BDS复杂场景自适应导航数据融合算法

BDS adaptive navigation data fusion algorithm of complex scenes

针对在实际复杂场景下,北斗卫星导航系统(BDS)导航定位精度不足的问题,提出1种基于多传感器导航数据融合算法:设计基于层次分析法(AHP)的多传感器多场景的权重最优决策方法,各传感器的权重能够随着场景的变化而自适应变化,并利用各传感器在不同场景下的定位优势,获得实时的高精度导航数据。实验结果表明,通过多传感器导航数据融合,能够弥补单传感器部分场景下定位精度不足的问题,并在现有的传感器定位效果下,最大限度地提升整体导航的定位性能。统计得出在基于层次分析法的自适应数据融合(ADF)下,定位误差小于2 m的高精度数据占比为85.53%。

Aiming at the problem of insufficient positioning accuracy of BeiDou navigation satellite system(BDS)under practical complex scenes,an algorithm based on multi-sensor navigation data fusion was proposed:a multi-sensor multi-scenario weighted optimal decision-making method based on analytic hierarchy process(AHP)was designed,in which the weight of each sensor adaptively changes with the change of the scenes,and the positioning advantages of each sensor in different scenarios were utilized to obtain the real-time high-precise navigation data.Experimental result showed that the multi-sensor navigation data fusion could make up for the problem of insufficient positioning accuracy in some scenes with single sensor,and maximize the positioning performance of the overall navigation under the existing sensor positioning effect.Moreover,it could be statistically concluded that the proportion of the high-precise data with positioning errors of less than 2 m under adaptive data fusion(ADF)based on analytic hierarchy process would be 85.53%.