Leveraging radar back-scattered data for classification of imaging targets

Research output: Chapter in Book/Report/Conference proceedingConference contribution

29 Downloads (Pure)

Abstract

Employing deep learning methodologies for computer vision tasks, particularly in the domain of radar image analysis, necessitates access to a large and diverse dataset. In the context of radar imagery, the creation of such a dataset often entails the intricate task of reconstructing images from raw radar back-scattered data. This reconstruction process involves handling substantial data volumes, which can be computationally intensve and time-consuming. In this research, a deep learning framework is proposed for target classification utilizing solely the radar back-scattered data, completely bypassing the need for image reconstruction procedure, thereby significantly reducing the classification time. To make the dataset generation easier, a computational imaging (CI) numerical model is employed. Subsequently, the deep learning model is trained using this dataset, and following the training phase, it is tested with radar back-scattered data that is not included in the network training. The outcomes of this evaluation confirm the benefit of training a deep learning model to perform image identification tasks based on radar back-scattered signatures.
Original languageEnglish
Title of host publication2024 IEEE European Conference on Antennas and Propagation (EuCAP): proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9788831299091
ISBN (Print)9798350394436
DOIs
Publication statusPublished - 26 Apr 2024
Event18th European Conference on Antennas and Propagation 2024 - Glasgow, United Kingdom
Duration: 17 Mar 202422 Mar 2024
https://www.eucap2024.org/

Publication series

NameEuropean Conference on Antennas and Propagation (EUCAP): proceedings
ISSN (Print)2164-3342

Conference

Conference18th European Conference on Antennas and Propagation 2024
Abbreviated titleEuCAP 2024
Country/TerritoryUnited Kingdom
CityGlasgow
Period17/03/202422/03/2024
Internet address

Fingerprint

Dive into the research topics of 'Leveraging radar back-scattered data for classification of imaging targets'. Together they form a unique fingerprint.

Cite this