Linxi Wang, Xiaoxi Hu, Xun Han, Yin Kuang, Xinquan Yang
{"title":"基于AGMM-PHD的多目标跟踪算法","authors":"Linxi Wang, Xiaoxi Hu, Xun Han, Yin Kuang, Xinquan Yang","doi":"10.1109/ICCC47050.2019.9064290","DOIUrl":null,"url":null,"abstract":"Aiming at the problem that traditional tracking algorithms can not effectively track maneuvering multi-target in clutter environment, a new maneuvering multi-target tracking algorithm is proposed in this paper. By combining the Adaptive Grid method with the PHD filtering algorithm, the adaptive adjustment of the model set is realized, so that the tracking algorithm can adapt to the state change of the maneuvering targets. The simulation results show that, compared with the traditional fixed structure multi-model tracking algorithm, the algorithm proposed in this paper has better tracking performance and higher cost-effectiveness ratio. It has broad application prospects in multi-target tracking.","PeriodicalId":6739,"journal":{"name":"2019 IEEE 5th International Conference on Computer and Communications (ICCC)","volume":"228 1","pages":"322-326"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Multi-target Tracking Algorithm Based on AGMM-PHD\",\"authors\":\"Linxi Wang, Xiaoxi Hu, Xun Han, Yin Kuang, Xinquan Yang\",\"doi\":\"10.1109/ICCC47050.2019.9064290\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at the problem that traditional tracking algorithms can not effectively track maneuvering multi-target in clutter environment, a new maneuvering multi-target tracking algorithm is proposed in this paper. By combining the Adaptive Grid method with the PHD filtering algorithm, the adaptive adjustment of the model set is realized, so that the tracking algorithm can adapt to the state change of the maneuvering targets. The simulation results show that, compared with the traditional fixed structure multi-model tracking algorithm, the algorithm proposed in this paper has better tracking performance and higher cost-effectiveness ratio. It has broad application prospects in multi-target tracking.\",\"PeriodicalId\":6739,\"journal\":{\"name\":\"2019 IEEE 5th International Conference on Computer and Communications (ICCC)\",\"volume\":\"228 1\",\"pages\":\"322-326\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 5th International Conference on Computer and Communications (ICCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCC47050.2019.9064290\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 5th International Conference on Computer and Communications (ICCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCC47050.2019.9064290","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Multi-target Tracking Algorithm Based on AGMM-PHD
Aiming at the problem that traditional tracking algorithms can not effectively track maneuvering multi-target in clutter environment, a new maneuvering multi-target tracking algorithm is proposed in this paper. By combining the Adaptive Grid method with the PHD filtering algorithm, the adaptive adjustment of the model set is realized, so that the tracking algorithm can adapt to the state change of the maneuvering targets. The simulation results show that, compared with the traditional fixed structure multi-model tracking algorithm, the algorithm proposed in this paper has better tracking performance and higher cost-effectiveness ratio. It has broad application prospects in multi-target tracking.