区域导航无人机空中基准站的多源信息融合容错导航系统研究

Research on Multi Information Fusion and Fault Tolerant Navigation System of Air Reference Station Based on UAVs in Regional Navigation

作为卫星导航系统的补充和备份,区域导航服务系统近年来得到较大发展。在基于无人机的区域导航服务系统中,无人机自身的定位精度对区域导航服务系统的可靠运行有直接的影响。针对无人机导航传感器及系统的容错和可靠性问题,设计了具有针对性和自优化功能的多源信息融合容错导航方案,提出了一种优化的基于矢量分配形式的自适应联邦滤波算法。通过对每个状态量设计不同的信息分配系数,实现传感器量测噪声的动态优化调整,有效减小了传感器故障对融合导航系统的影响,提高了无人机导航系统的鲁棒性。验证分析表明,该方法可以减小子滤波器故障信息对融合导航系统联邦滤波全局估计的影响,避免了故障子滤波器在信息重置过程中对系统造成的污染,提高和保障了无人机空中基准站多源信息融合导航系统的稳定性和可靠性。

As a supplement and backup of GNSS,regional navigation system has been greatly developed in recent years.In the regional navigation system based on UAV,the positioning accuracy of UAV has a direct impact on the reliability of the regional navigation system.In order to improve the performance of UAV in a navigation system,a fault-tolerant navigation scheme for multi information fusion based on two-state chi-square detection is designed,and an adaptive federated filtering algorithm using vector-formed information distribution is proposed.The dynamic adjustment of measurement noise is realized by using different information distribution coefficients for each state variable,which effectively reduces the influence of sensor fault and improves the robustness of the integrated navigation system.The simulation results show that this method can reduce the influence of fault information on the global estimation of federated filter,and improve the robustness of the UAV’s integrated navigation system.