GPS aided In Motion Coarse Alignment using Fast Optimal Attitude Matrix (FOAM) and Wavelet Filter

The alignment is an essential part of the inertial navigation system. A novel optimization-based initial alignment for global positioning system (GPS) supported inertial navigation system (SINS) is proposed in this paper. In optimization-based alignment, the required attitude between the body frame and navigation frame is divided into three parts, the two attitude matrix are time-varying and one is constant initial attitude matrix. The contribution of proposed method is twofold. Firstly, a novel approach based on Fast Optimal Attitude Matrix (FOAM) is proposed to estimate the constant initial attitude matrix. FOAM is more robust and computationally efficient than many existing attitude estimation methods. Secondly, the on-line pre-filtering of measurements of inertial sensor named the inertial measurement unit (IMU) is used. The pre-filtering and de-noising of the IMU noise is based on the real-time multi-levels discrete wavelet decomposition filter. Due to these proposed modifications, the proposed FOAM based alignment requires less computation power, and it improve the robustness. As the IMU noise affects the performance of the initial alignment, so the proposed pre-filtering improves the performance of alignment. Simulation results demonstrate the validity of the proposed OBA algorithm.