...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IEEE Transactions on Automatic Control >Chandrasekhar-Based Maximum Correntropy Kalman Filtering With the Adaptive Kernel Size Selection
【24h】

Chandrasekhar-Based Maximum Correntropy Kalman Filtering With the Adaptive Kernel Size Selection

机译：基于ChandraseKhar的最大矫正器Kalman滤波与自适应内核大小选择

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This technical note is aimed to derive the Chandrasekhar-type recursion for the maximum correntropy criterion (MCC) Kalman filtering (KF). For the classical KF, the first Chandrasekhar difference equation was proposed at the beginning of 1970s. This is the alternative to the traditionally used Riccati recursion and it yields the so-called fast implementations known as the Morf-Sidhu-Kailath-Sayed KF algorithms. They are proved to be computationally cheap because of propagating the matrices of a smaller size than nx n error covariance matrix in the Riccati recursion. The problem of deriving the Chandrasekhar-type recursion within the MCC estimation methodology has never been raised yet in engineering literature. In this technical note, we do the first step and derive the Chandrasekhar MCC-KF estimators for the case of adaptive kernel size selection strategy, which implies a constant scalar adjusting weight. Numerical examples substantiate a practical feasibility of the newly suggested MCC-KF implementations and correctness of the presented theoretical derivations.
机译：本技术说明旨在为最大正轮堆标准（MCC）卡尔曼滤波（KF）导出ChandraseKhar型递归。对于古典的KF，在20世纪70年代初提出了第一个ChandraseKhar差异方程。这是传统上使用的Riccati递归的替代方法，它产生了称为Morf-Sidhu-Kailath的KF算法的所谓快速实现。由于在RicCATI递归中传播比NX N误差协方差矩阵的较小尺寸的矩阵传播矩阵的矩阵，因此它们被证明是廉价的。在MCC估计方法内导出的ChandraseKhar型递归的问题从未在工程文献中提出过。在这本技术说明中，我们进行第一步，并为自适应内核尺寸选择策略的情况推导出ChandraseKhar MCC-KF估计，这意味着恒定的标量调整重量。数值示例证实了新建议的MCC-KF实现的实际可行性和所提出的理论衍生的正确性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号