Method for dynamic attitude estimation of vehicle based on mems inertial sensor

An inertial sensor and attitude estimation technology, applied in the field of MEMS sensing, can solve the problems of gyroscope drift error, poor dynamic performance, large error, etc., and achieve the effect of improving accuracy and reducing drift error.

Active Publication Date: 2020-07-24
LOW SPEED AERODYNAMIC INST OF CHINESE AERODYNAMIC RES & DEV CENT
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Problems solved by technology

However, MEMS inertial devices have the following disadvantages at the same time: 1) There is a drift error in the gyroscope, and there will be error accumulation after long-term use; 2) The accelerometer is greatly affected by linear acceleration and centripetal acceleration in the motion state, and there are Big error, poor dynamic performance
And because the interference of the magnetic field is random in reality, the error is pre-eliminated, and the error is large when the heading angle is solved alone

Method used

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  • Method for dynamic attitude estimation of vehicle based on mems inertial sensor
  • Method for dynamic attitude estimation of vehicle based on mems inertial sensor
  • Method for dynamic attitude estimation of vehicle based on mems inertial sensor

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Embodiment 2

[0117] Embodiment 2 effect experiment contrast

[0118] In this paper, three sets of experiments are set up for comparison to verify the effectiveness of the algorithm in this paper. The three sets of experiments are: 1) Static state plus high-frequency vibration experiment, the results are as follows image 3 As shown; 2) The swing test is carried out at a frequency of 0.5Hz and an amplitude of ±5°, and the results are as follows Figure 4 Shown; 3) The rotation test is carried out at an angular velocity of 50° / s, and the results are as follows Figure 5 shown. Each group of experiments is extremely three kinds of attitude calculation algorithms: the attitude calculation algorithm (G-A) using the accelerometer, the attitude calculation algorithm (FIR) using the FIR filter, and the EKF filter algorithm (EKF) designed by the application. By comparison Examine the performance of the three algorithms in different situations.

[0119] Depend on image 3 It can be seen that in ...

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Abstract

The invention discloses a carrier dynamic attitude estimation method based on an MEMS inertial sensor. The method comprises the following steps: acquiring triaxial accelerometer data and processing the triaxial accelerometer data through an accelerometer noise model; acquiring three-axis gyroscope data and processing the three-axis gyroscope data through a gyroscope noise model; and processing thedata processed by the three-axis gyroscope and the data processed by the three-axis accelerometer by an EKF filter and then performing multi-sensing information fusion to solve an attitude angle andupdate attitude information. Therefore, the accelerometer data is processed through the accelerometer noise model, the gyroscope data are processed through the gyroscope noise model, multi-sensing information fusion is performed on the data processed by the three-axis gyroscope and the data processed by the three-axis accelerometer through the EKF filter and thus the attitude information of the dynamic carrier is stably and accurately obtained.

Description

technical field [0001] The present application relates to the technical field of MEMS sensing, in particular to a method for estimating the dynamic posture of a carrier based on MEMS inertial sensors. Background technique [0002] Intelligent and unmanned is the development trend of today's vehicle industry. Whether it is the development of unmanned vehicles or the application of intelligently operated engineering vehicles, real-time, accurate and stable attitude information is the key to realizing intelligent operation and unmanned driving networks. premise. MEMS sensors are widely used in industry today due to their small size, light weight, low power consumption and high reliability. However, MEMS inertial devices have the following disadvantages at the same time: 1) There is a drift error in the gyroscope, and there will be error accumulation after long-term use; 2) The accelerometer is greatly affected by linear acceleration and centripetal acceleration in the motion s...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01C21/16G01C21/20
CPCG01C21/165G01C21/20
Inventor 吴志刚徐开明耿晓东时广轶王春波尹欣繁刘忠华
Owner LOW SPEED AERODYNAMIC INST OF CHINESE AERODYNAMIC RES & DEV CENT
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