# Visual-Inertial Method for Localizing Aerial Vehicles in GNSS-Denied Environments
## 5 Conclusions  
While further research is needed to fully delineate the method's accuracy and limitations, this study demonstrated its potential practical advantages. A key benefit is the minimal number of required world points, which is particularly useful in environments with limited distinguishable landmarks, such as densely vegetated areas or open seas. The method relies solely on Pitch and Roll (Euler) angles, focal length, and detector dimensions, deliberately excluding the Yaw (Euler) angle estimation typically obtained through less accurate magnetic compasses. This exclusion simplifies the approach and enhances its reliability. Additionally, the method's reliance on a series of rigid transformations eliminates the need for reiterative calculations, contributing to its rapid execution.  
The method presented here was validated using a LiDAR model of a building and 11 optical images. Previous studies confirmed that the solution of a PnP problem with only two points may generate accurate positional results. However, further tests should be conducted in realistic case scenarios outdoors using very accurate systems like RTK as ground truth. In this contribution, data like RTK were not available, and, instead, GNSS data and pose estimations from photogrammetric software were used. The dual cross-validation using GNSS data and RealityCapture pose estimation software provides a sufficient level of verification for this initial stage. By providing an efficient solution, this innovative approach could significantly enhance the operational capabilities of aerial vehicles. Its ability to maintain high accuracy with minimal reference points and without iterative calculations makes it a promising candidate for integration into a wide range of aerial platforms, paving the way for more reliable and precise navigation systems in the future.  
**Author Contributions:** Conceptualization, A.T.; methodology, A.T.; software, M.C.; formal analysis, A.T.; resources, M.P.; writing--original draft preparation, A.T.; writing--review, M.P. and M.C.; supervision, M.P., M.C., J.S.B. and N.N.N.N.L.; project administration, M.P. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported by national funds through FCT (Fundacao para a Ciencia e a Tecnologia) under the project UIDB/04152/2020 (DOI: 10.54499/UIDB/04152/2020)--Centro de Investigacao em Gestao de Informacao (MagIC)/NOVA IMS. This work was partially funded by the Deutsche Forschungsgemeinschaft under Germany's Excellence Strategy.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The raw data supporting the conclusions of this article will be made available by the authors on request.  
**Acknowledgments:** The authors would like to express their gratitude to the NOVA Impact Office ([[https://novainnovation.unl.pt/nova-impact-office/](https://novainnovation.unl.pt/nova-impact-office/)]([https://novainnovation.unl.pt/nova-impact-office/](https://novainnovation.unl.pt/nova-impact-office/)), accessed on 10 February 2024) for all the support provided.  
**Disclaimer:** The content of this paper does not necessarily reflect the official opinion of the European Maritime Safety Agency. Responsibility for the information lies entirely with the authors.  
**Conflicts of Interest:** The authors declare no conflict of interest.