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Using a Two-Dimensional Autoregressive Model for Interference Mitigation in FMCW Radar
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.ORCID iD: 0009-0005-1529-4130
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.ORCID iD: 0000-0003-0423-9927
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.ORCID iD: 0000-0003-3707-2780
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.ORCID iD: 0000-0002-6643-312X
2024 (English)In: Proceedings International Radar Symposium, IEEE Computer Society, 2024, p. 18-23Conference paper, Published paper (Refereed)
Abstract [en]

This work confronts the complex issue of cross-interference in Frequency Modulated Continuous Wave (FMCW) radars, a critical concern that has become more pronounced with the proliferation of automotive radar systems. The study intro-duces a two-dimensional autoregressive (AR) modeling technique for signal reconstruction in the time domain, tailored specifically for the textured nature of FMCW radar frames composed of fast- time (Range bin) and slow-time (Doppler bin) signals. According to the simulations conducted in this study, the proposed 2-D AR model (of order 3) exhibits superior performance compared to its 1-D counterpart (of order 5). This is evidenced by a slightly lower Mean Absolute Percentage Error (MAPE) during model training and a higher Signal-to-Interference-plus-Noise Ratio (SINR) for the reconstructed signal, suggesting that the 2-D model requires less frequent temporal sampling. The study further investigates different sampling strategies and evaluates the influence of model order on signal reconstruction. Based on these assessments, a third-order 2-D AR is recommended as a suitable trade-off model for interference mitigation of FMCW radars for the evaluated scenarios. This paper is structured as follows: Section I defines the interference problem in FM CW radars and the latest solutions to this problem are discussed. Sections II and III include the working principles of FMCW radar and theoretical backgrounds about multi-dimension auto-regressive modeling, respectively. Eventually, the mitigation techniques and numerical evaluations of the proposed approach are presented in Sections IV and V. © 2024 Warsaw University of Technology.

Place, publisher, year, edition, pages
IEEE Computer Society, 2024. p. 18-23
Series
Proceedings International Radar Symposium, ISSN 2155-5745, E-ISSN 2155-5753
Keywords [en]
Autoregressive, FMCW radar, Interference mitigation, Two-dimensional, Amplitude shift keying, Automotive radar, Doppler effect, Frequency shift keying, Image coding, Image segmentation, Pulse amplitude modulation, Radar simulators, Signal to noise ratio, Auto-regressive, Automotive radar system, Autoregressive modeling techniques, Autoregressive modelling, Cross interference, Frequency-modulated-continuous-wave radars, Signals reconstruction, Time domain, Radar interference
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:bth-26925ISI: 001307923500004Scopus ID: 2-s2.0-85203701423ISBN: 9788395602092 (print)OAI: oai:DiVA.org:bth-26925DiVA, id: diva2:1899557
Conference
2024 International Radar Symposium, IRS 2024, Wroclaw, July 2-4 2024
Available from: 2024-09-20 Created: 2024-09-20 Last updated: 2025-01-03Bibliographically approved

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Scopushttps://ieeexplore.ieee.org/document/10645042

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Joshani, MajidPalm, BrunaDahl, MattiasPettersson, Mats

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