In-motion Alignment of Inertial Navigation System with Doppler Speed Measurements
K. Bimal Raj, Ashok Joshi · 2015
This paper presents a nonlinear approach for the in-motion alignment problem of inertial navigation system using Doppler speed measurements with unknown initial vehicle attitude. Large angle error propagation model in wander azimuth frame is developed and it is used for mechanization of the in-motion alignment Kalman filter. Wander azimuth frame error models provide partial observability of heading angle error when it is aided with nongeographic frame navigation aids like Doppler speed measurements. Error dynamic models are nonlinear equations and hence linear model is obtained at every step from Jacobian matrix for using in the extended Kalman filter. Alignment simulation is repeated with unscented Kalman filter which doesn’t require linearized transformation function. Unscented kalman filter provides a better estimate of posteriori mean and covariance of the state vector and the performance of alignment algorithm is better than that of the extended Kalman filter.