{"title":"带未解析测量的轨迹导向MHT","authors":"S. Coraluppi, C. Carthel","doi":"10.1109/SDF.2019.8916657","DOIUrl":null,"url":null,"abstract":"This paper first validates that the track-oriented multiple-hypothesis tracking recursion holds in the case of state-dependent detection probabilities, as is generally assumed. Next, we seek to extend the track-oriented multiple-hypothesis tracking recursion to allow for unresolved measurements. The formulation requires some simplifying assumptions, including an assumption that targets be resolved at birth and a restriction on the size of unresolved target clusters. The tracking recursion requires some approximation to admit track-oriented (factored) form, and leads to a nonlinear optimization problem. We discuss a multi-stage architecture that provides a simpler and more robust processing approach for practical settings.","PeriodicalId":186196,"journal":{"name":"2019 Sensor Data Fusion: Trends, Solutions, Applications (SDF)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Track-Oriented MHT with Unresolved Measurements\",\"authors\":\"S. Coraluppi, C. Carthel\",\"doi\":\"10.1109/SDF.2019.8916657\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper first validates that the track-oriented multiple-hypothesis tracking recursion holds in the case of state-dependent detection probabilities, as is generally assumed. Next, we seek to extend the track-oriented multiple-hypothesis tracking recursion to allow for unresolved measurements. The formulation requires some simplifying assumptions, including an assumption that targets be resolved at birth and a restriction on the size of unresolved target clusters. The tracking recursion requires some approximation to admit track-oriented (factored) form, and leads to a nonlinear optimization problem. We discuss a multi-stage architecture that provides a simpler and more robust processing approach for practical settings.\",\"PeriodicalId\":186196,\"journal\":{\"name\":\"2019 Sensor Data Fusion: Trends, Solutions, Applications (SDF)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Sensor Data Fusion: Trends, Solutions, Applications (SDF)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SDF.2019.8916657\",\"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 Sensor Data Fusion: Trends, Solutions, Applications (SDF)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SDF.2019.8916657","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper first validates that the track-oriented multiple-hypothesis tracking recursion holds in the case of state-dependent detection probabilities, as is generally assumed. Next, we seek to extend the track-oriented multiple-hypothesis tracking recursion to allow for unresolved measurements. The formulation requires some simplifying assumptions, including an assumption that targets be resolved at birth and a restriction on the size of unresolved target clusters. The tracking recursion requires some approximation to admit track-oriented (factored) form, and leads to a nonlinear optimization problem. We discuss a multi-stage architecture that provides a simpler and more robust processing approach for practical settings.