Filtering alignment algorithm based on Rodrigue parameters and second-order nolinear measurement

Abstract

The invention discloses a filtering alignment algorithm based on Rodrigue parameters and second-order nolinear measurement. The filtering alignment algorithm comprises the steps of inertial system moving base alignment process, implement of a second-order nolinear filtering measurement estimation algorithm, founding of classic Rodrigue parameter singular points and a treatment method for the classic Rodrigue parameter singular points, specifically, by utilizing posture matrix decomposition, the estimation for the dynamic posture is converted into the estimation for the constant value posture, and the systematic equation linearity described in the inertial coordinate system is established by virtue of the Kelly transformation between the Rodrigue parameters and a posture matrix, and a measurement equation has a second-order nonlinear weak non-linear error model. Meanwhile, detailed analysis and a solving method are provided for solving the problem that singular points exists during posture description by the classic Rodrigue parameters. Under the classic maneuvering condition at the staring stage of a vehicle, the rapid convergence can be achieved, the alignment accuracy is high, and the nolinear moving base alignment with any misalignment angle is realized with calculation amount and calculation complexity equal to those of linear Kalman filtering.

Description

technical field [0001] The invention relates to the technical field of inertial navigation, in particular to a filter alignment algorithm based on Rodrigue parameters and second-order nonlinear measurement. Background technique [0002] The alignment of the moving base can effectively improve the maneuverability of the strapdown inertial navigation system carrier platform, and has high military application value. The research content of the alignment of the moving base mainly includes two aspects, one is to establish the nonlinear error model under the condition of large misalignment angle [1～3] ; The second is to design the corresponding nonlinear filter estimation algorithm [2～9] . [0003] According to different attitude description methods, different nonlinear error models can be obtained, such as the nonlinear error model based on quaternion [1] , Based on the Euler angle nonlinear error model [2] , Based on the modified Rodrigues parameter nonlinear error model [3...

AI Technical Summary

Problems solved by technology

[0004] In the selection of nonlinear filtering algorithm, the conventional EKF filtering algorithm needs to calculate the Jacobian matrix, and when dealing with serious nonlinear problems, the filtering error may increase or even diverge.

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