The optimal search algorithm based on double-difference carrier phase is one of the methods to solve the attitude angle. An adaptive weighted particle swarm optimization (AWPSO) algorithm based on the Chi-square test is proposed to solve the attitude angle of ultra-short baseline. We establish the fitness function by introducing the relationship between attitude angle and baseline vector into the observation equations of double-difference carrier phase. Searching the attitude according to the fitness model instead of calculating the angle directly, which avoids solving the integer ambiguity. Using adaptive inertial weights and synchronous adaptive learning factors to speed up the convergence of attitude search. Constructing the candidate solution sequence to save the search result and calculating the Mahalanobis distance of the candidate solution. The local optimal solution is eliminated by the Chi-square test, and the attitude angle is gained by weighting the filtered sequence. Various static experimental results show that the new algorithm performs better than the direct solution method, the least square estimation method, and the PSO-based attitude solution method. The RMS error of yaw angle and pitch angle is 0.245° and 0.236° directly at 0.575 m baseline.
Attitude determination is one of the most considerable applications in high-precision GNSS (Global Navigation Satellite System) positioning and navigation. For rigid-body applications, the baseline is approximately fixed on the same plane and its relative position does not change over time. This provides an important constraint that can be exploited to directly aid the attitude determination process. This study provides an attitude determination algorithm with orthogonal constraints for single frequency and single epoch by fully integrating the baseline orthogonal constraints into the observation equations. Carrier phase and pseudo-range measurement from more than two antennas are used to construct the double-difference observation equations. Given the inclusion analysis of the two search spaces, the LAMBDA algorithm is used to transform the non-ellipsoid space search into the ellipsoid space search. The attitude matrix is solved directly by the Lagrange multiplier method and the optimal solution is selected by search space verification. The analysis focuses on single-frequency, single-epoch, rigid-body attitude accuracy and calculation amount. Experimental results demonstrate that the proposed approach can effectively improve the success rate and reliability of single-frequency and single-epoch attitude resolution.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.