Attitude resolving method of flight attitude system based on geomagnetic field self-adaptive correction

An attitude system and self-adaptive technology, applied in the field of positioning and navigation, to achieve the effect of improving the accuracy of attitude calculation

Inactive Publication Date: 2019-08-27
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

In the attitude calculation process of the heading and attitude system (AHRS) sensor, the complementary filtering algorithm based on quaternion and the extended Kalman filtering algorithm are generally used to solve the above problems, but at present, the complementary filtering algorithm based on quaternion and the extended Kalman filtering algorithm are In the filtering algorithm, the soft magnetic interference in the environment is directly corrected by using the world geomagnetic model, ignoring the influence of magnetic anomalies that may occur in practice on the attitude calculation

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  • Attitude resolving method of flight attitude system based on geomagnetic field self-adaptive correction
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  • Attitude resolving method of flight attitude system based on geomagnetic field self-adaptive correction

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Embodiment Construction

[0047] Embodiments of the present invention are described in detail below, and the embodiments are exemplary and intended to explain the present invention, but should not be construed as limiting the present invention.

[0048] This embodiment proposes a method for calculating the attitude of the attitude system based on the self-adaptive correction of the earth's magnetic field, using the adaptive extended Kalman filter algorithm to calculate the attitude of the attitude system, wherein

[0049] The state equation is:

[0050] x k = Φ k / k-1 αX k-1 +W k-1

[0051] The measurement equation is:

[0052] Z k =H k x k +V k

[0053] where X k for t k The state vector at time, Z k for t k Measurement vector at time, Φ k / k-1 for t k-1 time to t k State transition matrix at time, H k is the measurement matrix, V k is the measurement noise, W k-1 is the system noise, and the system noise covariance matrix is ​​Q k-1 , the measurement noise covariance matrix is ​​R ...

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Abstract

The invention provides an attitude resolving method of flight attitude system based on geomagnetic field self-adaptive correction. The method comprises the following steps: respectively computing a state-transition matrix, a measurement matrix, a system noise covariance matrix, a measurement noise covariance matrix and a self-adaptive matrix; and performing attitude resolving of the flight attitude system by adopting a self-adaptive extended Kalman filtering algorithm. Through the resolving method provided by the invention, the problem that the carrier attitude is large in accumulative error is effectively solved, and the attitude resolving precision is improved at the same time.

Description

technical field [0001] The invention relates to an attitude calculation method based on the self-adaptive correction of the earth's gravity field and the earth's magnetic field, and belongs to the technical field of positioning and navigation. Background technique [0002] MEMS sensors (gyroscopes, accelerometers, magnetometers) are becoming more and more popular in the field of mobile devices. They have the advantages of low cost, high integration and small size. However, when performing attitude calculations, there are excessive output noises, Problems such as zero drift cannot be completely eliminated, and angular rate output is susceptible to interference. Therefore, under normal circumstances, it is necessary to use multiple sensors to achieve high-precision attitude calculation through information fusion algorithms. In the attitude calculation process of the heading and attitude system (AHRS) sensor, the complementary filtering algorithm based on quaternion and the ex...

Claims

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Application Information

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IPC IPC(8): G01C25/00G01C21/20G01C21/18G01C21/16
CPCG01C25/00G01C25/005G01C21/20G01C21/18G01C21/165
Inventor 刘明雍宋保维郭娇娇牛云刘禄王梦凡雷罡李赛楠杨扬向举苗王录
Owner NORTHWESTERN POLYTECHNICAL UNIV
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