{"title":"Track quality estimation for multiple-target tracking radars","authors":"T. W. Jeffrey","doi":"10.1109/NRC.1989.47619","DOIUrl":null,"url":null,"abstract":"A method is developed for estimating track quality for a multiple-target tracking radar, such as an electronically scanned array radar or track-while-scan system. It is assumed that tracking error residuals and error variance estimates are available, as is the case when minimum-variance track filters are used. A normalized distance function is selected as the direct measure of a target's instantaneous track quality. It is smoothed using a recursive fading memory filter to provide an estimate of track quality. A statistical hypothesis test is then applied to the track quality estimates to determine when target tracks have achieved a specified quality for the given application. This procedure can be implemented for each target in track, and it uses only data already required by the return-to-track association algorithms used by many multiple-target tracking radars. In addition, the technique is applicable to both active and passive radar operation, and it can easily be extended to incorporate alternate or additional quality criteria.<<ETX>>","PeriodicalId":167059,"journal":{"name":"Proceedings of the IEEE National Radar Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1989-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the IEEE National Radar Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NRC.1989.47619","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
A method is developed for estimating track quality for a multiple-target tracking radar, such as an electronically scanned array radar or track-while-scan system. It is assumed that tracking error residuals and error variance estimates are available, as is the case when minimum-variance track filters are used. A normalized distance function is selected as the direct measure of a target's instantaneous track quality. It is smoothed using a recursive fading memory filter to provide an estimate of track quality. A statistical hypothesis test is then applied to the track quality estimates to determine when target tracks have achieved a specified quality for the given application. This procedure can be implemented for each target in track, and it uses only data already required by the return-to-track association algorithms used by many multiple-target tracking radars. In addition, the technique is applicable to both active and passive radar operation, and it can easily be extended to incorporate alternate or additional quality criteria.<>