Study On Initial Alignment Of Attitude Measurement System Of Ship-borne Satellite Antenna

Ship-borne satellite antenna adopts Micro Electro Mechanical Systems (MEMS) inertial sensors and magnetometer as its measuring elements, which has small volume, light weight and low cost. From the practical point of view, the dissertation brings forward how to implement the initial alignment of the MEMS Attitude Measurement Unit (MAMU) on rocking and moving base.The error models are introduced for the MEMS inertial sensors and the magnetometer according to their temperature drift characteristic. Then the noise variance of the MAMU on rocking and moving base is achieved by Monte Carlo simulation experiment. An error model of the MAMU is also deduced. What's more, the observability of the filtering equation is analyzed by Special Value Decomposition (SVD), which is used to evaluate the convergence rate of the state variables used in the Kalman Filter (KF).Normally, there are two kinds of methods to solve the initial alignment problem of the Strap-down Inertial Navigation System (SINS) on swing base. The one is using the information provided by GPS and SINS to implement the initial alignment. The other is using the information provided by SINS itself to implement it. Generally speaking, the former is suitable for the amplitude more than 20 cm. The latter is suitable for the amplitude less than 20 cm.Two different self-alignment schemes are respectively put forward according to the different instances occurred during MAMU self-alignment. Then the error model of the MAMU with large azimuth angle is derived. The problem MAMU self-alignment with large azimuth angle on swing base is ideally solved by using the Extension Kalman Filter (EKF) algorithm.