Animation-driven Radar Across-section Optimization in Miniature Ultra-wideband Vehicle Radar Systems
DOI:
https://doi.org/10.63746/njtd.v22i4.3698Keywords:
UWB, RCS Optimization, Vehicular Radar Systems, Animation-Based Visualization, Object Detection and ClassificationAbstract
This study examines how to improve Radar Cross-Section (RCS) performance in small Ultra-Wideband (UWB) vehicle radars by using visual analysis methods to enhance radar effectiveness in automotive applications. The research uses MATLAB simulations to test and refine important factors like beam angle, operating frequency, and antenna gain, taking advantage of UWB technology's ability to detect objects with high precision. The study examines four different driving situations through 1,000 simulation runs each: detecting a single object ahead, detecting multiple objects in front, spotting objects at the roadside, and identifying vehicles during overtaking movements. The results show that carefully adjusted beam angles greatly improve detection accuracy, reaching 98.7% accuracy when detecting single objects directly ahead using 30°–60° beam width, 94.2% for multiple objects using beam widths of 90° or greater, and 87.5% for objects to the side using 90°–120° beam angles. Moving objects are easier to detect, with signal-to-noise ratios dropping from 90 dB to 18 dB over distances of 1-150 meters, while stationary objects show weaker performance with ratios falling from 32 dB to 10 dB over just 21-80 meters. The radar can detect objects up to 1 kilometer away under the best conditions, with average signal quality ranging from 24.1 dB when looking straight ahead to 18.9 dB when scanning to the sides. Visual mapping through color-coded displays helps identify areas where radar signals reflect poorly, allowing the system to adjust beam direction in real-time and improve overall radar design. The study shows that combining mathematical optimization techniques with visual feedback methods improves radar performance, achieving up to 91.8% detection success rates even in challenging situations where objects approach from multiple directions.
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