摘要
北斗与GPS或其他类型导航设备可构成组合导航系统,为无人飞行器提供高精度、高可靠导航信息。在处理动态导航数据采用"当前"统计模型(CS模型)并利用标准Kalman滤波方法时,系统动态噪声和观测噪声未知且时变,而且加速度上下限值不能自适应于未知运动规律的无人飞行器当前加速度,导致导航精度降低。为此,提出一种适应于飞行器运动状态的改进自适应算法,并应用于北斗/GPS动态导航系统中。实验仿真验证了该算法能有效提高组合导航系统的精度和可靠性,并能更好地自适应于无人飞行器的机动特性。
Compass can constitute integrated navigation system which provides high-precision, highly reliable information for un- manned aerial vehicle（UAV） with GPS or other types of navigation equipments. When using current statistical model（CS model） and standard Kalman filter to deal with dynamic navigation data, dynamic noise and observation noise was unknown and time-varying, and limits of acceleration couldn＇t be adaptive to the current acceleration of UAV. All of these has resulted in low navigation accuracy. To solve the problem, the paper presents an improved adaptive algorithm which adapts to UAV＇s motion, and applies to Compass/GPS dynamic navigation system. The simulation shows that it can effectively improve the accuracy and reliability, and adapt to the maneuvering characteristics of UAV better.
出处
《电子技术应用》
北大核心
2015年第10期58-61,共4页
Application of Electronic Technique
基金
国家自然科学基金(61361006)
广西自动检测技术与仪器重点实验室基金项目(YQ14203)
广西高校无人机遥测重点实验室(WRJ2015ZR02)
关键词
北斗
GPS
组合导航
无人飞行器
自适应算法
Compass
GPS
integrated navigation
unmanned aerial vehicle
adaptive algorithm
