Performance Analysis of Highway Vehicle Tracking Using Different Object Trackers

Abstract

Radar is a crucial technology widely used across various sectors, including the military, defense, space exploration, environmental monitoring, and traffic control. This paper presents advancements in radar technology, focusing on extended object tracking and multipath radar reflections to enhance tracking and classification accuracy in challenging environments such as heavy rain, fog, and dense traffic. We explore two main systems: the first employs parametric variation in object tracking to reduce false alarms and errors, significantly improving the tracking performance. The second system leverages multipath radar reflections, where parametric adjustments have led to a notable increase in target detection accuracy (91.42%). This improvement is particularly vital for applications requiring precise target identification, such as autonomous driving and vehicle tracking, ensuring safer and more efficient operations. Our results demonstrate the effectiveness of parametric modeling in optimizing radar systems for better reliability and robustness in diverse applications. This research contributes to the development of safer transportation systems and more accurate environmental sensing, showcasing the potential of advanced radar technologies in addressing real-world challenges