Urban Traffic Imaging Using Millimeter-Wave Radar
نویسندگان
چکیده
Imaging technology enhances radar environment awareness. can provide richer target information for traffic management systems than conventional detection radar. However, there is still a lack of research on millimeter-wave imaging urban surveillance. To solve the above problem, we propose an improved three-dimensional FFT algorithm architecture roadside in scenarios, enabling concurrence dynamic and static targets imaging. Firstly, by analyzing characteristics background noise scenes, Monte-Carlo-based constant false alarm (MC-CFAR) MC-CFAR are proposed, respectively, moving vehicles environmental detection. Then, velocity ambiguity solution problem with multiple large cycles, Hypothetical Phase Compensation (HPC-SNR) proposed complimented. Further, Density-Based Spatial Clustering Applications Noise (DBSCAN) used to remove outliers obtain clean point cloud image. Finally, within 50 m range presented as two-dimensional (2D) In addition, also try estimate vehicle type size, its accuracy reaches more 80% sparse condition. The method verified actual scenario data collected system installed roadside. work support further intelligent transportation extend applications.
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2022
ISSN: ['2315-4632', '2315-4675']
DOI: https://doi.org/10.3390/rs14215416