LPE) communication algorithms are being studied to prevent military force loss. One LPD, LPI, and LPE communication algorithm, physical-layer security, has been discussed and studied. We propose a noise signaling system, a type of physical-layer security, which modifies conventionally modulated I/Q data into a noise-like shape. To suggest the possibility of realistic implementation, we use Software-Defined Radio (SDR). Since there are certain hardware limitations, we present the limitations, requirements, and preferences of practical implementation of the noise signaling system. The proposed system uses ring-shaped signaling, and we present a ring-shaped signaling system algorithm, SDR implementation methodology, and performance evaluations of the system using the metrics of Bit Error Rate (BER) and Probability of Modulation Identification (PMI), which we obtain by using a Convolutional Neural Network (CNN) algorithm. We conclude that the ring-shaped signaling system can perform high LPI/LPE communication functioning because an eavesdropper cannot obtain the correct modulation scheme information. However, the performance can vary with the configurations of the I/Q data-modifying factors. Full article

Accurate direction of arrival (DOA) estimation of wideband, low-power nonstationary signals is important in many radio frequency (RF) applications. This article analyses the performance of two incoherent aggregation techniques for the DOA estimation of high chirp-rate linear frequency modulated (LFM) signals used in modern radar and electronic warfare (EW) applications. The aim is to determine suitable aggregation techniques for blind DOA estimation for real-time implementation with a frequency channelised signal. The first technique calculates a single pseudospectrum by directly combining the spatial covariance matrices from each of the frequency bins. The second technique first calculates the spatial pseudospectra from the spatial covariance matrix (SCM) from each frequency bin and then combines the spatial pseudospectra into one single estimate. Firstly, for single and multiple signal emitters, we compare the DOA estimation performance of incoherent SCM-based aggregation with that of the incoherent spatial pseudospectra-based aggregation using the root mean-squared error (RMSE). Secondly, we determine the types of signals and conditions for which these incoherent aggregation techniques are more suited. We demonstrate that the low-complexity SCM-based aggregation technique can achieve relatively good estimation performance compared to the pseudospectra-based aggregation technique for multiple narrowband signal detection. However, pseudospectra aggregation is better suited for single wideband emitter detection. Both the incoherent aggregation techniques presented in this article offer a computational advantage over the coherent processing techniques and hence are better suited for real-time implementation. Full article

Passive ground emitter geolocation techniques are essential to electronic warfare systems, as they provide threat warnings in hostile environments, while ensuring the electronic silence of the mission platform. Geolocation of enemy emitters indicates the position of and type of adversary troops, and allows for the use of guided munition against enemy targets. Three-dimensional geolocation solutions based on least squares and particle filter estimation, using only azimuth and elevation measurements, were considered. Three batch-processing and one instantaneous solution algorithms, i.e., using a single pulse or a single observation point, were developed and investigated. The performance of the proposed solutions was demonstrated by simulations. Results showed that the batch-processing solutions achieved acceptable accuracies with a sufficient number of observation points. The performance degraded with fewer observation points. The instantaneous geolocation solution improved performance with increasing observation points, i.e., working in the sequential mode, and therefore could approach the accuracy of the batch-processing solutions. Full article

Electronic Warfare (EW) effectiveness evaluation plays an important role in promoting the development of EW technology, promoting the construction of EW equipment systems, and improving the operational capability of the system. Due to the incomplete information caused by the non-cooperative nature of EW, the data of the evaluation index, which are used for effectiveness evaluation, are in Grey scale. In order to approach these problems, we develop a novel method for EW effectiveness evaluation based on Conflict Status Grey Correlation analysis. Specifically, based on conflict theory and correlation theory, an analysis model for the approximation degree of the observation status and expected status of EW is established. Then we introduce the status Grey relational analysis method. The effectiveness value is acquired through the function correlation of the approximation values of both sides, and then we propose an evaluation discrimination method based on status robustness and correlation discrimination. At the same time, we evaluate the effect of errors in the observed values on the evaluation results. The simulation example results show that the proposed model is rational and feasible. This method can effectively overcome the problem of single-angle evaluation of the system and solves the issue of high dependence of traditional EW effectiveness evaluation theory on target data. Full article

A new line-of-sight (LOS) decision algorithm applicable to simulation of electronic warfare (EW) is developed. For accurate simulation, the digital terrain elevation data (DTED) of the region to be analyzed must be reflected in the simulation, and millions of datasets are necessary in the EW environment. In order to obtain real-time results in such an environment, a technology that determines line-of-sight (LOS) quickly and accurately is very important. In this paper, a novel algorithm is introduced for determining LOS that can be applied in an EW environment with three-dimensional (3D) DTED. The proposed method shows superior performance as compared with the simplest point-to-point distance calculation method and it is also 50% faster than the conventional interpolation method. The DTED used in this paper is the data applied as level 0 for the Republic of Korea, and the decision of the LOS at approximately 1.8 million locations viewed by a reconnaissance plane flying 10 km above the ground is determined within 0.026 s. Full article

An Electronic Warfare (EW) system is a highly complex and highly uncertain dynamic system. With a change of environment conditions, EW systems present different states and exhibit the characteristics of a Markov chain, which also directly affects and determines the effectiveness of EW systems. In order to describe and solve the problem of evaluating the effectiveness of EW, based on the definition of EW conflict system, this paper analyses the dynamic relationship of state between target unit and task unit of an EW system, studies the measurability of state, obtains measurable state space, then introduces randomness into state space and gives the theory, properties and applications of the state random process, state Markov process. Finally, the dynamic conflict analysis model of EW effectiveness is constructed and used to analyze the state transition process in the dynamic conflict process of an EW system, which is of great value to improve the theoretical system of EW effectiveness evaluation. Full article

Current electronic warfare (EW) systems, along with the rapid development of information and communication technology, are essential elements in the modern battlefield associated with cyberspace. In this study, an efficient evaluation framework is proposed to assess the effectiveness of various types of EW systems that operate in cyberspace, which is recognized as an indispensable factor affecting modern military operations. The proposed method classifies EW systems into primary and sub-categories according to EWs’ types and identifies items for the measurement of the effectiveness of each EW system by considering the characteristics of cyberspace for evaluating the damage caused by cyberattacks. A scenario with an integrated EW system incorporating two or more different types of EW equipment is appropriately provided to confirm the effectiveness of the proposed framework in cyber electromagnetic warfare. The scenario explicates an example of assessing the effectiveness of EW systems under cyberattacks. Finally, the proposed method is demonstrated sufficiently by assessing the effectiveness of the EW systems using the scenario. Full article