KR20190003916A - Inertial sensor unit caliberation method for navigation - Google Patents

Abstract

The present invention relates to an inertial sensor calibration method for navigation, determining a driving section of a vehicle with improved open key and satellite sensitivity using a detailed map database to correct errors accumulated as time goes, and performing acceleration sensor calibration in real time with a weighting component using a ratio of NMEA speed information and an acceleration speed integration value in the section. Moreover, a gyro sensor is calibrated through tilt angle calculation and compensation matrix generation using the corrected acceleration sensor value. Accordingly, errors accumulated as time goes and mounting angle errors are corrected to reduce heading and distance errors so that dead reckoning (DR) performance can be improved.

Description

[0001] The present invention relates to an inertial sensor unit caliberation method for navigation,

The present invention relates to a method for calibrating a navigation inertial sensor and, in order to correct an accumulated error over time, a traveling section of a vehicle having an open sky and a satellite sensitivity is determined using a precision map database, Acceleration sensor calibration is performed in real time as a weight component using ratio of NMEA speed information and acceleration sensor integration value. The gyro sensor is calibrated through the tilt angle calculation and the compensation matrix generation by using the corrected acceleration sensor value to correct the accumulated error and the mounting angle error over time, thereby reducing the heading and distance error, thereby improving the DR (Dead Reckoning) And more particularly, to a method for calibrating a navigation inertial sensor.

In general, a navigation system using a Global Navigation Satellite System (GNSS) signal is widely used. However, since this navigation system does not know the position information when the GNSS signal is not received, a navigation system that uses the inertial sensor or the inertial sensor and the GNSS together to obtain the position information of the vehicle has been developed.

This navigation system can estimate the position of a moving object by using an inertial sensor based on a MEMS (Microelectromechanical Systems) called an Inertial Measurement Unit (IMU). In this navigation system, the position information of the moving object is obtained using a predetermined navigation calculation algorithm. In this case, the position information can be obtained by integrating inertia data (e.g., acceleration, angular velocity, etc.) obtained in the IMU.

The inertial navigation system uses a navigation algorithm to calculate the information of the attitude, speed and position of the vehicle. The navigation calculation algorithm is used to calculate an output from the inertia measurement unit (IMU) of the body frame The sensor output value is used. The assumption is that the coordinate system of the inertial measurement unit (IMU), which consists of a three-axis accelerometer and a three-axis gyro, should be mounted exactly in line with the vehicle's body frame.

However, in the case of an inertial measurement unit (IMU) mounted on a vehicle, there is a possibility that there is a deviation between the body coordinate system and the sensor coordinate system due to a close coincidence in the snow or a movement and / or vibration of the vehicle. , ≪ / RTI > and / or location information.

As a technique for improving such errors or inaccuracies, a navigation system using sensor frame calibration and a method for providing the same is proposed in Korean Patent Publication No. 2011-0130775, which is shown in FIG.

Referring to FIG. 1 (a), when the dynamic state of the moving object is stationary on a plane (S10), the output value of the acceleration sensor included in the IMU should exist only in the z-axis direction. However, if the sensor coordinate system is wrong, the revolving module receives the inertia data from the acceleration sensor included in the IMU (S11), and obtains roll angle and pitch angle deviation information (S12).

In addition, referring to FIG. 1 (b), in the navigation system using the sensor frame calibration, the yaw angle information can be obtained while performing the straight running. That is, if the dynamic state of the vehicle is a straight running state (S21), the calibration module may receive GPS data from the GPS module and receive inertial data from the IMU (S22). The forward direction (x-axis direction) acceleration can be obtained by differentiating the speed from the received GPS data.

This conventional technique can calibrate the deformation of the sensor coordinate system using the respective deformation information in the case of the stop state and the straight running state, thereby improving the accuracy of the position information of the navigation system and improving the overall performance thereof have.

However, this conventional technique calibrates the shift of the sensor coordinate system in consideration of the case where the vehicle is in a stationary state and a straight running state as a moving vehicle, so that, when a low-cost inertial sensor is used, There is an inconvenience that calibration can be performed only when the vehicle is in a stopped state.

In addition, the position error of the vehicle caused by the inertial sensor corresponds to a position error that is negligible when the driver directly drives the vehicle. However, in the case of a vehicle capable of autonomous driving other than the driver, the position error causes a serious situation .

In order to solve the above-mentioned inconveniences of the prior art, the present invention has been developed to calibrate the gyro sensor by calibrating the calibrated acceleration sensor value through a tilt angle calculation and a compensation matrix generation, thereby correcting errors accumulated in time and mounting angle errors The objective is to improve the DR (Dead Reckoning) performance by reducing heading and distance error.

In order to correct accumulated errors over time, the present invention uses a precise map database to determine a running section of a vehicle having a good open sky and a high satellite sensitivity, and a NMEA (National Marine Electronics Association) speed Another object of the present invention is to perform acceleration sensor calibration in real time as a weight component using a ratio of information and an acceleration sensor integral value.

According to another aspect of the present invention, there is provided a method of calibrating an inertial sensor for navigation, the method comprising: an acceleration sensor calibration step of calibrating an acceleration sensor based on vehicle speed information using position information received from a GNSS; A tilt angle calculating step using the acceleration sensor value; Generating a compensation matrix using the tilt angle; And a step of calibrating the gyro sensor. ≪ IMAGE >

Therefore, the inertial sensor calibration method of the present invention calibrates the gyro sensor by calibrating the calibrated acceleration sensor value through the tilt angle calculation and the compensation matrix generation, thereby correcting the accumulated error and the mounting angle error over time, And the DR (Dead Reckoning) performance can be improved.

In addition, the present invention uses a precise map database to determine a running section of a vehicle having good open and satellite sensitivity, and performs acceleration sensor calibration in real time as a weight component using the ratio of the NMEA speed information and the acceleration sensor integral value in the section There is another effect you can do.

1 is a schematic diagram of a method for providing a navigation system using a sensor frame calibration according to a conventional technique,
2 is a flowchart of a gyro sensor calibration according to the present invention,
3 is a flowchart of acceleration sensor calibration according to the present invention.

The terms and words used in the present specification and claims should not be construed as limited to ordinary or dictionary terms and the inventor may appropriately define the concept of the term in order to best describe its invention It should be construed as meaning and concept consistent with the technical idea of the present invention.

Therefore, the embodiments described in this specification and the configurations shown in the drawings are merely the most preferred embodiments of the present invention and do not represent all the technical ideas of the present invention. Therefore, It is to be understood that equivalents and modifications are possible.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

2 is a gyro sensor calibration flowchart according to the present invention. As shown in FIG. 2, the navigation inertial sensor calibration method of the present invention calibrates an acceleration sensor based on vehicle speed information using position information received from a GNSS (S100), and then, using the calibrated acceleration sensor value, (S102).

Here, the tilt angle means the mounting angle of the inertial sensor, which means pitch and roll values, and can be expressed by the following expression (1).

[Formula 1]

Here, Ax1, Ay1, Az1 are acceleration sensor values.

Then, the compensation matrix of [Equation 2] is generated using the calculated tilt angle (S103), and the gyro sensor is calibrated using this compensation matrix (S104).

[Formula 2]

Here, θ: Pitch, φ: Roll, acceleration sensor values: (Ax1, Ay1, Az1), and compensation matrix: Ctilt.

3 is a flowchart of acceleration sensor calibration according to the present invention. 3, the acceleration sensor calibration S100 extracts and stores weight information by comparing the NMEA speed information received by the GNSS receiver with the speed information of the acceleration sensor (S202).

The weighting information is calculated based on the relative ratio of acceleration data integration information of the acceleration sensor to the NMEA speed information as a reference value.

If the number of weight information is greater than or equal to the preset threshold value, the weight information is averaged to calculate a weighted average value (S204).

Here, if the number of weight information is less than or equal to the preset threshold value, an average calculation error occurs due to the insufficient number of samples. To improve this, the weight information is further extracted (S101) Sensor calibration is performed (S100), and weight information extracted further is extracted by determining a weight extraction area having a good open space and good GNSS reception sensitivity in the accurate map database.

Here, it is more preferable that the weight extraction area is a highway or a bridge having a straight running time equal to or greater than a threshold value.

Thereafter, the scale of the acceleration sensor is corrected based on the calculated weight information average value (S205), thereby reducing the distance error that may occur due to the acceleration sensor scale error.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is clearly understood that the same is by way of illustration and example only and is not to be taken by way of limitation, Various changes and modifications will be possible.

Claims (7)

A navigation inertial sensor calibration method comprising:
An acceleration sensor calibration step of calibrating the acceleration sensor based on the vehicle speed information using the position information received from the GNSS;
A tilt angle calculating step using the acceleration sensor value;
Generating a compensation matrix using the tilt angle;
And calibrating the gyro sensor. ≪ Desc / Clms Page number 20 >
The method according to claim 1,
The acceleration sensor calibration step
A weight extracting and storing step of extracting and storing weight information by comparing information of the NMEA speed information received by the GNSS receiver and the speed of the acceleration sensor;
Determining whether the number of the weight information is equal to or greater than a preset threshold value;
Averaging the weight information when the number of weight information is equal to or greater than a predetermined threshold; And
And a scale correction step of correcting the scale of the acceleration sensor based on the calculated average value.
3. The method of claim 2,
Wherein the weight information is calculated by a ratio of the NMEA speed information to acceleration data integration information of the acceleration sensor using the NMEA speed information as a reference value.
The method of claim 3,
Wherein the weight information is further extracted using the precision map database when the number of weight information is less than or equal to the preset threshold value.
5. The method of claim 4,
Wherein the weight information extracted further is extracted from the precise map database by determining a weight extraction area having good open coverage and good GNSS reception sensitivity.
6. The method of claim 5,
Wherein the weight extraction area is a highway or a bridge having a straight running time equal to or greater than a threshold value.
The method according to claim 1,
Wherein the tilt angle is a pitch value and a roll value.

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