Optimal orthonormalization of the strapdown matrix by using singular value decomposition

AbstractThe existing iterative algorithms for optimal orthonormalization of the strapdown matrix are reviewed. In order to ensure convergence these algorithms all have restrictions in the initial direction cosine matrix. Another algorithm, the singular vector algorithm, is proposed. This algorithm is based on the singular value decomposition of a matrix. Convergence of the algorithm is established. The advantages of the algorithm are investigated by comparing its convergence, accuracy and computational demands with other algorithms. The algorithm is illustrated with numerical examples