基于测速测距激光雷达的飞行器地形匹配导航方法

Terrain matching navigation method for air vehicle based on FMCW LiDAR

针对中低空飞行器地形匹配与惯导组合中惯导误差累积导致高程图变形限制地形匹配精度、二维地形匹配运算量大和地形匹配失效时定位可用性差的问题,提出一种基于测速测距激光雷达的地形匹配导航方法。利用激光测速信息辅助构建高程图,减小高程图变形从而提高匹配精度,同时降低匹配结果与惯导的相关性;设计集成尺度不变特征变换(SIFT)特征与分步核验的地形匹配算法,提高匹配的实时性;采用激光测速信息辅助校正惯导,提高地形匹配失效时定位的可用性。典型场景地形数据的测试结果表明,基于激光测速辅助构建的高程图较基于惯导构建的高程图的地形匹配定位精度提高了36.6%,所提的卡方初始化随机抽样一致性地形特征误匹配检测算法(TCI-RANSAC)相比于RANSAC算法缩短了55.6%的核验时间,且测速信息的引入将组合定位精度提高了65.9%,具备较高的工程应用价值。

The integration of terrain matching and inertial navigation is a crucial autonomous navigation method for low and medium altitude vehicles,but the traditional method has the following problems:the deformation of the elevation model due to the accumulation of inertial navigation errors restricts the terrain matching accuracy,the two-dimensional terrain matching has a large amount of computing power,and the positioning usability is poor after the terrain matching fails.A terrain matching navigation method based on frequency modulated continuous wave laser radar is proposed.Elevation model is constructed assisted by laser velocimetry,which reduces the deformation of the elevation model to improve the matching accuracy and reduces the correlation between the matching result and inertial navigation.A terrain matching algorithm integrating scale-invariant feature transform(SIFT)and stepwise verification is designed to enhance the real-time performance of the matching.The laser velocimetry is used to assist the correction of inertial navigation,which improve the positioning availability when the terrain matching fails.The proposed terrain matching navigation method is tested based on real terrain data of a typical scenario.The result shows that the terrain matching positioning accuracy of the elevation model based on laser velocity measurement is improved by 36.6%compared with that based on inertial navigation.The proposed terrain cardinality initialized random sample consensus terrain feature mismatch detection algorithm(TCI-RANSAC)reduces the verification time by 55.6%compared to the RANSAC algorithm.Furthermore,the introduction of the laser velocity information improves the integrated positioning accuracy by 65.9%.In conclusion,the proposed terrain matching navigation method has high engineering application value.