Ground-Based Radar Tracking of Ballistic Target on Re-entry Phase Using Derivative-Free Filters

2006 Annual IEEE India Conference Pub Date : 2006-09-01 DOI:10.1109/INDCON.2006.302781

M. Srinivasan, S. Sadhu, T. Kumar Ghoshal

{"title":"Ground-Based Radar Tracking of Ballistic Target on Re-entry Phase Using Derivative-Free Filters","authors":"M. Srinivasan, S. Sadhu, T. Kumar Ghoshal","doi":"10.1109/INDCON.2006.302781","DOIUrl":null,"url":null,"abstract":"Radar tracking of a ballistic target in re-entry phase has been considered in this paper. The motion of the target is evaluated with the assumptions that the drag and gravity are the only forces acting on the ballistic target after it enters into the endo-atmospheric phase. With unknown ballistic coefficient, the problem is actually a case for combined state and parameter estimation. After around 1997 the central or divided difference filter was developed for nonlinear stochastic estimation, which is a derivative-free filter and takes care of the second term of Taylor series expansion. The performance of the CDF is expected to be considerably better than the EKF and close to the UKF. This paper addresses the quantitative aspects of the improvement of performance. In particular, using Monte Carlo runs, the performance of the CDF has been compared with that of the EKF, standard UKF and Square Root UKF. While the performance of the CDF is comparable with the UKF, the CDF has a higher computational efficiency compared to the UKF. These features make it one of a strong candidate for on-line implementation in ground based radar tracking","PeriodicalId":122715,"journal":{"name":"2006 Annual IEEE India Conference","volume":"159 12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 Annual IEEE India Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDCON.2006.302781","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 5

Abstract

Radar tracking of a ballistic target in re-entry phase has been considered in this paper. The motion of the target is evaluated with the assumptions that the drag and gravity are the only forces acting on the ballistic target after it enters into the endo-atmospheric phase. With unknown ballistic coefficient, the problem is actually a case for combined state and parameter estimation. After around 1997 the central or divided difference filter was developed for nonlinear stochastic estimation, which is a derivative-free filter and takes care of the second term of Taylor series expansion. The performance of the CDF is expected to be considerably better than the EKF and close to the UKF. This paper addresses the quantitative aspects of the improvement of performance. In particular, using Monte Carlo runs, the performance of the CDF has been compared with that of the EKF, standard UKF and Square Root UKF. While the performance of the CDF is comparable with the UKF, the CDF has a higher computational efficiency compared to the UKF. These features make it one of a strong candidate for on-line implementation in ground based radar tracking

查看原文本刊更多论文

基于无导数滤波器的弹道目标再入段地基雷达跟踪

研究了弹道导弹再入段目标的雷达跟踪问题。在弹道目标进入大气层后，假设阻力和重力是作用在目标上的唯一作用力，以此来评估目标的运动。在弹道系数未知的情况下，该问题实际上是一种状态估计与参数估计相结合的情况。大约在1997年之后，用于非线性随机估计的中心或分差滤波器被开发出来，它是一种无导数滤波器，负责泰勒级数展开的第二项。CDF的表现预计将大大优于EKF，并接近UKF。本文讨论了绩效改进的定量方面。特别是，使用蒙特卡罗运行，将CDF的性能与EKF、标准UKF和平方根UKF进行了比较。虽然CDF的性能与UKF相当，但与UKF相比，CDF的计算效率更高。这些特点使其成为地面雷达跟踪在线实现的有力候选者之一

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

2006 Annual IEEE India Conference

自引率

0.00%

发文量