【24h】

Sensor Data Fusion Using Kalman Filter

机译:使用卡尔曼滤波器的传感器数据融合

获取原文
获取原文并翻译 | 示例

摘要

This Many sensor devices are used for the navigation purposes in an aircraft. This paper proposes the fusion of two sensors namely RADAR and IRST data to improve the accuracy of the target location respectively. RADAR is of RF domain whereas IRST tracks the target in IR domain, both gives the target data in azimuth, elevation and range. Sensor data fusion is used to combine the advantages in both the sensors, i.e RADAR provides accurate range whereas LOS is not accurate. On the other hand IRST provides accurate LOS and range accuracy is ambiguous. Thus to avoid the ambiguity of both the sensors and to have a more accurate information of target the fusion of data from the sensors is done. Extended Kalman filter is used for the Sensor Data Fusion, as the estimates which are obtained from this statistical method is more accurate and nearer to the true value than the measured value, also fusion methods are compared.
机译:这许多传感器设备用于飞机中的导航目的。为了提高目标定位的准确性,本文提出了两种雷达雷达和IRST数据的融合。 RADAR属于RF域,而IRST则跟踪IR域中的目标,均以方位角,仰角和范围给出了目标数据。传感器数据融合用于组合两个传感器的优点,即RADAR提供准确的范围,而LOS不准确。另一方面,IRST提供了准确的LOS,并且范围精度不明确。因此,为了避免两个传感器的歧义性并且具有更准确的目标信息,完成了来自传感器的数据融合。扩展卡尔曼滤波器用于传感器数据融合,因为从这种统计方法获得的估计值比测量值更准确且更接近真实值,因此还对融合方法进行了比较。

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