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Gyroscope filtering method based on Sage-Husa Kalman filtering

A Kalman filter and gyroscope technology, applied in low-cost gyroscope output signal processing and inertial navigation fields, can solve the problems of cumbersome Kalman filter steps, lack of generality, etc., to achieve stable and reliable algorithm, ensure noise estimation accuracy, Improve the effect of filtering and stability

Active Publication Date: 2018-08-17
BEIHANG UNIV
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Problems solved by technology

[0004] In order to solve the problem that the steps of Kalman filtering using time series analysis and modeling are cumbersome and not universal, the present invention proposes a simple modeling Sage-Husa Kalman filtering algorithm to filter the output data of the gyroscope

Method used

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  • Gyroscope filtering method based on Sage-Husa Kalman filtering
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  • Gyroscope filtering method based on Sage-Husa Kalman filtering

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Embodiment Construction

[0051] The present invention will be further described below in conjunction with the accompanying drawings.

[0052] (1) if figure 1 As shown, for the traditional Kalman filter or the Sage-Husa Kalman filter, the state equation and measurement equation of the system must be established first, and then the initial value of the filter is set to enter the solution iteration cycle.

[0053]For the gyroscope used in drones, because the navigation and control system has high requirements for real-time performance, the sampling frequency of the gyroscope is extremely fast, and the data change rate of the gyroscope between two data samples is 0; As part of the state quantity to improve the filtering effect and stability, the state equation and measurement equation are obtained:

[0054]

[0055]

[0056] One-step state transition matrix obtained from the above formula ε(k-1) is white noise with a mean value of zero; Z(k) is the angular velocity observation value at time k, th...

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Abstract

The invention provides a gyroscope filtering method based on Sage-Husa Kalman filtering. A gyroscope is an important device of inertial navigation calculation in drones and is also the core element ofattitude calculation, and the attitude calculation is the foundation of follow-up speed and position calculation. A traditional filtering method uses low-pass filtering and time sequence modeling toperform Kalman filtering but has problems that low-pass filtering is severe in time delay; a noise matrix during the time sequence modeling can only represent the features of certain period of time under static conditions, reanalysis and remodeling are needed for different devices, the procedures are complex, and the time sequence modeling is not universal. The method has the advantages that the Sage-Husa self-adaptation Kalman filtering is adopted, simple modeling is performed by analyzing gyroscope features, the time sequence analysis modeling which is complex and not universal is omitted, the noise is processed as the filtering state quantity, and the random drift of the system can be well inhibited.

Description

technical field [0001] The invention mainly relates to the technical field of low-cost gyroscope output signal processing, belongs to the technical fields of inertial navigation, unmanned aerial vehicle navigation, etc., and specifically relates to a gyroscope filtering method based on Sage-Husa Kalman filtering. Background technique [0002] Low-cost gyroscopes are now commonly used in industries such as mobile phones, smart wearables, and drones. It is the core device of inertial navigation attitude calculation, and its random noise has a great impact on navigation calculation. [0003] For gyroscope data processing, the simplest methods are low-pass filtering and sliding window filtering. The advantage is that it is simple to implement and does not require a system model. However, when the effect is strong, the delay is more serious. At present, the more common method is to collect the gyroscope data offline, conduct time series analysis, obtain the state equation, and t...

Claims

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Application Information

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IPC IPC(8): G01C25/00
CPCG01C25/00
Inventor 胡少兴李晓东田博显肖深
Owner BEIHANG UNIV
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