Optimal attitude solving method for bionic navigation

Abstract

The invention provides an optimal attitude solving method for bionic navigation, and belongs to the technical field of polarized light navigation attitude solving. In this method, a polarization vector and a gravity vector are used to construct a target error function model, and an optimal attitude quaternion is solved according to different motion states, so as to improve attitude solution accuracy under a complex maneuvering condition. According to the method provided by the invention, the heading information compensation correction of an unmanned aerial vehicle is realized by solving a polarization azimuth angle error searching direction, and the problem of angle ambiguity caused by direct solution is avoided. A polarized light navigation scheme designed by the invention decouples a solving process of heading and horizontal attitude to overcome spatial position constraint of attitude solving, and simultaneously a gradient optimization method with variable search factors is adopted,so that the step size in search can be changed in real time according to different motion states of the aircraft, and measurement accuracy and robustness of a polarized light navigation system are improved.

Description

technical field [0001] The invention belongs to the technical field of aircraft attitude measurement and estimation, relates to a heading and attitude reference system (AHRS) based on a polarized light sensor, and mainly relates to a gradient optimization attitude calculation method with a variable search factor. Background technique [0002] Attitude and Heading Reference System (AHRS) is a key device in the navigation platform, which can provide accurate and reliable flight status information for the aircraft. The traditional attitude reference system uses the inertial measurement unit (IMU) as the main attitude calculation component. On this basis, there are two expansion methods according to the performance requirements of the navigation platform: one is composed of the inertial measurement unit and the geomagnetic sensor. The other is composed of an inertial measurement unit combined with GPS. However, both of the above two attitude measurement schemes have their own s...

AI Technical Summary

Problems solved by technology

However, both of the above two attitude measurement schemes have their own shortcomings: the geomagnetic sensor in scheme one determines the heading information by detecting the magnetic field vector, but it is very sensitive to electromagnetic interference, and is easily affected by the surrounding electromagnetic field and airborne electronic equipment, which will cause the heading attitude to be unresolved. The calculation accuracy is reduced; in the case of high maneuvering, the inconsistency between the satellite signal transmission frequency and the aircraft movement frequency is significantly enhanced, resulting in the serious phenomenon of GPS star loss in method 2, which affects the accurate calculation of heading information

However, both of these two methods have certain limitations: method one has the problem of polarization and azimuth ambiguity in the process of calculating the heading information, and the accuracy of the attitude calculation is closely related to the error accuracy of the aircraft's horizontal attitude. Higher orientation accuracy can only be achieved when the range changes, which greatly limits the space attitude calculation of the aircraft

Among them, the Kalman filter model has a large amount of calculation in each iteration process, so it needs a microprocessor with a fast enough calculation speed, otherwise it will not be able to guarantee the real-time requirements of attitude calculation, and at the same time, the model error of the polarization sensor is affected by various Influenced by factors, the corresponding error term cannot be accurately input in the Kalman filter, which further restricts the improvement of navigation accuracy and system performance by this method

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