Explore the vast range of titles available.

In microwave RF receiver systems, the receiving front-end is an important module of the receiver front-end system and a crucial component in modern microwave communication, radar, electronic warfare systems, and other applications. The article introduces the design method of the microwave receiving front-end and specifically designs a microwave receiving front-end in the SC band.

Currently, in the field of military modernization, tactical networks using advanced unmanned aerial vehicle systems, such as drones, place an emphasis on proactively preventing operational limiting factors produced by cyber-electronic warfare threats and responding to them. This characteristic has recently been highlighted as a key concern in the functioning of modern network-based combat systems in research on combat effect analysis. In this paper, a novel discrete-event-system-specification-based cyber-electronic warfare M&S (D-CEWS) was first proposed as an integrated framework for analyzing communication effects and engagement effects on cyber-electronic warfare threats and related countermeasures that may occur within drones. Accordingly, for the first time, based on communication metrics in tactical ad hoc networks, an analysis was conducted on the engagement effect of blue forces by major wireless threats, such as multi-layered jamming, routing attacks, and network worms. In addition, the correlations and response logics between competitive agents were also analyzed in order to recognize the efficiency of mutual engagements between them based on the communication system incapacitation scenarios for diverse wireless threats. As a result, the damage effect by the cyber-electronic warfare threat, which could not be considered in the existing military M&S, could be calculated according to the PDR (packet delivery ratio) and related malicious pool rate change in the combat area, and the relevance with various threats by a quantifiable mission attribute given to swarming drones could also be additionally secured.

This paper presents a theoretical analysis in discrete time for a multi-tier weak radiofrequency (RF) signal estimation process with N simultaneous signals. Discrete time dynamic sampling is introduced and is shown to provide the capability to extract signal parameter values with increased accuracy compared with accuracy of estimates obtained in prior work. This paper advances phase measurement approaches by proposing discrete time dynamic sampling which our paper shows offers the desirable capability for more accurate weak signal parameter estimates. For N=2 simultaneous signals with a strong signal at 850 MHz and a weak signal at 855 MHz, the results show that dynamically sampling the instantaneous frequency at 24 times the Nyquist rate provides weak signal frequency estimates that are within 1.7×10-5 of the actual weak signal frequency and weak signal amplitude estimates that are within 428 PPM of the actual weak signal amplitude. Results are also presented for situations with N=2 simultaneous 5G signals. In one case, the strong signal is 3950 MHz, and the weak signal is 3955 MHz; in the other case the strong case is 5950 MHz, and the weak signal is 5955 MHz. The results for these cases show that estimates obtained with dynamic sampling are more accurate than estimates provided using a single sample rate of 65 MSPS. This work has promising applications for weak signal parameters estimation using instantaneous frequency measurements.

In a congested signal environment, it is difficult to obtain estimates of weak RF signal parameters. Determining signal parameter estimates in real time is a challenge for electronic warfare receivers that aim to receive multiple simultaneous signals. Prior work provided estimates of weak signal parameters (weak signal frequency and weak signal amplitude) without taking into account any error introduced by analog-to-digital converters that are inherently part of digital signal processing systems. In order to obtain realistic estimates, we need to take error introduced by an ADC into account. The primary aim of this paper is to quantify error introduced by a single ideal ADC as a function of angle. This paper presents a method to estimate angle resolution and quantization levels in N-bit analog-to-digital converters (ADCs) for use in a weak radiofrequency (RF) simultaneous signal estimation process. The paper quantifies the error in the angle quantization of an N-bit ADC for an input complex signal that is the instantaneous frequency obtained for the situation in which there are two simultaneous signals (with one strong signal and one weak signal) in a weak RF simultaneous signal estimation process. The presented method describes the process to determine the angle quantization range, angle quantization uncertainty, and angle quantization error. This approach has potential applications in electronic warfare (EW) systems. The approach also has potential for assessing ADC performance for measurements that approach the quantum limit. Results are presented for 1-bit, 2-bit, 3-bit, and 10-bit ADCs.

In this article a compact sinusoidal tapered slot Vivaldi linear antenna array is designed for X and Ku band applications is presented. Printed Vivaldi antennas are extensively used for broadband applications because it gives high gain and broad bandwidth. The proposed antenna consists of two circular stubs, one rectangular slot and sinusoidal tapered lines on both sides of the antenna structure. These two tapered lines separated by circular slots and rectangular slot. The bandwidth of the antenna is improved with two circular stubs before the tapering. A rectangular slot is included before the two stubs to reduce the aperture width of the antenna. The feed line is then terminated with sectorial stub to have better coupling to the slot. The profile of the tapering of slot is designed as sinusoidal variation to have good end fire radiation for the entire frequency range. The simulated single antenna has return loss less than− 10 dB in between the frequencies 8.2–20 GHz. A five-element linear array is designed, simulated and prototype model is fabricated. The simulated and experimental results show return loss is less than − 7.5 dB for the frequency range of 8.2–20 GHz. The maximum gain of single element and array is 4.6 dBi and 7 dBi respectively. The Co and cross polarization radiation patterns are measured. The designed Vivaldi antenna array is used in X, KU band, electronic warfare and phased array applications.

Cyber threats are projected to cause USD 10.5 trillion in damage to the global economy in 2025. Comprehending the level of threat is core to adjusting cyber posture at the personal, organizational, and national levels. However, representing the threat level with a single score is a daunting task if the scores are generated from big and complex data sources such as social media. This paper harnesses the modern technological advancements in artificial intelligence (AI) and natural language processing (NLP) to comprehend the contextual information of social media posts related to cyber-attacks and electronic warfare. Then, using keyword-based index generation techniques, a single index is generated at the country level. Utilizing a convolutional neural network (CNN), the innovative process automatically detects any anomalies within the countrywide threat index and explains the root causes. The entire process was validated with live Twitter feeds from 14 October 2022 to 27 December 2022. During these 75 days, AI-based language detection, translation, and sentiment analysis comprehended 15,983 tweets in 47 different languages (while most of the existing works only work in one language). Finally, 75 daily cyber threat indexes with anomalies were generated for China, Australia, Russia, Ukraine, Iran, and India. Using this intelligence, strategic decision makers can adjust their cyber preparedness for mitigating the detrimental damages afflicted by cyber criminals.

From the height of system-of-systems combat and operational perspective, the operations of cognitive electronic warfare (CEW) was analysed, and its main process and links were described. Secondly, the jamming effectiveness evaluation (JEE) model of cognitive electronic attack (CEA) operations was established based on the interference side, in which the change of threat degree was used as the measure index of jamming effectiveness. Then, based on the Q-learning model, an intelligent countermeasure strategy generation (ICSG) model was established, and the main steps in the model were given. Finally, on the basis the JEE model and the ICSG model, the simulation experiment was carried out for CEA operations. The result showed that combining the JEE model with the ICSG model can express the main process of the operations of CEW, as well as proved the validity of these models.

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.

Deinterleaving or radar pulse separation is a very important goal in terms of radar sources for identifying and implementing electronic warfare systems. In order to separate radar pulses, parameters measured by electronic warfare receivers such as electronic warfare support measures (ESM) and electronic signals intelligence (ELINT) are used in pulse separation. This paper presents a multi-parameter improved method for separating the pulse sequence of radar signals based on time of arrival (TOA) processing with sorting the other pulse descriptor words (PDW) parameters. In the proposed method, after extracting all the pulse repetition intervals (PRIs) based on TOA, the parameters of the angle of arrival, pulse width and carrier frequency (RF) are being used in pulse sorting to separate the received interleaved pulse sequences. The sequential difference histogram (SDIF) algorithm or cumulative difference histogram (CDIF) algorithm is used to extract all pulse repetition intervals. Also, in order to separate the sequence of the received pulses from all surroundings emitters, in addition to matching the potential PRI among the TOAs of the pulses and the similarity measurement in the other parameters of the pulse sequence (pulse sorting) have been used. This proposed algorithm is implemented in the integrated and complete design for deinterleaving of the radar pulses. The proposed method by considering low-cost computing sources considers a fast and low-complexity solution that can be used for edge-enabled distributed processors in aerial radar platforms as edge devices for military/combat unmanned aerial vehicles or networked missiles. The simulation results show that our method is completely effective.