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Attitude estimation method based on iteration volume Kalman filter

A Kalman filter and attitude estimation technology, which is applied in the direction of navigation computing tools, etc., can solve the problems of affecting the filtering accuracy, filtering divergence, and decreasing filtering accuracy.

Active Publication Date: 2014-07-02
HARBIN ENG UNIV
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Problems solved by technology

However, EKF has certain limitations: 1) The truncation error introduced by model linearization will lead to a decrease in filtering accuracy, and a more complex Jacobian matrix needs to be calculated; 2) When the initial state error is large or the system model is more nonlinear When it is high, it will seriously affect the filtering accuracy and even cause the filtering to diverge

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Embodiment Construction

[0084] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0085] The aircraft attitude estimation method based on iterative volumetric Kalman filter proposed by the present invention is simulated by Matlab simulation software, and compared with the estimation performance of existing filtering algorithms, such as multiplicative extended Kalman filter (Multiplicative Extended Kalman Filter, MEKF) and iterative volumetric Kalman filtering (ICKF). The simulation hardware environment is Intel(R) Core(TM) i5-2410M CPU2.30GHz, 4G RAM, Windows7 operating system. Such as Figure 1 to Figure 3 As shown, the IICKF algorithm proposed by the present invention is equivalent to the convergence speed of the ICKF algorithm, but their estimation accuracy and convergence speed are always higher than the MEKF algorithm. This is because the IICKF algorithm and the ICKF algorithm of the present invention are based on the CKF algorithm. Its acc...

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Abstract

The invention discloses an attitude estimation method based on iteration volume Kalman filter. The method comprises the following steps: 1, acquiring output data of a gyroscope and a star sensor as measurement amount; 2, confirming a state vector quantity and a measurement vector quantity; 3, estimating an error quaternion vector part and a gyroscope drift error at k moment by using the iteration volume Kalman filter at k-1 moment; 4, calculating quaternion estimation and gyroscope drift estimation for the estimation as shown in the specification at the k moment, and correcting the attitude and gyroscope drift, so as to obtain the modified attitude and the gyroscope drift at the k moment; and 5, in the attitude estimation, if the operation time of a non-linear discrete system is M and k is equal to M, outputting the result of the attitude and the gyroscope drift, and if k is smaller than M, repeating the steps 3 and 4 till the attitude estimation system operation is accomplished. The method has the advantages of high estimation precision and small calculation amount.

Description

technical field [0001] The invention belongs to the technical field of attitude estimation by using nonlinear filtering technology and iteration theory, and in particular relates to an attitude estimation method based on iterative volumetric Kalman filtering. Background technique [0002] The accuracy of aircraft attitude estimation directly affects the accuracy of aircraft attitude control. Therefore, attitude estimation is one of the key technologies of attitude control. Attitude estimation methods are mainly divided into two categories: deterministic algorithms and state estimation methods. The advantage of the deterministic algorithm is that it can directly solve the attitude matrix of the aircraft at that moment based on a set of measurement information at a certain moment. The algorithm is simple and the physical meaning is clear, but it needs to know at least two independent observation vectors at the current moment, namely Accurate measurement information, but it is...

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Application Information

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IPC IPC(8): G01C21/20
CPCG01C21/20
Inventor 钱华明黄蔚沈忱孙龙富振铎彭宇
Owner HARBIN ENG UNIV
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