基于图像匹配的机载惯导位置和航向修正方法OA

To address the challenge of UAV navigation in GPS-free and nighttime environments,this paper proposes an airborne autonomous localization and navigation method based on heterogenous image matching and inertial navi-gationfusion.The proposed method enables the alignment of infrared or visible aerial images with geo-referenced sat-ellite images,and subsequently realizes autonomous localization estimation and heading correction based on the alignment results.The heterogenous image matching method in this paper consists of a fast structural feature-based image matching module and an end-to-end learning-based fine registration network.The former provides position cor-rections at approximately 20 Hz,while the latter enables high-precision position and heading refinement.A pose fusion filtering strategy is employed to integrate the position and heading information obtained from image matching with iner-tial navigation data,effectively suppressing the drift in inertial systems and ultimately improving navigation accuracy.The flight test shows that the proposed method can effectively improve the positioning accuracy and reliability com-pared with existing methods,and can reach real-time processing on the airborne embedded computing platform.