Method and system for deep integration and real-time compensation of micro-inertial measurement information

A technology of micro-inertial measurement and real-time compensation, applied in the field of signal processing, can solve the problems of low precision of micro-inertial measurement, error fusion and compensation, increase of fusion deviation, etc., and achieve the effect of improving estimation accuracy, improving accuracy and fast response speed

Inactive Publication Date: 2017-09-15
BEIJING INSTITUTE OF TECHNOLOGYGY +1
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  • Summary
  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The measurement deviation of multiple sensors will lead to an increase in the fusion deviation. In order to eliminate the deviation, the sensor needs to be calibrated or filtered offline. However, due to the low efficiency of the

Method used

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  • Method and system for deep integration and real-time compensation of micro-inertial measurement information
  • Method and system for deep integration and real-time compensation of micro-inertial measurement information
  • Method and system for deep integration and real-time compensation of micro-inertial measurement information

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Effect test

Embodiment 1

[0050] Such as figure 1 As shown, the deep fusion and real-time compensation methods of micro-inertial measurement information include:

[0051] Step 11: Obtain the angular velocity information, acceleration information and magnetic field strength information of the research object respectively. In this embodiment, the angular velocity information of the research object is measured by a three-axis gyroscope, the acceleration information of the research object is measured by a three-axis accelerometer, and the three-axis The magnetometer measures the magnetic field strength information of the research object;

[0052] Step 12: Using the deep learning method to perform real-time compensation on the angular velocity information, acceleration information and magnetic field strength information respectively, and obtain the compensated angular velocity information, the compensated acceleration information and the compensated magnetic field strength information respectively;

[0053...

Embodiment 2

[0065] Such as Figure 4 As shown, the deep fusion and real-time compensation system of micro-inertial measurement information includes:

[0066] An information acquisition module 41, configured to acquire angular velocity information, acceleration information and magnetic field strength information of the research object respectively;

[0067] The real-time compensation module 42 is used to perform real-time compensation on the angular velocity information, the acceleration information and the magnetic field strength information respectively by using a deep learning method, and respectively obtain compensated angular velocity information, compensated acceleration information and compensated magnetic field strength information;

[0068] The Euler angle calculation module 43 is configured to determine a first Euler angle according to the compensated angular velocity information, and determine a second Euler angle according to the compensated acceleration information and the com...

Embodiment 3

[0081] Embodiment 3: The method for deep fusion and real-time compensation of micro-inertial measurement information includes:

[0082] Step 31: Obtain the angular velocity information, acceleration information and magnetic field strength information of the research object respectively:

[0083]Obtain Microelectro Mechanical Systems (MEMS) sensors, including three-axis gyroscopes, three-axis accelerometers, and three-axis magnetometers, which output angular velocity information, acceleration information, and magnetic field strength information respectively, and the three axes of the sensor X-Y-Z Defined as front-right-down, the Euler angle is represented by α-Yaw, β-Pitch, γ-Roll, the carrier attitude is represented by roll angle γ and pitch angle β, and the heading is represented by yaw angle α.

[0084] Step 32: Using a deep learning method to perform real-time compensation on angular velocity information, acceleration information, and magnetic field strength information, re...

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Abstract

The invention discloses a method and system for deep integration and real-time compensation of micro-inertial measurement information. The method comprises the following steps: respectively acquiring angular velocity information, acceleration information and magnetic field intensity information of a study object; respectively carrying out real-time compensation on the angular velocity information, the acceleration information and the magnetic field intensity information by virtue of a deep learning method, so as to respectively obtain compensated angular velocity information, acceleration information and magnetic field intensity information; determining a first Euler angle according to the compensated angular velocity information, and determining a second Euler angle according to the compensated acceleration information and the compensated magnetic field intensity information; and determining an integration gain coefficient of a self-adaption gain method according to a mean square error of the first Euler angle and a mean square error of the second Euler angle, and integrating the first Euler angle with the second Euler angle according to the integration gain coefficient, so as to obtain the integrated Euler angle. According to the method and the system, the micro-inertial measurement precision can be increased, the stability and the reliability are high, the aging ratio is high, and the response speed is high.

Description

technical field [0001] The present invention relates to the field of signal processing, in particular to a method and system for deep fusion and real-time compensation of micro-inertial measurement information Background technique [0002] At present, the MEMS inertial measurement equipment researched at home and abroad is mainly composed of multiple MEMS measuring devices, such as MEMS (Microelectro Mechanical Systems, MEMS), gyroscopes and accelerometers, through the combination of information fusion technology. Due to its low-cost advantage, it is widely used in mobile robots, aerospace, automotive automatic navigation and other fields. The measurement deviation of multiple sensors will lead to an increase in the fusion deviation. In order to eliminate the deviation, the sensor needs to be calibrated or filtered offline. However, due to the low efficiency of the offline calibration of the sensor and the introduction of new errors, the conventional filtering method does no...

Claims

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Application Information

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IPC IPC(8): G01C21/16
CPCG01C21/165G01C21/20
Inventor 刘福朝苏中李擎费程羽刘宁刘洪
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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