  We present an ambiguity resolution method for Global Navigation Satellite
System (GNSS)-based attitude determination. A GNSS attitude model with
nonlinear constraints is used to rigorously incorporate a priori information.
Given the characteristics of the employed nonlinear constraints, we formulate
GNSS attitude determination as an optimization problem on a manifold. Then,
Riemannian manifold optimization algorithms are utilized to aid ambiguity
resolution based on a proposed decomposition of the objective function. The
application of manifold geometry enables high-quality float solutions that are
critical to reinforcing search-based integer ambiguity resolution in terms of
efficiency, availability, and reliability. The proposed approach is
characterized by a low computational complexity and a high probability of
resolving the ambiguities correctly. The performance of the proposed ambiguity
resolution method is tested through a series of simulations and real
experiments. Comparisons with the principal benchmarks indicate the superiority
of the proposed method as reflected by the high ambiguity resolution success
rates.
