An Artificial Neural Network Based Target Angle Estimation Technique for FMCW MIMO Radars

Basit Öğe Kaydı
dc.contributor.authorAkçapınar, Kudret
dc.contributor.authorÖnhon, Naime Özben
dc.contributor.authorGürbüz, Özgür
dc.date.accessioned2025-02-20T08:46:31Z
dc.date.available2025-02-20T08:46:31Z
dc.date.issued2023
dc.departmentTürk-Alman Üniversitesien_US
dc.description.abstract—In this paper, an artificial neural network (ANN) based approach is proposed for the estimation of the target angle using Multiple Input Multiple Output (MIMO) radars operating in Frequency Modulated Continuous Wave (FMCW). The proposed technique operates in two stages, with the first stage being the formation of the range profile at each MIMO element via Discrete Fourier Transform (DFT) and the second stage being the estimation of the target azimuth angle via an artificial neural network. The range profile formed in the first stage is fed to the second stage as a single snapshot angle measurement. The performance of the proposed technique is apprised with other existing methods under different Signal-to-Noise Ratio (SNR) conditions and measurement model uncertainties. The simulations performed show that the learning capability of the model strongly hinges on SNR conditions, and the learning process is ameliorated as SNR in training data increases as anticipated. Under low SNR conditions, the proposed technique performs better than other techniques in terms of Mean Square Error (MSE). We have also shown that our solution remains unaffected by the model uncertainties as it fully relies on the calibration data, while the performance of the model-based angle estimation techniques dramatically degrades as the uncertainty in the underlying model grows. © 2023, Electromagnetics Academy. All rights reserved.
dc.identifier.doi10.2528/PIERC23012305
dc.identifier.endpage130en_US
dc.identifier.issn1937-8718
dc.identifier.scopus2-s2.0-85164273748
dc.identifier.scopusqualityQ3
dc.identifier.startpage119en_US
dc.identifier.urihttps://doi.org/10.2528/PIERC23012305
dc.identifier.urihttps://hdl.handle.net/20.500.12846/1769
dc.identifier.volume134en_US
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElectromagnetics Academy
dc.relation.ispartofProgress In Electromagnetics Research C
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_Scopus_20250220
dc.subjectDiscrete Fourier transformsen_US
dc.subjectFrequency estimationen_US
dc.subjectFrequency modulationen_US
dc.subjectLearning systemsen_US
dc.subjectMean square erroren_US
dc.subjectMIMO radaren_US
dc.subjectMIMO systemsen_US
dc.subjectSignal to noise ratioen_US
dc.subjectUncertainty analysisen_US
dc.subjectAngle estimationen_US
dc.subjectConditionen_US
dc.subjectEstimation techniquesen_US
dc.subjectFrequency modulated continous wavesen_US
dc.subjectModeling uncertaintiesen_US
dc.subjectMultiple-input multiple-output radarsen_US
dc.subjectNetwork-baseden_US
dc.subjectPerformanceen_US
dc.subjectRange-profilesen_US
dc.subjectTarget angleen_US
dc.subjectNeural networksen_US
dc.titleAn Artificial Neural Network Based Target Angle Estimation Technique for FMCW MIMO Radars
dc.typeArticle

Dosyalar

Koleksiyon

Scopus İndeksli Yayınlar Koleksiyonu