Serial inertial navigation nonlinear alignment method based on fuzzy self-adaptation control technology

Abstract

The invention discloses a serial inertial navigation nonlinear alignment method based on a fuzzy self-adaptation control technology. According to the invention, by utilizing a characteristic that fuzzy logic is suitable for expressing qualitative knowledge and experience with indistinct boundary, and reasoning regular fuzzy information problems which are difficultly solved by the conventional method, and by adding a fuzzy logic control module especially used for dynamically optimizing a weakening factor matrix between filtering time update and filtering measurement update, adaptive adjustment of a suboptimum fading factor is realized. The serial inertial navigation nonlinear alignment method has the advantages that under the conditions of a large misalignment angle and a movement base, a fuzzy logic controller is used for adjusting a filter gain through linearly selecting the suboptimum fading factor and keeping strong tracking capacity on a movement state of ship-based equipment by using movement information of an AUV (Autonomous Underwater Vehicle) included by a residual error, and a high-precision alignment requirement of a complex underwater environment is met.

Description

technical field [0001] The invention mainly relates to the field of shipboard navigation technology, in particular to a strapdown inertial navigation nonlinear alignment method based on fuzzy adaptive control technology. Background technique [0002] The inertial navigation system must perform initial alignment before entering the navigation working state. The strapdown inertial navigation system (SINS) directly connects the inertial sensor to the carrier, and uses a calculated mathematical platform instead of the physical platform. Therefore, the initial alignment of the SINS is to determine the initial moment attitude matrix. The initial alignment error is the main error source of SINS, and the alignment accuracy directly affects the performance of SINS; autonomous underwater vehicle (AUV) is an intelligent unmanned vehicle that relies on its own autonomy to manage and control itself. The support of accurate navigation and positioning is the guarantee for reliable and con...

AI Technical Summary

Problems solved by technology

In the marine environment, AUV is disturbed by various factors such as gusts, ocean currents, and waves, especially under the conditions of large misalignment angle and severe shaking, which restricts the classical Kalman filter method based on the linear small misalignment angle model; and Traditional nonlinear filtering methods such as EKF and UKF have disadvantages such as low alignment accuracy under high-dimensional conditions and poor ability to deal with uncertain factors, and because GPS cannot be used underwater, the invention has high precision and can effectively deal with complex environments. The nonlinear intelligent filtering method for DVL-assisted SINS moving base alignment of Doppler velocimeter is of great significance

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