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Special Issue "Radar Signal Detection, Recognition and Identification"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: 25 October 2022 | Viewed by 2324

Special Issue Editors

Prof. Dr. Janusz Dudczyk
E-Mail Website1 Website2
Guest Editor
Institute of Information Technology and Technical Sciences, Stefan Batory State University, 96-100 Skierniewice, Poland
Interests: specific emitter identification; radar signal processing; feature extraction; radar emitter recognition; radar emitter identification; C4I Systems; ELINT systems; electronic warfare systems
Prof. Dr. Piotr Samczyński
E-Mail Website
Guest Editor
Politechnika Warszawska, Warsaw University of Technology, 00-661 Warszawa, Poland
Interests: SAR/ISAR; passive radars; passive SAR/ISAR; noise radars; radar signal processing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In  radar signals recognition and identification theory, the main task is to set distinctive patterns of such signals and work out methods for distinguishing them. In the literature, terms such as source emission patterns separating surfaces in the measurable features space are widely used to describe pattern recognition and classification. Because radar emitter recognition and classification is based on defining the location of the emission source from the above separating surfaces, it is essential to indicate a very significant fact. The radar metrics needs to be defined in the measurable feature space of this signal and extract the specific features of the radar signal to set a distinctive radar signal pattern.

Recently there has been a rapid development in electronic warfare systems. There are different methods of electromagnetic environment observation which are used to analyze radars’ signatures. These methods increase the quality of algorithms that recognize objects and targets automatically. A difference can be found in the ways of gaining distinctive features.

The aim of this Special Issue is to present the latest research results in the area of modern solutions in radar signal recognition and identification utilizing measurement and signature intelligence and the process of distinctive features extraction from radar signals in different applications, including both military use and a broad spectrum of civilian applications. Contributions from leading experts in this field of research will be collected and presented in this Special Issue.

This Special Issue aims to highlight advances in radar signal recognition and identification. Topics include but are not limited to:

  • Modern solutions in radar signal detection, recognition and identification;
  • Specific radar emitters identification;
  • New technologies in the process of features extraction in radar signals;
  • Classification methods and data particle divide;
  • New technologies in radar signal and data processing;
  • Application of artificial intelligence to radar signal detection, recognition and identification;
  • Countermeasures to modern radar and ELINT systems;
  • Civilian and military applications of modern radar technology in electronic warfare.

Prof. Dr. Janusz Dudczyk
Prof. Dr. Piotr Samczyński
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Radar Signal Detection
  • Recognition
  • Identification

Published Papers (4 papers)

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Research

Article
Multi-Sensory Data Fusion in Terms of UAV Detection in 3D Space
Sensors 2022, 22(12), 4323; https://doi.org/10.3390/s22124323 - 07 Jun 2022
Viewed by 324
Abstract
The paper focuses on the problem of detecting unmanned aerial vehicles that violate restricted airspace. The main purpose of the research is to develop an algorithm that enables the detection, identification and recognition in 3D space of a UAV violating restricted airspace. The [...] Read more.
The paper focuses on the problem of detecting unmanned aerial vehicles that violate restricted airspace. The main purpose of the research is to develop an algorithm that enables the detection, identification and recognition in 3D space of a UAV violating restricted airspace. The proposed method consists of multi-sensory data fusion and is based on conditional complementary filtration and multi-stage clustering. On the basis of the review of the available UAV detection technologies, three sensory systems classified into the groups of passive and active methods are selected. The UAV detection algorithm is developed on the basis of data collected during field tests under real conditions, from three sensors: a radio system, an ADS-B transponder and a radar equipped with four antenna arrays. The efficiency of the proposed solution was tested on the basis of rapid prototyping in the MATLAB simulation environment with the use of data from the real sensory system obtained during controlled UAV flights. The obtained results of UAV detections confirmed the effectiveness of the proposed method and theoretical expectations. Full article
(This article belongs to the Special Issue Radar Signal Detection, Recognition and Identification)
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Article
Pedestrian and Animal Recognition Using Doppler Radar Signature and Deep Learning
Sensors 2022, 22(9), 3456; https://doi.org/10.3390/s22093456 - 01 May 2022
Viewed by 401
Abstract
Pedestrian occurrences in images and videos must be accurately recognized in a number of applications that may improve the quality of human life. Radar can be used to identify pedestrians. When distinct portions of an object move in front of a radar, micro-Doppler [...] Read more.
Pedestrian occurrences in images and videos must be accurately recognized in a number of applications that may improve the quality of human life. Radar can be used to identify pedestrians. When distinct portions of an object move in front of a radar, micro-Doppler signals are produced that may be utilized to identify the object. Using a deep-learning network and time–frequency analysis, we offer a method for classifying pedestrians and animals based on their micro-Doppler radar signature features. Based on these signatures, we employed a convolutional neural network (CNN) to recognize pedestrians and animals. The proposed approach was evaluated on the MAFAT Radar Challenge dataset. Encouraging results were obtained, with an AUC (Area Under Curve) value of 0.95 on the public test set and over 0.85 on the final (private) test set. The proposed DNN architecture, in contrast to more common shallow CNN architectures, is one of the first attempts to use such an approach in the domain of radar data. The use of the synthetic radar data, which greatly improved the final result, is the other novel aspect of our work. Full article
(This article belongs to the Special Issue Radar Signal Detection, Recognition and Identification)
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Article
Multi-Criteria Decision Making to Detect Multiple Moving Targets in Radar Using Digital Codes
Sensors 2022, 22(9), 3176; https://doi.org/10.3390/s22093176 - 21 Apr 2022
Viewed by 176
Abstract
Technological advancement in battlefield and surveillance applications switch the radar investigators to put more effort into it, numerous theories and models have been proposed to improve the process of target detection in Doppler tolerant radar. However, still, more effort is needed towards the [...] Read more.
Technological advancement in battlefield and surveillance applications switch the radar investigators to put more effort into it, numerous theories and models have been proposed to improve the process of target detection in Doppler tolerant radar. However, still, more effort is needed towards the minimization of the noise below the radar threshold limit to accurately detect the target. In this paper, a digital coding technique is being discussed to mitigate the noise and to create clear windows for desired target detection. Moreover, multi-criteria of digital code combinations are developed using discrete mathematics and all designed codes have been tested to investigate various target detection properties such as the auto-correlation, cross-correlation properties, and ambiguity function using mat-lab to optimize and enhance the static and moving target in presence of the Doppler in a multi-target environment. Full article
(This article belongs to the Special Issue Radar Signal Detection, Recognition and Identification)
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Article
An X-Band CMOS Digital Phased Array Radar from Hardware to Software
Sensors 2021, 21(21), 7382; https://doi.org/10.3390/s21217382 - 06 Nov 2021
Viewed by 748
Abstract
Phased array technology features rapid and directional scanning and has become a promising approach for remote sensing and wireless communication. In addition, element-level digitization has increased the feasibility of complicated signal processing and simultaneous multi-beamforming processes. However, the high cost and bulky characteristics [...] Read more.
Phased array technology features rapid and directional scanning and has become a promising approach for remote sensing and wireless communication. In addition, element-level digitization has increased the feasibility of complicated signal processing and simultaneous multi-beamforming processes. However, the high cost and bulky characteristics of beam-steering systems have prevented their extensive application. In this paper, an X-band element-level digital phased array radar utilizing fully integrated complementary metal-oxide-semiconductor (CMOS) transceivers is proposed for achieving a low-cost and compact-size digital beamforming system. An 8–10 GHz transceiver system-on-chip (SoC) fabricated in 65 nm CMOS technology offers baseband filtering, frequency translation, and global clock synchronization through the proposed periodic pulse injection technique. A 16-element subarray module with an SoC integration, antenna-in-package, and tile array configuration achieves digital beamforming, back-end computing, and dc–dc conversion with a size of 317 × 149 × 74.6 mm3. A radar demonstrator with scalable subarray modules simultaneously realizes range sensing and azimuth recognition for pulsed radar configurations. Captured by the suggested software-defined pulsed radar, a complete range–azimuth figure with a 1 km maximum observation range can be displayed within 150 ms under the current implementation. Full article
(This article belongs to the Special Issue Radar Signal Detection, Recognition and Identification)
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