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The extended preferred ordering theorem for radar tracking using the extended Kalman filter.

机译：使用扩展卡尔曼滤波器进行雷达跟踪的扩展首选排序定理。

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摘要

A certain problem in nonlinear estimation exists in radar tracking. Usually radar detections provide instantaneous position measurements in radar (polar) coordinates at discrete times, while tracks (estimated positions and motions over continuous time) are determined in rectangular coordinates; and the linear Kalman filter (LKF) is used as the estimator. Less common, the LKF is used to determine the tracks in radar coordinates, which are then converted into rectangular coordinates. Rarely is the extended Kalman filter (EKF) used, where the tracks are directly determined in rectangular coordinates from the radar detections via a local linearization. And so most radar tracks tend to be biased---and their Kalman covariance matrices are inconsistent with the true ones. Of course, some techniques have been proposed for "debiasing" them and making their mean squared errors "consistent" with the covariance matrices determined by the tracking filter. It is shown here, however, that the leading one for debiasing the LKF can make the biases worse; and a remedy for that is provided. But the focus is upon the EKF. In an earlier work by this author---dubbed the Preferred Ordering Theorem (POT)---it was shown that the linearization errors in range of the EKF can be virtually eliminated by using the measurement components of a detection recursively in a certain order: azimuth first and range last. But that has a fundamental limitation, namely, that "preferred" order. And so here a new version is provided, dubbed the Extended-POT (EPOT). Not only can the EPOT be more efficient than the POT in certain settings, but under it the measurements may be used in any order with virtually the same results.
机译：雷达跟踪中存在非线性估计中的一个问题。通常，雷达检测可在离散时间在雷达（极坐标）中提供瞬时位置测量，而轨迹（在连续时间内的估计位置和运动）则在直角坐标中确定；线性卡尔曼滤波器（LKF）用作估计量。不太常见的是，LKF用于确定雷达坐标中的航迹，然后将其转换为直角坐标。很少使用扩展的卡尔曼滤波器（EKF），其中通过本地线性化从雷达检测直接在直角坐标中确定轨迹。因此，大多数雷达航迹往往会产生偏差-并且它们的卡尔曼协方差矩阵与真实的矩阵不一致。当然，已经提出了一些技术来“消偏”它们并使它们的均方误差与由跟踪滤波器确定的协方差矩阵“一致”。但是，这里显示的是，对LKF进行去偏斜的领先方法会使偏见更严重。并为此提供了补救措施。但是重点是EKF。在作者更早的工作中-被称为“首选订购定理（POT）”-表明，通过以一定顺序递归使用检测的测量分量，可以消除EKF范围内的线性化误差。 ：首先是方位角，最后是范围。但这有一个基本限制，即“优先”顺序。因此，这里提供了一个新版本，称为Extended-POT（EPOT）。在某些设置下，EPOT不仅比POT更有效率，而且在其下，可以按任何顺序使用测量，结果几乎相同。

著录项

  • 作者

    Leskiw, Donald Myron.;

  • 作者单位

    Syracuse University.;

  • 授予单位 Syracuse University.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2011
  • 页码 143 p.
  • 总页数 143
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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