| 摘要: |
| 针对无人机飞行末段的飞行特点,提出了一种用战术空中导航系统(TACAN)辅助惯性导航系统(INS)、全球卫星定位系统(GPS)的新组合导航模式。详细推导了一种系数加权的联邦卡尔曼算法,并将此算法运用到SINS/GPS/TACAN组合导航中。通过融合导航系统的导航信息估计出组合导航系统的误差状态量,以提高导航系统定位精度。此算法不必计算加权矩阵,从而避免了求解滤波误差方差阵的逆矩阵,运算速度有所提高。仿真计算结果表明,该算法可抑制滤波发散,并提高导航系统的精度和速度,此组合导航模式有较好的容错性和环境适应性,具有实用价值。 |
| 关键词: 无人机,惯性导航,组合导航,数据融合,联邦卡尔曼滤波 |
| DOI：10.3969/j.issn.1001-893X. |
| 修订日期：2007-08-30 |
| 基金项目: |
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| Federated Kalman Filter Method for SINS/GPS/TACAN Integrated Navigation |
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| Abstract: |
| According to the characteristics of terminal stage of UAVs,a new integrated navigation mode adopting TACAN to assist INS and GPS is presented.Then a new coefficient-weighted Federated Kalman Filter algorithm is deduced in detail,and is applied to SINS/GPS/TACAN integrated navigation.By integrating the information of navigation,this algorithm could evaluate error estimation of integrated navigation system,to improe the location accuracy.This algorithm do not need to calculate weight matrix,and avoids calculating inverse matrix of the error variance matrix,so has faster calculation speed. The simulation results show that the method is effective to improve the precision and calculation speed of autonomous navigation system and to provide with better fault tolerance ability and adaptability. |
| Key words: UAV,inertial navigation,integrated navigation,data fusion,federated Kalman filter |
《电讯技术》编辑部 