TY - GEN
T1 - A GNSS Attitude Determination Algorithm Using Optimization Techniques on Riemannian Manifolds
AU - Liu, Xing
AU - Ballal, Tarig
AU - Ahmed, Mohanad
AU - Al-Naffouri, Tareq Y.
N1 - KAUST Repository Item: Exported on 2023-08-29
PY - 2022/10/20
Y1 - 2022/10/20
N2 - This paper presents a Global Navigation Satellite Systems (GNSS) attitude determination method based on Riemannian manifold optimization techniques. By noting that the solution set of the attitude determination problem is a Riemannian manifold, we formulate the problem as an optimization on the Riemannian manifold. We study the manifold geometry to design an efficient attitude determination algorithm. As a first step, we calculate a float solution using Riemannian manifold optimization to be used as the starting point for the integer search process. Since this solution makes full use of the geometrical constraints, it is expected to have an improvement over the popular least-squares estimator. To utilize the improved float solution, we propose a new decomposition of the objective function, which allows us to apply Riemannian optimization to the process of integer ambiguity resolution. Numerical simulations and actual experiments demonstrate that the proposed algorithm significantly outperforms state-of-the-art approaches for various system configurations.
AB - This paper presents a Global Navigation Satellite Systems (GNSS) attitude determination method based on Riemannian manifold optimization techniques. By noting that the solution set of the attitude determination problem is a Riemannian manifold, we formulate the problem as an optimization on the Riemannian manifold. We study the manifold geometry to design an efficient attitude determination algorithm. As a first step, we calculate a float solution using Riemannian manifold optimization to be used as the starting point for the integer search process. Since this solution makes full use of the geometrical constraints, it is expected to have an improvement over the popular least-squares estimator. To utilize the improved float solution, we propose a new decomposition of the objective function, which allows us to apply Riemannian optimization to the process of integer ambiguity resolution. Numerical simulations and actual experiments demonstrate that the proposed algorithm significantly outperforms state-of-the-art approaches for various system configurations.
UR - http://hdl.handle.net/10754/693760
UR - https://www.ion.org/publications/abstract.cfm?articleID=18329
UR - http://www.scopus.com/inward/record.url?scp=85167824088&partnerID=8YFLogxK
U2 - 10.33012/2022.18329
DO - 10.33012/2022.18329
M3 - Conference contribution
SN - 9781713871361
SP - 2032
EP - 2041
BT - ION GNSS+, The International Technical Meeting of the Satellite Division of The Institute of Navigation
PB - Institute of Navigation
ER -