Performance Comparison of SAC Methods for Radar Dynamic Object Classification

The sample consensus (SAC) methods have become increasingly important in the field of radar-based dynamic object classification for applications such as ego-motion estimation and obstacle avoidance. This paper presents a comprehensive performance comparison of several SAC methods for classifying dynamic objects using radar data. Our extensive experiments show that each SAC method’s pros and cons, and provide insights into the effective use of SAC methods for radar-based dynamic object classification. It is expected that this study will help to increase the accuracy of dynamic object classification in real-world scenarios and guide future research in this area.