Innovations in AI and Signal Processing for Advanced Sensing, Radar, RFID, and Communication Systems

Topic Information

Dear Colleagues,

We are pleased to invite contributions to this Special Issue focusing on Innovations in AI and Signal Processing for Advanced Sensing, Radar, RFID, and Communication Systems. This edition aims to explore the transformative role of Artificial Intelligence (AI), Machine Learning (ML), and advanced signal processing techniques in shaping next-generation sensing and communication technologies.

This Topic aims to highlight innovative research and practical applications that address critical challenges and unlock new opportunities in a range of interconnected domains, including:

• Advanced Sensing Technologies: Exploring AI/ML-driven advancements in sensors for diverse applications.
• Radar Systems: Investigating signal processing and AI techniques for enhancing radar accuracy, resolution, and adaptability.
• RFID Systems: Examining how intelligent algorithms and signal processing can optimize RFID performance in industrial, agricultural, and healthcare applications.
• Communication Technologies: Showcasing breakthroughs in antenna design and signal processing for 5G and beyond.
• Emerging Applications: Delving into AI/ML’s role in areas such as Brain–Computer Interfaces (BCI) and biometric authentication.

This Special Issue seeks to provide a comprehensive platform for researchers and practitioners to present their cutting-edge findings, share insights, and discuss challenges in these rapidly evolving fields. Contributions may include original research articles, case studies, and reviews, focusing on theoretical advancements, practical implementations, or experimental studies.

We look forward to receiving your valuable contributions.

Dr. Shuvashis Dey
Dr. Dipankar Mitra
Dr. Rig Das
Dr. Giovanni Andrea Casula
Prof. Dr. Francisco Falcone
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
AI ai	3.1	7.2	2020	18.9 Days	CHF 1600	Submit
Applied Sciences applsci	2.5	5.3	2011	18.4 Days	CHF 2400	Submit
Electronics electronics	2.6	5.3	2012	16.4 Days	CHF 2400	Submit
Sensors sensors	3.4	7.3	2001	18.6 Days	CHF 2600	Submit
Signals signals	-	3.2	2020	28.3 Days	CHF 1000	Submit
Telecom telecom	2.1	4.8	2020	20.5 Days	CHF 1200	Submit
Technologies technologies	4.2	6.7	2013	21.1 Days	CHF 1600	Submit

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Published Papers (1 paper)

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All AI Applied Sciences Electronics Sensors Signals Telecom Technologies

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25 pages, 7385 KiB  

Open AccessArticle

Integrated Waveform Design and Signal Processing Based on Composite Noise Nimble Modulated Signals

by Xinquan Cao, Shiyuan Zhang, Ke Tan, Xingyu Lu, Jianchao Yang, Zheng Dai and Hong Gu

Electronics 2025, 14(6), 1227; https://doi.org/10.3390/electronics14061227 - 20 Mar 2025

Viewed by 93

Abstract

In modern radar operations, detection and jamming systems play a critical role. Integrated detection and jamming systems simultaneously fulfill both functions, thereby optimizing resource utilization. In this paper, we introduce a novel random noise frequency modulation nimble modulation integrated signal (RNFM-NMIS) that is [...] Read more.

In modern radar operations, detection and jamming systems play a critical role. Integrated detection and jamming systems simultaneously fulfill both functions, thereby optimizing resource utilization. In this paper, we introduce a novel random noise frequency modulation nimble modulation integrated signal (RNFM-NMIS) that is designed based on reconnaissance analysis of adversary linear frequency modulated (LFM) radar signal parameters. This waveform facilitates flexible adjustment of parameters, enabling adaptive detection and jamming functions. Furthermore, to address the challenge of direct-wave interference from adversary transmissions, we propose a signal processing method based on time-domain pre-cancellation (TDPC). Simulation and experimental results show that the proposed integrated waveform exhibits excellent and adjustable detection and jamming capabilities. Under the proposed processing method, interference suppression and target detection performance are significantly enhanced, achieving substantial improvements over traditional methods. Full article

(This article belongs to the Topic Innovations in AI and Signal Processing for Advanced Sensing, Radar, RFID, and Communication Systems)

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