{"title":"Maneuvering target tracking via dynamic-programming based Track-Before-Detect algorithm","authors":"Ziqian Wang, Jun Sun","doi":"10.1109/RADAR.2016.8059558","DOIUrl":null,"url":null,"abstract":"Owing to a high detection possibility and a simple kinetic model, track-before-detect (TBD) processorsare capable to detect low signal-to-noise ratio (SNR) targets uniformly moving with constant velocities. However, when a target with weak echo is accelerating, redirecting or decelerating, conventional TBD method might be ineffective for two reasons: heavier computational cost and higher possibility of forming false trajectories. In order to solve the problem of poor capability in tracking with the maneuvering targets, we propose a dynamic programming based TBD algorithm. In this TBD procedure, higher threshold is selected in order to reduce the possibility of forming false tracks during multi-frame processing. Additionally, resulted lower detection probability can be tolerated. The performance of tracking maneuvering objects based on this TBD processor is also exhibited.","PeriodicalId":245387,"journal":{"name":"2016 CIE International Conference on Radar (RADAR)","volume":"291 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 CIE International Conference on Radar (RADAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADAR.2016.8059558","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Owing to a high detection possibility and a simple kinetic model, track-before-detect (TBD) processorsare capable to detect low signal-to-noise ratio (SNR) targets uniformly moving with constant velocities. However, when a target with weak echo is accelerating, redirecting or decelerating, conventional TBD method might be ineffective for two reasons: heavier computational cost and higher possibility of forming false trajectories. In order to solve the problem of poor capability in tracking with the maneuvering targets, we propose a dynamic programming based TBD algorithm. In this TBD procedure, higher threshold is selected in order to reduce the possibility of forming false tracks during multi-frame processing. Additionally, resulted lower detection probability can be tolerated. The performance of tracking maneuvering objects based on this TBD processor is also exhibited.