{"title":"Multi hypothesis parameter tracking in relative time of arrival","authors":"C. Degen, F. Govaers, W. Koch","doi":"10.1109/SDF.2013.6698252","DOIUrl":null,"url":null,"abstract":"The passive non-cooperative localization and tracking of mobile terminals in urban scenarios, called blind mobile localization (BML), is a highly demanding task which occurs for instance in safety, emergency and security applications. In BML the measurement set consists out of several multipaths which are usually parametrized by their direction of arrival (DoA) and their relative time of arrival (RToA). Clutter multipaths can occur due to obstacles like pedestrians, cars, etc. near the receiver side. If a clutter multipath is received before the first measurement of a target, i.e., if it possesses a negative RToA compared to the target related measurements, the computation of the particular likelihood function is deteriorated and thus the accuracy of any BML fusion algorithm decreases. In this paper a pre-processing of the measurement set by an application of a multi-hypothesis tracking (MOT) in the parameter space is proposed. Therefore, two extensions of the MOT-approach processing additional global clutter hypothesis are derived. Finally, a ray-tracing simulation is used to numerically assess the proposed methods for different clutter levels in terms of the optimal subpattern assignment (OSPA) metric.","PeriodicalId":228075,"journal":{"name":"2013 Workshop on Sensor Data Fusion: Trends, Solutions, Applications (SDF)","volume":"175 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Workshop on Sensor Data Fusion: Trends, Solutions, Applications (SDF)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SDF.2013.6698252","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The passive non-cooperative localization and tracking of mobile terminals in urban scenarios, called blind mobile localization (BML), is a highly demanding task which occurs for instance in safety, emergency and security applications. In BML the measurement set consists out of several multipaths which are usually parametrized by their direction of arrival (DoA) and their relative time of arrival (RToA). Clutter multipaths can occur due to obstacles like pedestrians, cars, etc. near the receiver side. If a clutter multipath is received before the first measurement of a target, i.e., if it possesses a negative RToA compared to the target related measurements, the computation of the particular likelihood function is deteriorated and thus the accuracy of any BML fusion algorithm decreases. In this paper a pre-processing of the measurement set by an application of a multi-hypothesis tracking (MOT) in the parameter space is proposed. Therefore, two extensions of the MOT-approach processing additional global clutter hypothesis are derived. Finally, a ray-tracing simulation is used to numerically assess the proposed methods for different clutter levels in terms of the optimal subpattern assignment (OSPA) metric.
城市场景下移动终端的被动非合作定位与跟踪被称为盲目性移动定位(blind mobile localization, BML),是一项要求很高的任务,经常出现在安全、应急、安防等应用中。在BML中,测量集由多个多路径组成,这些多路径通常由它们的到达方向(DoA)和相对到达时间(RToA)参数化。杂波多路径可能由于接收器侧附近的行人、汽车等障碍物而发生。如果在目标的第一次测量之前接收到杂波多径,即与目标相关的测量相比具有负的RToA,则会使特定似然函数的计算变差,从而降低任何BML融合算法的精度。提出了一种在参数空间中应用多假设跟踪(MOT)对测量集进行预处理的方法。因此,对mot方法处理附加全局杂波假设进行了两种扩展。最后,通过射线追踪仿真对不同杂波水平下的最优子图分配度量进行了数值评价。