首页> 外文会议>System Theory (SSST 2010), 2010 >A comparative study of nonlinear filters for target tracking in mixed coordinates
【24h】

A comparative study of nonlinear filters for target tracking in mixed coordinates

机译:混合坐标系下用于目标跟踪的非线性滤波器的比较研究

获取原文

摘要

The measurement model nonlinearity is a major challenge in target tracking. This paper presents a comparative performance study of seven nonlinear filters in handling the measurement model nonlinearity. They are: the extended Kalman filter, the unscented filter, the second order divided-differences filter, the Gauss-Hermite quadrature filter, the two-step Kalman filter, the Gaussian particle filter, and the linear minimum mean-square error tracking filter with polar measurements. Comprehensive performance evaluation and comparison of all of the above mainstream nonlinear filters over the same tracking scenarios are conducted via Monte Carlo simulation. The results can facilitate the choice and design of nonlinear tracking filters in mixed coordinates.
机译:测量模型的非线性是目标跟踪的主要挑战。本文介绍了七个非线性滤波器在处理测量模型非线性方面的比较性能研究。它们是:扩展卡尔曼滤波器,无味滤波器,二阶除差滤波器,高斯-赫尔姆特正交滤波器,两步卡尔曼滤波器,高斯粒子滤波器以及具有极地测量。通过蒙特卡洛模拟,对相同跟踪情况下的所有上述主流非线性滤波器进行了综合性能评估和比较。结果可以促进混合坐标系中非线性跟踪滤波器的选择和设计。

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