Abstract
Guidance and navigation algorithms play a crucial role in ensuring a successful spacecraft mission. This work proposes a full guidance and navigation algorithm based on differential algebra successive convex programming technique (SCVX). By leveraging the high-order expansions around the reference trajectory it is possible to enhance the computational efficiency of convex-based guidance and navigation algorithms. The high-order expansion enables to capture of the non-linearities in the estimation and guidance problems without sacrificing the robustness of the algorithms. Monte Carlo analyses are carried out to assess the benefits of recom-puting the guidance from the estimated state with this new high-order approach while being robust to uncertainties and errors.