Sage-Husa adaptive unscented Kalman Filter attitude data fusion method

An unscented Kalman and adaptive filtering technology, applied in navigation computing tools and other directions, can solve the problems of noise statistical deviation, non-positive definite variance matrix, large filtering error, etc.

Active Publication Date: 2019-07-05
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

However, this method is likely to cause the variance matrix to be non-positive definite, and the filtering effect is poor when the noise changes greatly. At the same time, the noise statistics will be biased due to factors such as changes in the surrounding environment noise, which will eventually lead to a large filtering error or even failure.

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  • Sage-Husa adaptive unscented Kalman Filter attitude data fusion method

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[0098] The following describes the embodiment of the present invention in detail, and this embodiment is exemplary, and is only used to explain the present invention, and should not be construed as limiting the present invention. A Sage-Husa adaptive unscented Kalman filter attitude data fusion method of the present invention will be described in detail below with reference to the accompanying drawings.

[0099] In order to better reflect the implementation and effect of the concrete steps of the present invention, the following simulation experiments are set up: use the MATLAB simulation platform to check the performance of the algorithm. In this experimental environment, the following measurement models can be built:

[0100] The gyroscope attitude measurement model and error model are where ω o and ω represent the angular velocity vector and the real angular velocity vector measured by the gyroscope in continuous time, respectively, n g and n εg represent zero-mean whi...

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Abstract

The invention provides a Sage-Husa adaptive unscented Kalman filter attitude data fusion method, belongs to the technical field of digital filter and multi-sensor data fusion and is mainly used for improving carrier attitude estimation precision. According to the method, error quaternion unscented Kalman filter is taken as a frame, data of a gyroscope, an accelerometer and a magnetometer are fused, through analysis of sensor errors, a relatively accurate sensor measurement model is established, and through combination of an error quaternion method and a UKF (Unscented Kalman Filter) filter algorithm, data fusion of the sensors is realized. The method is applicable to a nonlinear attitude measurement system and has relatively good anti-interference performance and attitude calculation precision. A carrier attitude calculation problem under a complex environment can be effectively solved.

Description

technical field [0001] A Sage-Husa adaptive unscented Kalman filter attitude data fusion method provided by the invention belongs to the technical field of digital filtering and multi-sensor data fusion, and the method provided by the invention is suitable for nonlinear attitude measurement systems. Background technique [0002] The attitude measurement system of the carrier is actually a nonlinear system. In order to achieve accurate calculation of the attitude, it is necessary to use nonlinear filtering to fuse the data of the gyroscope, accelerometer, and magnetometer. However, the sensor itself is susceptible to external interference and the sensor output The data contains a lot of noise. Both process noise and measurement noise are unknown and have time-varying characteristics. Wrong parameter estimation may lead to filtering divergence, so a suitable filtering algorithm needs to be used. Therefore, a Sage-Husa adaptive unscented Kalman filter algorithm came into being....

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/20
CPCG01C21/20Y02T90/00
Inventor 周翟和刘颀绮程遵堃
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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