Road Users Classification Based on Bi-Frame Micro-Doppler with 24-GHz FMCW Radar
Permanent link to this recordhttp://hdl.handle.net/10754/668953
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AbstractRadar sensors hold excellent capabilities to estimate distance and motion accu- rately, penetrate nonmetallic objects, and remain unaffected by weather conditions. These capabilities make these devices extremely flexible in their applications. Elec- tromagnetic waves centered at frequencies around 24 GHz offer high precision target measurements, compact antenna and circuitry design, and lower atmospheric absorp- tion than higher frequency-based systems. This thesis presents a case study for a 24 GHz frequency modulated continuous wave radar module. We start by addressing the theoretical background necessary for this work and describing the architecture of the module used. We present three classes’ classification accuracy, namely pedes- trians, cyclists, and cars. A set of features for the classification is designed based on theoretical models, and their effectiveness is validated through experiments. The features are extracted from the available geometrical and motion-related information and used to train different classification models to compare the results. Finally, a trade-off between feature number and accuracy is presented.
CitationCoppola, R. (2021). Road Users Classification Based on Bi-Frame Micro-Doppler with 24-GHz FMCW Radar. KAUST Research Repository. https://doi.org/10.25781/KAUST-X10N1