Research on Lightweight Vehicle Classification and Trajectory Reconstruction Based on Distributed Acoustic Sensing Arrays

Vehicle detection and trajectory reconstruction are core tasks in the field of intelligent transportation perception. Traditional traffic monitoring methods face bottlenecks such as high costs and difficult maintenance when deployed on a large scale. Distributed acoustic sensing technology has attracted much attention due to its non-invasive installation and all-weather working capabilities. However, existing vehicle classification methods based on acoustic signals have redundant parameters and high computational costs, making it difficult to meet the real-time inference needs at the edge; The trajectory reconstruction algorithm lacks adaptability to array configuration and noisy environments. In response to the above issues, this article proposes a joint algorithm framework for vehicle lightweight classification and trajectory reconstruction based on distributed acoustic sensing arrays.