Detection and tracking of the trajectories of dynamic UAVs in restricted and cluttered environment
作者：
Highlights：
• A novel smoothing data association idea in the LM-IPDA algorithm.
• The significant detection and tracking performance of UAV are analyzed by experiment.
• Backward multi-tracks are used to estimate a forward track in past scan for smoothing.
• False-track discrimination is obtained using smoothing target existence probability.
• The algorithm reduces RMS errors, and tracks multi-vehicles in clutter efficiently.
摘要
•A novel smoothing data association idea in the LM-IPDA algorithm.•The significant detection and tracking performance of UAV are analyzed by experiment.•Backward multi-tracks are used to estimate a forward track in past scan for smoothing.•False-track discrimination is obtained using smoothing target existence probability.•The algorithm reduces RMS errors, and tracks multi-vehicles in clutter efficiently.
论文关键词：Detection,Estimation,False-track discrimination (FTD),Smoothing,Tracking,Targets existence,UAV
论文评审过程：Received 24 March 2020, Revised 21 April 2021, Accepted 30 May 2021, Available online 5 June 2021, Version of Record 11 June 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.115309
