Cognition and Utilization of Electromagnetic Space Signals

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".

Deadline for manuscript submissions: closed (15 July 2024) | Viewed by 3473

Special Issue Editors


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Guest Editor
Communication Engineering College, Xidian University, Xi'an 710071, China
Interests: electromagnetic signal processing; statistical signal processing; Artificial Intelligence
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Guest Editor
Department of Engineering, University of Durham, Durham DH1 3LE, UK
Interests: wireless communications; UAV communications; statistical signal processing; wireless relaying and energy harvesting
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
National Key Laboratory of Electromagnetic Space Security, Jiaxing 314000, China
Interests: machine learning and electromagnetic signal processing

Special Issue Information

Dear Colleagues,

The cognition and utilization of electromagnetic space signals have long provided the basis of electromagnetic signal processing. With the emergence of technologies and services such as mobile Internet, Internet of Things, big data, robotics, etc., there has been exponential growth in the variety types of electromagnetic equipment and systems, such as communication, radar, navigation, remote sensing, etc., resulting in the emergence of electromagnetic signals with complex characteristics such as nonlinear causality, self-organised evolution, and large-scale emergence. To attain a thorough comprehension and optimal usage of intricate electromagnetic spatial signals, it is imperative to investigate fresh models and concepts of electromagnetic spatial perception and usage. These include immersive perception, integrated detection of subject and object, and measurement fusion, which can prompt leapfrog development and disruptive innovation within the corresponding electromagnetic information technology sector. Despite the use of statistical analysis, data mining, artificial intelligence, and other technologies in a great deal of research aimed at enhancing the capacity for cognition and utilization of electromagnetic signals, these works still fail to maximize the use of deep cognitive capabilities and scientific utilization. Topics of interest include, but are not limited to, the following areas:

  • interaction mechanism of electromagnetic signals;
  • intelligent sensing of electromagnetic signals;
  • intelligent cognition of electromagnetic signals;
  • fusion characterization of electromagnetic signals;
  • passive detection using electromagnetic signals;
  • target cognition using electromagnetic signals;
  • behavior prediction of emitter using electromagnetic signals;
  • control and application of electromagnetic signals.

Dr. Mingqian Liu
Prof. Dr. Yunfei Chen
Dr. Huaji Zhou
Guest Editors

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Keywords

  • Artificial Intelligence
  • electromagnetic signals
  • signal interaction and control
  • signal processing
  • intelligence control
  • intelligence information security

Published Papers (3 papers)

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Research

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15 pages, 2493 KiB  
Article
Interference Response Prediction of Receiver Based on Wavelet Transform and a Temporal Convolution Network
by Lingyun Zhang, Hui Tan and Zhili Wang
Electronics 2024, 13(1), 162; https://doi.org/10.3390/electronics13010162 - 29 Dec 2023
Viewed by 661
Abstract
In order to improve the prediction performance of existing methods amidst multi modulation coupling interference in complex electromagnetic environments, this paper introduces a novel approach that integrates wavelet transform with a temporal convolutional network. The model begins with a data preprocessing stage, where [...] Read more.
In order to improve the prediction performance of existing methods amidst multi modulation coupling interference in complex electromagnetic environments, this paper introduces a novel approach that integrates wavelet transform with a temporal convolutional network. The model begins with a data preprocessing stage, where wavelet transform decomposes the original signal into various scales. This step generates scale coefficients across different frequency categories, effectively reducing the signal length. To enhance the model’s ability to capture long-term dependencies in time series data, temporal convolutional networks are employed for feature extraction. Moreover, the model’s performance is further refined by incorporating an attention mechanism-driven feature fusion strategy. This strategy methodically combines high and low frequency features along with local and global characteristics. The model’s efficacy is validated using a custom MATLAB dataset, with simulation results confirming a significant improvement in prediction accuracy. Full article
(This article belongs to the Special Issue Cognition and Utilization of Electromagnetic Space Signals)
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13 pages, 1986 KiB  
Article
Radar Signal Behavior in Maritime Environments: Falling Rain Effects
by Xun Wang, Menghan Wei, Ying Wang, Houjun Sun and Jianjun Ma
Electronics 2024, 13(1), 58; https://doi.org/10.3390/electronics13010058 - 21 Dec 2023
Viewed by 882
Abstract
Precision modeling of radar signal behavior in maritime environments holds paramount importance in ensuring the robust functionality of maritime radar systems. This work delves into the intricate dynamics of radar signal propagation in maritime environments, with a particular focus on the effects of [...] Read more.
Precision modeling of radar signal behavior in maritime environments holds paramount importance in ensuring the robust functionality of maritime radar systems. This work delves into the intricate dynamics of radar signal propagation in maritime environments, with a particular focus on the effects of falling rain. A theoretical model encompassing raindrop scattering, gaseous absorption, and ocean surface backscattering was developed and validated. Key findings reveal that rain significantly alters radar backscattering, with a noticeable decrease in signal strength under higher rainrates. Additionally, gaseous absorption, particularly at elevated frequencies and humidity levels, emerged as a critical factor. The study also highlights the complex interplay between wind-induced ocean surface roughness and radar signal behavior. We think these insights are pivotal for enhancing maritime radar system accuracy, particularly in adverse weather conditions, and paving the way for future research in refining environmental impact models on radar signals. Full article
(This article belongs to the Special Issue Cognition and Utilization of Electromagnetic Space Signals)
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Review

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20 pages, 4905 KiB  
Review
Research Progress of Wireless Positioning Methods Based on RSSI
by Bohang Chen, Jun Ma, Lingfei Zhang, Jiacheng Zhou, Jinyu Fan and Haiming Lan
Electronics 2024, 13(2), 360; https://doi.org/10.3390/electronics13020360 - 15 Jan 2024
Cited by 1 | Viewed by 1135
Abstract
Location-based services are now playing an integral role in the development of emerging industries, such as the Internet of Things, artificial intelligence and smart cities. Although GPS, Beidou and other satellite positioning technologies are becoming more and more mature, they still have certain [...] Read more.
Location-based services are now playing an integral role in the development of emerging industries, such as the Internet of Things, artificial intelligence and smart cities. Although GPS, Beidou and other satellite positioning technologies are becoming more and more mature, they still have certain limitations. In order to meet the needs of high-precision positioning, wireless positioning is proposed as a supplementary technology to satellite positioning, in which the Received Signal Strength Indication (RSSI) is one of the most popular positioning methods. In this paper, the application scenarios, evaluation methods and related localization methods of wireless positioning based on RSSI are studied. Secondly, the relevant optimization methods are analyzed and compared from different angles, and the methods of RSSI data acquisition are described. Finally, the existing problems and future development trends in RSSI positioning methods are expounded, which has certain reference significance for further research on RSSI localization. Full article
(This article belongs to the Special Issue Cognition and Utilization of Electromagnetic Space Signals)
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