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High-dynamic vehicle attitude calculation method and system based on multi-sensor inertial navigation system

An inertial navigation system and multi-sensor technology, applied in the field of high-dynamic vehicle attitude calculation methods and systems, can solve the problems of complex vehicle noise, inability to predict and eliminate in advance, errors, etc.

Inactive Publication Date: 2020-08-18
BEWIS TECH +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, a single MEMS sensor has the following disadvantages: 1) The gyroscope has serious cumulative drift errors in the integration
2) Linear acceleration and vibration effects cause large errors in the attitude calculation of the accelerometer
The main disadvantage of the entire MEMS attitude measurement system is that the vehicle generates very complex noise during motion, which is random and cannot be predicted and eliminated in advance
Therefore, it is not possible to obtain a high-precision pose of a moving car using only raw sensor data

Method used

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  • High-dynamic vehicle attitude calculation method and system based on multi-sensor inertial navigation system

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Experimental program
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Embodiment 1

[0079] like figure 1 One aspect shown provides a method for estimating the attitude of a highly dynamic vehicle based on a multi-sensor inertial navigation system, characterized in that it includes the following steps:

[0080] Obtain vehicle-mounted speedometer and accelerometer data, use the vehicle-mounted speedometer to compensate the accelerometer data to obtain the compensated acceleration, obtain the acceleration through motion acceleration suppression processing, and obtain the observed attitude quaternion.

[0081] Obtain the gyroscope data, use the angular velocity value output by the gyroscope, and obtain the state estimation value of the quaternion through the quaternion differential equation.

[0082] By extending Kalman to perform multi-sensor information fusion, the final attitude angle information is output.

[0083] Wherein, the accelerometer data is compensated by using the on-board speedometer to obtain the compensated acceleration including the following f...

Embodiment 2

[0140] Such as figure 2 As shown, a system for applying the aforementioned method is provided, which is characterized in that it includes an accelerometer (1), a speedometer (2), a gyroscope (3), a processor (4) and a filter (5), the The data output end of accelerometer (1), speedometer (2) and gyroscope (3) is connected with the input end of described processor (4), and the data output end of described processor (4) is connected with described filter (5) connected to the input.

[0141] Above, it needs to be explained that: the b system is the carrier coordinate system; the n system is the navigation coordinate system. The conversion relationship between the carrier coordinate system and the navigation coordinate system is as follows: The attitude angle of the carrier is composed of three angles, the rotation around the X axis is the pitch angle, the rotation around the Y axis is the roll angle, and the Z axis is the yaw angle. The three angles are θ, φ, and ψ. Assume t...

Embodiment 3

[0150] In this paper, a 32-bit microprocessor of STM32 with ARM-CortexM3 as the core is used to construct a data acquisition system. The inertial navigation sensor adopts BW-VG500 from BEWIS Sensing Technology Co., Ltd. This is a high-performance MEMS inertial measurement device that integrates a three-axis accelerometer and a three-axis gyroscope. It can accurately measure the parameters of the vehicle. The linear motion speed uses the STM32 module to read the actual vehicle speed of the vehicle OBD system. In the experiment, the raw data measured by the sensor was sampled at a frequency of 100 Hz. The inertial navigation sensor is aligned with the sampling point of the vehicle speed sensor through STM32. Then, send the raw data to the PC using the serial port. Use the extended Kalman filter designed in this application to process the data on the PC, and then use the serial port to send the raw data to the PC. Finally, the results are obtained through curve description. ...

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Abstract

The invention discloses a high-dynamic vehicle attitude estimation method based on a multi-sensor inertial navigation system. The method comprises the following steps: acquiring data of a vehicle-mounted speedometer and an accelerometer, compensating the data of the accelerometer by using the vehicle-mounted speedometer to obtain compensated acceleration, and obtaining acceleration through motionacceleration suppression processing to obtain an observation attitude quaternion; obtaining gyroscope data, and obtaining a state estimation value of a quaternion through a quaternion differential equation by utilizing an angular velocity value output by a gyroscope; performing multi-sensor information fusion through extended Kalman, and outputting final attitude angle information. Therefore, theinfluence of motion acceleration on attitude estimation can be eliminated, and the observation attitude quaternion is obtained. According to the method, a quaternion-based attitude estimation filtering equation is established, so that high-precision calculation of the vehicle attitude is completed, navigation information output in a GPS-free state can be supplemented, and necessary information ofan autonomous navigation system of the vehicle is provided.

Description

technical field [0001] The present application relates to the technical field of high dynamic vehicle attitude estimation, in particular to a method and system for calculating high dynamic vehicle attitude based on a multi-sensor inertial navigation system. Background technique [0002] With the development of modern automobile industry. Intelligent driving system has become the development trend of today's automotive industry. People's demand for intelligent driving system is getting higher and higher. Most of these electronic systems require feedback based on vehicle pose and position information. Therefore, the development of intelligent driving vehicle systems is based on accurate, stable, and real-time attitude and navigation information. [0003] Attitude measurement systems composed of MEMS sensors are widely used in today's automotive industry due to their low power consumption, small size, and low cost. However, a single MEMS sensor has the following disadvantag...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/16G01C21/26G06F17/16
CPCG01C21/165G01C21/26G06F17/16
Inventor 赖郁友耿晓东时广轶王春波吴志刚徐开明金玉丰
Owner BEWIS TECH
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