INS Fine Alignment With Low-Cost Gyroscopes: Adaptive Filters for Different Measurement Types

Abstract

Inertial navigation system stationary fine alignment process is a critical step in reducing the initial errors of the attitude and sensor biases. While many studies had been made for tactical grade systems, less attention was given to low-cost sensors, which are a major player in today's inertial sensors market. To fill this gap, a measurement strategy combining different INS aiding types is proposed, analyzed and compared using numerical simulations and field experiments. Additionally, an analytical linear observability analysis is made to support the numerical comparisons. Further, five types of adaptive Kalman filters with the proposed measurement strategy are compared to find the appropriate one to improve the alignment performance. The proposed measurement strategy can be used in other applications of stationary conditions such as land vehicles, robots or shoe-mounted inertial navigation systems.