...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Signal Processing, IET >Alternative framework for the iterated unscented Kalman filter
【24h】

Alternative framework for the iterated unscented Kalman filter

机译：迭代的无味卡尔曼滤波器的替代框架

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

The iterated version of a family of non-linear Kalman filters, named the unscented transform (UT) based unscented Kalman filters (UKF), are revisited. Two existing frameworks of the iterated UKF are analysed and some shortcomings of them are pointed out. A new framework is proposed based on the statistical linear regression (SLR) perspective of the UT and the framework of the iterated extended Kalman filter (IEKF). The virtue of the proposed framework is twofold: first, the observation equation is linearised strictly following the SLR perspective implying that the regression error is also considered; second, it strictly follows the framework of the IEKF implying that in each iteration, the linearised equation is used to correct the a priori estimate rather than the latest estimate. A simple but illustrative benchmark example is simulated to check the feasibility of the proposed framework, and the results demonstrate the efficacy of the proposed framework.
机译：再次介绍了非线性卡尔曼滤波器家族的迭代版本，该版本称为基于无味变换（UT）的无味卡尔曼滤波器（UKF）。分析了迭代UKF的两个现有框架，并指出了它们的一些缺点。基于UT的统计线性回归（SLR）观点和迭代扩展卡尔曼滤波器（IEKF）的框架，提出了一个新的框架。所提出框架的优点是双重的：首先，严格按照SLR观点线性化观测方程，这意味着还考虑了回归误差。其次，它严格遵循IEKF的框架，这意味着在每次迭代中，线性化方程均用于校正先验估计而不是最新估计。模拟了一个简单但说明性的基准示例，以检查所提出框架的可行性，结果证明了所提出框架的有效性。

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