【24h】

Research on ship tracking based on adaptive particle filter

机译:基于自适应粒子滤波的舰船跟踪研究

获取原文
获取原文并翻译 | 示例

摘要

Locating remote slow sea-surface targets with airborne radar is a problem of the non-linear and non-Gaussian state estimation, resulting in the deviation of the target location and the track jitter when dealing with tradition Kalman filter. In this paper, adaptive particle filter (APF) is used to solve the ship tracking problem under glint noise. The algorithm can choose the number of particles based on KLD-Sampling, which is efficient and has smaller time consumption. Computer simulation proves that adapti ve particle filter can track quickly sea-surface targets under glint noise, and the tracking performance is superior to that of standard particle filter (PF), so APF is practically valuable for engineering use.
机译:利用机载雷达定位远程慢海面目标是非线性和非高斯状态估计的问题,在处理传统的卡尔曼滤波器时会导致目标位置的偏差和航迹抖动。本文采用自适应粒子滤波器(APF)解决了闪烁噪声下的船舶跟踪问题。该算法可以根据KLD采样选择粒子数量,效率高且耗时少。计算机仿真表明,自适应粒子滤波器可以在闪烁噪声下快速跟踪海面目标,其跟踪性能优于标准粒子滤波器(PF),因此APF对于工程应用具有实用价值。

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