Revolutionizing Detection: The Advancement and Application of FMCW Radar Technology

dc.contributor.advisorTovar, Julian
dc.contributor.authorRodríguez Lasso, Nicolas Andrés
dc.contributor.corporatenameUniversidad Santo Tomásspa
dc.contributor.orcidhttps://orcid.org/0000-0003-3618-7463Spa
dc.coverage.campusCRAI-USTA Tunjaspa
dc.date.accessioned2023-10-11T22:21:26Z
dc.date.available2023-10-11T22:21:26Z
dc.date.issued2023-10-11
dc.descriptionEste artículo tiene como objetivo investigar exhaustivamente la tecnología de radar de Onda Continua Modulada en Frecuencia (FMCW, por sus siglas en inglés) y su utilidad en la sociedad interconectada y automatizada de hoy en día. Se centra en el sensor UMRR-S, una innovación clave, y su aplicación en la Detección de Túneles Southwick en la plataforma de pruebas. A través de una metodología deductiva, establece una comprensión fundamental de la tecnología FMCW y cómo ha transformado diversas aplicaciones, desde mejorar la eficiencia de las redes de comunicación móvil hasta avanzar en los vehículos autónomos. El artículo también profundiza en aplicaciones específicas, como el sensor UMRR-S, que supera los requisitos de los Sistemas Avanzados de Asistencia al Conductor (ADAS, por sus siglas en inglés) y destaca un proyecto de evaluación en un complejo entorno de túnel. Estos análisis proporcionan una visión integral del potencial transformador de la tecnología de radar FMCW en las infraestructuras tecnológicas modernas. La tecnología de radar FMCW se ha convertido en una herramienta indispensable en diversas aplicaciones de vanguardia, debido a su precisión y robustez, incluso en condiciones climáticas adversas como niebla, lluvia o nieve. A diferencia de los sistemas de radar tradicionales, el radar FMCW emplea una señal de onda continua, modulando su frecuencia para determinar tanto la distancia como la velocidad del objeto, lo que lo hace altamente versátil. Esta tecnología desempeña un papel crucial en las telecomunicaciones, permitiendo la medición precisa de las distancias de señal y las velocidades de los paquetes de datos, y en el Internet de las Cosas (IoT, por sus siglas en inglés), donde se utiliza para aplicaciones como hogares inteligentes, industria 4.0 y agricultura para la recolección de datos, detección de objetos y monitoreo ambiental. Además, el radar FMCW ha tenido un impacto significativo en el desarrollo y operación de vehículos autónomos, contribuyendo a funciones como la evitación de colisiones, asistencia para cambio de carril y navegación completamente autónoma, mejorando la seguridad pública.spa
dc.description.abstractThis article aims to thoroughly investigate Frequency Modulated Continuous Wave (FMCW) radar technology and its utility in today's interconnected and automated society. It focuses on the UMRR- S sensor, a key innovation, and its application in the Southwick Tunnel Detection .Test Bed. Through a deductive methodology, it establishes a fundamental understanding of FMCW technology and how it has transformed various applications, from enhancing the efficiency of mobile communication networks to advancing autonomous vehicles. The article also delves into specific applications, such as the UMRR-S sensor, which surpasses Advanced Driver Assistance Systems (ADAS) requirements and highlights an evaluation project in a complex tunnel environment. These analyses provide a comprehensive view of the transformative potential of FMCW radar technology in modern technological infrastructures. FMCW radar technology has become an indispensable tool in various cutting-edge applications, owing to its precision and robustness, even in adverse weather conditions like fog, rain, or snow. Unlike traditional radar systems, FMCW radar employs a continuous wave signal, modulating its frequency to determine both object distance and speed, making it highly versatile. This technology plays a crucial role in telecommunications, enabling precise measurement of signal distances and data packet speeds, and in the Internet of Things (IoT), where it is used for applications such as smart homes, industry 4.0, and agriculture for data collection, object detection, and environmental monitoring. Moreover, FMCW radar has had a significant impact on the development and operation of autonomous vehicles, contributing to functions such as collision avoidance, lane-change assistance, and fully autonomous navigation, enhancing public safety.spa
dc.description.degreelevelPregradospa
dc.description.degreenameIngeniero Informáticospa
dc.format.mimetypeapplication/pdfspa
dc.identifier.citationRodríguez Lasso, N. A. (2023). Revolutionizing Detection: The Advancement and Application of FMCW Radar Technology. [Trabajo de Grado, Universidad Santo Tomás]. Repositorio Institucional.spa
dc.identifier.instnameinstname:Universidad Santo Tomásspa
dc.identifier.reponamereponame:Repositorio Institucional Universidad Santo Tomásspa
dc.identifier.repourlrepourl:https://repository.usta.edu.cospa
dc.identifier.urihttp://hdl.handle.net/11634/52717
dc.language.isospaspa
dc.publisherUniversidad Santo Tomásspa
dc.publisher.facultyFacultad de Ingeniería de Sistemasspa
dc.publisher.programIngeniería Informáticaspa
dc.relation.referencesM. Jankiraman, FMCW radar design, Artech House, Norwood: ARTECH HOUSE, 2018.spa
dc.relation.referencesA. H. P. A. Shoykhetbrod, "A scanning FMCW-radar system for the detection of fast moving objects," IEEE, pp. 1-5, 2014.spa
dc.relation.referencesS. Futatsumori, N. Yonemoto, N. Shibagaki, Y. Sato and K. Kashima, "Performance Evaluations of Airport Runway Foreign Object Detection System Using a 96 GHz Millimeter-Wave Radar System Based on International Standard," IEEE, pp. 1-2, 2022.spa
dc.relation.referencesM. Ralph, B. Marc, M. Marc-Michael, B. Arne and Thanh-Binh, "The UMRR-S: A High-Performance 24GHz Multi Mode Automotive Radar Sensor for Comfort and Safety Applications," Researchgate, 2003.spa
dc.relation.referencesN. Statt, "LIDR is the Latest Game- Changing Advancement for Autonomous Vehicles," IEEE innovationatwork, 01 10 2018. [Online]. Available: https://innovationatwork.ieee.org/lidr-is-the- latest-game-changing-advancement-for- autonomous-vehicles/. [Accessed 04 10 2023].spa
dc.relation.referencesG. Velasco-Hernandez and J. Barry, "Sensor and Sensor Fusion Technology in Autonomous Vehicles:A Review," MDPI, vol. 21, no. 6, pp. 1 - 37, 2021.spa
dc.relation.referencesX. Gao, S. Roy and G. Xing, "MIMO-SAR: A Hierarchical High-Resolution Imaging Algorithm for mmWave FMCW Radar in Autonomous Driving," IEEE, vol. 70, no. 8, pp. 7322-7334, 2021.spa
dc.relation.referencesF. A. Butt, J. N. Chattha, J. Ahmad, M. U. Zia, M. Rizwan and I. H. Naqvi, "On the Integration of Enabling Wireless Technologies and Sensor Fusion for Next- Generation Connected and Autonomous Vehicles," IEEE, vol. 10, pp. 14643-14668, 2022.spa
dc.relation.referencesM. Ławryńczuk and K. Zarzycki, "LSTM and GRU Neural Networks as Models of Dynamical Processes Used in Predictive Control: A Comparison of Models Developed for Two Chemical Reactors," Faculty of Electronics and Information Technology, Institute of Control and Computation Engineering, Warsaw University of Technology, p. 15/19, 2021.spa
dc.relation.referencesO. Güneş and ö. Morgül, "LSTM Based Classification of Targets using FMCW Radar Signals," IEEE, vol. 10, pp. 1 - 4, 2021.spa
dc.relation.referencesJ. Ling, "Advances in FMCW radar technology for automotive applications," Sensors, vol. 13, no. 7, pp. 7929 - 7959, 2013.spa
dc.relation.referencesF. Shoichiro and H. Kyosuke, Radar for Meteorological and Atmospheric Observations, Springer Science & Business Media, 2014.spa
dc.relation.referencesJ. Federhoff, Radar Basics, Springer Science & Business Media, 2011.spa
dc.relation.referencesE. L. Roth, Fundamentals of radar signal processing, New York: McGraw-Hill Education, 2014.spa
dc.relation.referencesN. Brailsford, "Evaluation SMART Radar Southwick Tunnel Detection System Test Bed," National Highways, Brunswick, 2021.spa
dc.relation.referencesV. Winkler, "Range Doppler detection for automotive FMCW radars," in European Radar Conference, Munich, Germany, 2007.spa
dc.rightsAtribución-NoComercial-SinDerivadas 2.5 Colombia*
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2spa
dc.rights.localAbierto (Texto Completo)spa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/co/*
dc.subject.keywordFMCW radarspa
dc.subject.keywordUMRR-S sensorspa
dc.subject.keywordautonomous vehiclesspa
dc.subject.keywordtechnologyspa
dc.subject.keywordapplicationsspa
dc.subject.keywordtelecommunicationsspa
dc.subject.keywordIoTspa
dc.subject.keywordprecisionspa
dc.subject.keywordversatilityspa
dc.subject.keywordsafetyspa
dc.subject.proposalFMCWspa
dc.subject.proposalradarspa
dc.subject.proposalUMRR-S sensorspa
dc.subject.proposalautonomous vehiclesspa
dc.subject.proposaltechnologyspa
dc.subject.proposalapplicationsspa
dc.subject.proposaltelecommunicationsspa
dc.subject.proposalIoTspa
dc.subject.proposalprecisionspa
dc.subject.proposalversatilityspa
dc.subject.proposalsafetyspa
dc.titleRevolutionizing Detection: The Advancement and Application of FMCW Radar Technologyspa
dc.type.coarhttp://purl.org/coar/resource_type/c_7a1f
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.driveinfo:eu-repo/semantics/bachelorThesis
dc.type.localTrabajo de gradospa
dc.type.versioninfo:eu-repo/semantics/acceptedVersion

Files

Original bundle

Now showing 1 - 3 of 3
Loading...
Thumbnail Image
Name:
2023nicolasrodriguez
Size:
202.35 KB
Format:
Adobe Portable Document Format
Description:
Thumbnail USTA
Name:
2023cartaderechosautor
Size:
459.79 KB
Format:
Adobe Portable Document Format
Description:
Thumbnail USTA
Name:
2023cartaaprobaciónfacultad
Size:
356.37 KB
Format:
Adobe Portable Document Format
Description:

License bundle

Now showing 1 - 1 of 1
Thumbnail USTA
Name:
license.txt
Size:
807 B
Format:
Item-specific license agreed upon to submission
Description: