On the measurement selection for stationary SINS alignment Kalman filters

Abstract

This paper presents a comprehensive study aiming at the optimal measurement selection for Kalman filters applied to the stationary fine self-alignment of strapdown inertial navigation systems (SINS). On the basis of the definition of nonholonomic constraints, two very important measurement strategies for alignment purposes are investigated and mathematically derived: the standalone “zero velocity update” (ZVU) strategy, and an augmented measurement strategy, formed from the ZVU constraint in addition to the “constant Earth rate and gravity update” (CERGU) constraint. As main contribution of this paper, we analytically prove, trough the Cholesky factorization of the observability information matrix, that the augmented strategy is able to improve the convergence rate of the stationary fine self-alignment Kalman filter. For complying with the SINS rapidity requirement, the augmented measurement strategy is considered superior to the traditional standalone ZVU strategy. Simulated and experimental results confirm the adequacy of the outlined conclusions.