A Novel Geolocalization Algorithm for UAV Under GNSS-denied Environment using Heading Estimation before Image Matching

The glocalization problem under GNSS-denied environments plays a significant role in real-time location-based services. However, previous studies need multiple image matching operations for glocalization, causing overheard computational burden on UAVs with limited computing resources. This study proposed a novel glocalization algorithm for UAV under GNSS-denied environment. Specifically, we propose an adaptive search strategy to dynamically search for the UAV probable position, reducing the candidate position space and improving the matching accuracy and computational efficiency. In addition, we adopt an image vector approach to estimate the UAV heading to rotate the UAV image before matching, which reduces the error by more than 60%. A case study was demonstrated to evaluate the performance of the developed algorithm in real application. Results show that the developed algorithm can position with the error less 10 m.