Study On A Swaying-Base Self-alignment Method Of Rotary Sins

Rotary Strapdown Inertial Navigation System(Rotary SINS) can minish the influence of the inertial equipment’s floating error on its performance through steady rotation. The restriction to Inertial Navigation System(INS) due to the level of inertial equipment can be solved in this way. It has a great significance in the field of national defense. However, initial error cannot be compensated by Rotary SINS. Initial alignment is a key technology of INS, which determines the accuracy and quick reaction ability of INS. So it’s necessary to study on the initial alignment technology of Rotary SINS.Due to the interference acceleration and interference angle velocity, the traditional analytic alignment method on swaying base is difficult to achieve. So an initial self-alignment method of two-axis Rotary SINS on swaying base is studied in this paper. The content mainly comprises of the following aspects:Firstly, according to the basic principle of initial alignment for Rotary SINS, the coarse alignment method in inertial frame for Rotary SINS was researched with the change of the gravity direction in the inertial space containing the north information of the earth. By this way, the angular and linear moving disturbance can be easily eliminated to realize coarse alignment in the condition of swaying base. On the basis of coarse alignment results, the fine alignment error model of Rotary SINS on swaying base was established. The observability of the system is discussed by Piece-Wise Constant System(PWCS) theory and the observable degree is computed by the Singular Value Decomposition(SVD) theory. The observability analysis results of the fine alignment error model can be obtained. The results demonstrated that the system is completely observable.Secondly, aiming at the uncertainty of measurement noise in the fine alignment error model, two improved algorithms are proposed to achieve the fine alignment on swaying base, respectively improved multiple fading factors adaptive Kalman filter and improved adaptive Kalman filter for estimating measurement noise variance. The proposed algorithms can estimate and correct the system noise and measurement noise in real time, to achieve accurate estimation of attitude angle error. The accuracy and performance of the proposed algorithms are demonstrated by the simulation studies which compared the proposed algorithms with the existing adaptive filter algorithm.Finally, based on the optimal attitude alignment idea, the relationship between the initial alignment problem and the optimal attitude determination problem is established. Following the famous q-method algorithm for Wahba attitude determination, we could pose the alignment problem as an optimization problem. According to the optimal estimation of the initial attitude, the initial attitude before the carrier navigation can be achieved. The proposed method is inherently able to realize self-alignment on swaying base with rapidness and accuracy. Comparing with the initial alignment method in inertial frame, it validates the validity and feasibility of the proposed method by the simulation studies.