{"title":"超视距雷达多目标跟踪的随机样本一致性算法","authors":"Hua Lan, Zhishan Zhang, ZengfuWang, Q. Pan","doi":"10.23919/IRS.2017.8008099","DOIUrl":null,"url":null,"abstract":"Multiple target tracking in over-the-horizon radar (OTHR) suffers from two major challenges due to the multipath propagation phenomenon. The first is multipath detection that detects appearing and disappearing targets automatically, while one target may produce s tracks for s propagation paths. The second is multipath tracking that calculates the target-to-measurement-to-path assignment matrices to estimate target states, which is computationally intractable due to the combinatorial explosions. A joint multipath target detection and tracking method is proposed based on random sample consensus (RANSAC). Using the iterative hypothesize-and-test framework of RANSAC, the close loop between identification of target-to-measurement-to-path and estimation of target states is established, which is conducive to improving the tracking performance by utilizing multipath measurements. Numerical simulations demonstrate the effectiveness of the proposed method.","PeriodicalId":430241,"journal":{"name":"2017 18th International Radar Symposium (IRS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Random sample consensus algorithm for multiple target tracking in over-the-horizon radar\",\"authors\":\"Hua Lan, Zhishan Zhang, ZengfuWang, Q. Pan\",\"doi\":\"10.23919/IRS.2017.8008099\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multiple target tracking in over-the-horizon radar (OTHR) suffers from two major challenges due to the multipath propagation phenomenon. The first is multipath detection that detects appearing and disappearing targets automatically, while one target may produce s tracks for s propagation paths. The second is multipath tracking that calculates the target-to-measurement-to-path assignment matrices to estimate target states, which is computationally intractable due to the combinatorial explosions. A joint multipath target detection and tracking method is proposed based on random sample consensus (RANSAC). Using the iterative hypothesize-and-test framework of RANSAC, the close loop between identification of target-to-measurement-to-path and estimation of target states is established, which is conducive to improving the tracking performance by utilizing multipath measurements. Numerical simulations demonstrate the effectiveness of the proposed method.\",\"PeriodicalId\":430241,\"journal\":{\"name\":\"2017 18th International Radar Symposium (IRS)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 18th International Radar Symposium (IRS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/IRS.2017.8008099\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 18th International Radar Symposium (IRS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/IRS.2017.8008099","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Random sample consensus algorithm for multiple target tracking in over-the-horizon radar
Multiple target tracking in over-the-horizon radar (OTHR) suffers from two major challenges due to the multipath propagation phenomenon. The first is multipath detection that detects appearing and disappearing targets automatically, while one target may produce s tracks for s propagation paths. The second is multipath tracking that calculates the target-to-measurement-to-path assignment matrices to estimate target states, which is computationally intractable due to the combinatorial explosions. A joint multipath target detection and tracking method is proposed based on random sample consensus (RANSAC). Using the iterative hypothesize-and-test framework of RANSAC, the close loop between identification of target-to-measurement-to-path and estimation of target states is established, which is conducive to improving the tracking performance by utilizing multipath measurements. Numerical simulations demonstrate the effectiveness of the proposed method.