KR20210134597A - Method and apparatus for measuring position with multiple imu sensors - Google Patents

Abstract

In the present invention, disclosed is a position measuring device that comprises a PCB substrate containing a primary MEMS-based IMU sensor, a plurality of secondary MEMS-based IMU sensors, and a temperature sensor; and a cooling means disposed under the PCB substrate. An object of the present invention is to realize a high-precision position measuring sensor while lowering the manufacturing cost.

Description

Position measurement method and device using multiple IMU sensors {METHOD AND APPARATUS FOR MEASURING POSITION WITH MULTIPLE IMU SENSORS}

The present invention relates to a sensor for measuring the position and posture of an object, and more particularly, to a method and apparatus for measuring a position using a plurality of IMU sensors.

With the advent of the 4th industrial revolution, various attempts are being made to expand and apply telematics technology to construction and agricultural machinery. As the application of such telematics technology is attempted, the demand for high-precision position/position measurement sensors according to the automation/unmanned construction of construction equipment is increasing at civil construction sites. In the agricultural machinery field, the need for a position measuring sensor is also increasing more than ever since the development of advanced agricultural machinery is being carried out according to the 4th industrial revolution.

In order to apply telematics technology to construction equipment and agricultural machinery, high-precision positioning devices are required.

On the other hand, many high-precision position measuring devices have been developed in the market to meet these needs. However, such a high-precision position measuring sensor has a disadvantage that its price is very high.

In the case of using an IMU (Inertial Measurement Unit) sensor based on MEMS (Micro Electro-Mechanical Systems) to reduce cost, there is a disadvantage in that the measurement accuracy is greatly reduced due to the errors of the accelerometer and gyroscope built into the IMU sensor. .

Specifically, a gyroscope measures angular velocity, unlike an acceleration sensor that measures acceleration. Angular velocity refers to the angle of rotation per hour. The measurement principle of the gyro sensor is as follows.

For example, if the angular velocity is 0 degrees/sec in a horizontal state (stationary state), and the object is tilted by 50 degrees while moving for 10 seconds, the average angular velocity for 10 seconds is 5 degrees/sec. To find the angle from the angular velocity, you need to integrate it over the whole time. The gyroscope can calculate the tilt angle by measuring the angular velocity in this way and integrating the angular velocity over the entire time. However, an error occurs in the gyroscope due to the influence of temperature, and this error is accumulated during the integration process and the final value drifts. Therefore, the gyroscope must also use a temperature sensor to compensate for the error.

Also, from the point of view of a long time in the stationary state, the tilt angle calculated by the accelerometer shows a correct value, but the gyroscope shows an incorrect value as time goes by. Conversely, in terms of short moving time, the gyroscope shows the correct value, but the accelerometer may give a different calculated value than the tilted angle. Therefore, using both the accelerometer and the gyroscope, an algorithm that can compensate for each disadvantage is applied to calculate the roll or pitch value. A widely applied compensation method and filtering is a Kalman filter or a complementary filter.

Furthermore, gyroscopes and accelerometers have temperature drift in which the output fluctuates with temperature changes. The bias of the accelerometer and the gyroscope according to the temperature change causes an error in calculating the Euler angle by fusing the outputs of the two sensors with a Kalman filter.

Since the temperature drift means the error of the sensor, a temperature compensation method to eliminate the temperature drift has been proposed. The most basic temperature compensation method is to measure the internal temperature of the sensor and the sensor output for each temperature, and obtain a compensation model expressed as a polynomial for temperature using a curve fitting method for the measured temperature and output data. When the compensation model is obtained, the compensation value is calculated by inputting the temperature inside the sensor into the compensation model, and the compensated output is obtained by subtracting the compensation value from the sensor output. Although such a compensation model is a function of temperature, compensation models that are expressed as a function of only temperature are often not well compensated due to the characteristics of the sensor.

In US Patent No. 5,416,585, a compensation model using the temperature difference between the spool and the housing or the temperature differential of the spool was used to eliminate the temperature drift of the optical fiber gyroscope. For this purpose, a compensation model using the resonance frequency, driving voltage, and quadrature control voltage of the sensing structure was used without using a temperature sensor.

However, since this compensation model is a method that can be applied only to a specific sensor, it is difficult to apply temperature compensation in a general case.

An object of the present invention is to realize a high-precision position measuring sensor while lowering manufacturing cost.

In particular, the present invention intends to implement a position measuring device that enables high-precision position measurement while using a MEMS-based IMU sensor.

Further, in the present invention, it is intended to implement a position measuring device capable of reducing the error according to the temperature of the measured sensor value to a minimum by maintaining a constant temperature of the IMU sensor.

In addition, an object of the present invention is to provide a position measurement method capable of compensating for an error in a MEMS-based IMU sensor using measurement values of a plurality of IMU sensors.

In an embodiment of the present invention, preparing a PCB board including a main MEMS-based IMU sensor and a plurality of auxiliary MEMS-based IMU sensors as a position measurement method, the average of the values measured by the plurality of auxiliary MEMS-based IMU sensors Obtaining, based on the average value, correcting the value measured by the main MEMS-based IMU sensor; provides a position measurement method comprising a.

In another embodiment of the present invention, as a position measurement method, preparing a PCB board including a main MEMS-based IMU sensor and a plurality of auxiliary MEMS-based IMU sensors, the standard deviation of values measured by the plurality of auxiliary MEMS-based IMU sensors It provides a position measurement method comprising the step of obtaining , and correcting a value measured by the main MEMS-based IMU sensor based on the standard deviation.

In another embodiment of the present invention, measuring the temperature of the substrate on which the main MEMS-based IMU sensor and the plurality of auxiliary MEMS-based IMU sensors are disposed, adjusting the temperature of the substrate based on the measured temperature It provides a position measurement method further comprising.

In an embodiment of the present invention, a position measuring device including a main MEMS-based IMU sensor, a PCB substrate including a plurality of auxiliary MEMS-based IMU sensors and a temperature sensor as a position measuring device, and a cooling means disposed under the PCB substrate provides

In another embodiment of the present invention, the plurality of auxiliary MEMS-based IMU sensors provide a position measuring device having eight.

In another embodiment of the present invention, there is provided a position measuring device in which the plurality of MEMS-based IMU sensors are disposed around the main MEMS-based IMU sensor.

In another embodiment of the present invention, the cooling means provides a position measuring device including a Peltier module disposed under the PCB substrate and a fan driven cooler disposed under the Peltier module.

By the position measuring apparatus and method proposed in the present invention, high-precision position measurement is possible even at low manufacturing cost.

1 shows a configuration of a position measuring device according to an embodiment according to the present invention.
2 shows a hardware configuration diagram of the position measuring apparatus 100 according to an embodiment of the present invention.
3 shows the overall operation algorithm 200 of the position measuring device 100 according to the present invention.
4 illustrates an operation algorithm 300 of the calibration unit 211 .
5 shows an operation algorithm 400 of the calibration unit 221 .
FIG. 6 is a flowchart of data processing in a stage before the complementary filter 230 in FIG. 3 .
7 shows a dynamic drift reduction algorithm for a gyro sensor.
8A to 8C are block diagrams showing the contents related to the complementary filter 230 .

Hereinafter, an image generating apparatus and method according to each embodiment of the present invention will be described with reference to the accompanying drawings.

The following examples are detailed descriptions for helping understanding of the present invention, and not limiting the scope of the present invention. Accordingly, equivalent inventions performing the same functions as the present invention will also fall within the scope of the present invention.

In addition, in adding reference numerals to the components of each drawing, it should be noted that the same components are given the same reference numerals as much as possible even though they are indicated on different drawings. In addition, in describing the present invention, if it is determined that a detailed description of a related known configuration or function may obscure the gist of the present invention, the detailed description thereof will be omitted.

In addition, in describing the components of the present invention, terms such as first, second, A, B, (a), (b), etc. may be used. These terms are only for distinguishing the components from other components, and the essence, order, or order of the components are not limited by the terms. When a component is referred to as being “connected” or “connected” to another component, it is understood that the other component may be directly connected or connected to the other component, but other components may exist in between. it should be On the other hand, when it is said that a certain element is "directly connected" or "directly connected" to another element, it should be understood that no other element is present in the middle. Other expressions describing the relationship between elements, such as "between" and "immediately between" or "neighboring to" and "directly adjacent to", should be interpreted similarly.

In addition, the terms used in the present application are only used to describe specific embodiments, and are not intended to limit the present invention. The singular expression includes the plural expression unless the context clearly dictates otherwise. In the present application, terms such as “comprise” or “have” are intended to designate that a feature, number, step, operation, component, part, or combination thereof described in the specification exists, but one or more other features It should be understood that this does not preclude the existence or addition of numbers, steps, operations, components, parts, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in a commonly used dictionary should be interpreted as having a meaning consistent with the meaning in the context of the related art, and should not be interpreted in an ideal or excessively formal meaning unless explicitly defined in the present specification. does not

1 shows a configuration of a position measuring device according to an embodiment according to the present invention. The position measuring apparatus 100 according to the present invention includes a PCB substrate 10 and a cooling means attached to a lower portion of the substrate. The cooling means is not a means for continuously lowering or increasing the heat generated in the PCB substrate 10, but controlling or maintaining the temperature of the PCB substrate 10 in stages to a constant temperature (eg, room temperature 25° C.) is a means to Preferably, the cooling means may comprise a peltier module 20 and a fan drive cooler 30 . A pad may be used instead of the fan driven cooler 30 .

Meanwhile, the main IMU sensor 12 and the plurality of auxiliary IMU sensors 14 are disposed on the PCB substrate 10 . The IMU sensors 12 and 14 are preferably MEMS-based in terms of cost reduction. Also preferably, 8 auxiliary IMU sensors 14 are arranged, and it is preferable that the main IMU sensors 12 be arranged in a 3 × 3 matrix structure with the main IMU sensor 12 in the center.

A plurality of auxiliary IMU sensors 14 may be used to correct errors in values measured by the primary IMU sensor 12 .

As an embodiment, an average of the values measured by the plurality of auxiliary IMU sensors 14 is obtained, the average value is compared with a value measured by the primary IMU sensor 12 , and the primary IMU sensor 12 is measured in proportion to the difference. values can be corrected.

As another embodiment, the standard deviation of the measurement values of the plurality of auxiliary IMU sensors 14 may be obtained, and the measurement values of the main IMU sensor 12 may be corrected based on the standard deviation.

2 shows a hardware configuration diagram of the position measuring apparatus 100 according to an embodiment of the present invention.

A main control unit (MCU) 90 receives the measured values measured from each of the IMU sensors 12 and 14 and compensates for the error. The method of compensating for the error is as described above. A method of calculating the average of the measured values of all the auxiliary IMU sensors or obtaining the standard deviation of the auxiliary IMU sensors and correcting the measured values of the main IMU sensor based on this may be used. These are merely examples, and it should be noted that the method of correcting the measurement value of the primary IMU sensor using the measurement value of the secondary IMU sensor is not limited thereto.

The wireless communication module 40 enables communication with the smart device 70 via the antenna 62 . The wireless communication module 40 may support, for example, Bluetooth, Wi-Fi, NFC, and the like.

The smart device 70 preferably uses a smart device (including a dedicated app) rather than a dedicated terminal.

The GPS sensor module 50 transmits the GPS signal received through the antenna 64 to the main control device 90 .

The main control device 90 may enhance the accuracy of the GPS sensor by performing Real Time Kinematic (RTK) surveying using the position correction value received from the virtual base station (VRS) 80 through the smart device 70 . .

The temperature measuring sensor 16 measures the temperature of the PCB substrate 10 and transmits the measured value to the main control device 90 . The main control device 90 may control the operation of the Peltier module 20 so as to constantly maintain the temperature of the PCB substrate 10 based on the measured temperature value. If necessary, a cooler such as a fan drive cooler 30 may be further attached to the Peltier module 20 . Alternatively such cooling means may be configured as a pad.

In this way, by maintaining the temperature of the PCB substrate 10 constant, it is possible to maintain the temperature of the IMU sensors disposed on the PCB substrate 10 constant, and thus the error of the gyroscope and the accelerometer sensor due to the temperature fluctuation. can be reduced to a minimum.

3 to 6 are diagrams for explaining an algorithm 200 for operating the position measuring device 100 according to the present invention.

First, FIG. 3 is a view for explaining the entire operation algorithm 200 of the position measuring apparatus 100 according to the present invention, FIG. 4 is a view for explaining the operation algorithm 300 of the calibration unit 211, and FIG. 5 is It is a diagram explaining the operation algorithm 400 of the calibration unit 221 .

The value measured by the gyroscope 210 is biased, scaled, and temperature compensated by the calibration unit 211 to generate a delta angle (see FIG. 4 ). The delta angle is input to the dynamic drift reducing unit 212 to generate an angular velocity, and the thus generated angular velocity is input to the complementary filter 230 .

Meanwhile, the acceleration measurement value measured by the accelerometer 220 is biased, scaled, and temperature compensated by the calibration unit 221 to generate acceleration (see FIG. 5 ). The generated acceleration is input to the complementary filter 230 through the dynamic scale factor adjusting unit 222 .

In FIG. 6 , the process before the complementary filter 230 in FIG. 3 , that is, data processing of the calibration unit 211 and the dynamic drift reducing unit 212 for the gyroscope 210 , and calibration for the accelerometer 220 . A flowchart related to data processing of the unit 221 and the dynamic scale factor adjusting unit 222 is shown. Hereinafter, this will be described in detail.

sensor value Read (S1100)

When the data read from the first IMU sensor in the MCU 90 is displayed as follows, a ₁ is a 3-axis acceleration vector, ω ₁ is a 3-axis angular velocity vector, m ₁ is a 3-axis geomagnetic vector, and t ₁ is the temperature is a scalar quantity.

Since 9 IMU sensors are connected to the MCU, the data read from all sensors can be displayed as follows.

First IMU sensor data:

Second IMU sensor data:

...

Ninth IMU sensor data:

Average sensor value calculation (S1200)

Data read from nine IMU sensors are averaged for the same sensor type and axis.

만큼 줄어드는 것으로 알려져 있다.If each sensor value contains white noise, if n values are averaged, the noise of the sensor values is

is known to decrease.

If the output values of nine sensors are averaged as described above, it can be expected that the average value will be three times more precise than the value measured from one sensor.

in the calibration unit 221 Accelerometer temperature compensation, bias scale adjustment (S1300)

Hereinafter, it will be described with reference to FIG. 5 together.

Bias correction by temperature

The temperature coefficient means the rate of change of the value of the acceleration sensor according to the temperature. Assuming that the temperature coefficient is already known in advance by the function of correcting the change of each sensor value due to the temperature, it is corrected by the following equation.

Output value = temperature coefficient × temperature + input value

Sensor's Intrinsic Bias and Scale Calibration

Assuming that the sensor's intrinsic bias and scale values are already known in advance by the correction function, they are corrected according to the following equation.

Output = Scale × (Input - Bias)

IIR filter

The IIR filter is a typical first-order low-pass filter.

Gravity rotation compensation

If the accelerometer is mounted on the PCB in an inclined state or the PCB is mounted in a tilted state on the metal frame, the Euler angle calculated by the filter may not be 0° even if the frame is level. This is because the angle is corrected when the direction of gravitational acceleration is slightly inclined. In order to prevent this problem, it is necessary to correct the acceleration vector so that the acceleration vector becomes (0, 0, -1) when the sensor becomes horizontal. This is corrected by multiplying the acceleration vector by the gravitational rotation matrix in the above figure.

in the calibration unit 211 gyro Sensor temperature compensation, bias scale adjustment (S1300')

Hereinafter, it will be described with reference to FIG. 4 together.

Bias correction by temperature

The temperature coefficient means the rate of change of the gyro sensor value according to the temperature. Assuming that the temperature coefficient is already known in advance by the function of correcting the change of each sensor value due to the temperature, it is corrected by the following equation.

Output value = temperature coefficient × temperature + input value

Sensor's Intrinsic Bias and Scale Calibration

Assuming that the sensor's intrinsic bias and scale values are already known in advance by the correction function, they are corrected according to the following equation.

Output = Scale × (Input - Bias)

integrator

The reason for integrating the sensor value is that when the cycle of sampling and storing the sensor value in the memory is different from the cycle of reading the memory value from the MCU, when the sensor value is sampled to increase the sensor measurement accuracy, it is integrated in the memory. Also, when the MCU reads, it is possible to increase the precision of the sensor value by reading the difference between the value at the time of previous reading and the value at the time of current reading.

Dynamic scale for the acceleration sensor in the dynamic scale filter adjustment unit 222 factor Adjustment (S1400)

Since the acceleration measured by the acceleration sensor includes gravity, the velocity and position are calculated by integrating after removing the gravity. Occurs. Here, a dynamic scale factor adjustment algorithm for adjusting such a scale factor will be described.

<Dynamic Scale Factor Adjustment Algorithm>

를 1로 설정한다.(

=1)1. Scale factor

is set to 1. (

=1)

를 계산한다.2. The magnitude of the measurement value of the accelerometer

to calculate

를 업데이트 한다.3. Subject to the following conditions

update

를 계산한다.4. Scale-adjusted acceleration

to calculate

5. If a new measured value is received, repeat the process from step 2.

는 1보다 미소하게 큰 값을 사용한다. (Ex:

=1.0001)* Variables used in the above process

uses a value slightly larger than 1. (Ex:

=1.0001)

dynamic drift in the reduction part 212 gyro dynamic to sensor drift Decrease (S1400')

The rotation angle is calculated by integrating the measured values of the gyro sensor. At this time, if even a small bias drift is accumulated through integration, a large error occurs. Here, we describe the use of a dynamic drift reduction algorithm for the gyro sensor to minimize such bias drift.

<Dynamic drift reduction algorithm for gyro sensor>

It will be described with reference to FIG. 7 .

는 에러가 포함되지 않은 이상적인 값인데, Gyro 센서가 측정을 할 때

와

가 포함된다.

는 센서가 움직이지 않는 일정한 기간의 측정값을 평균하여 계산한 초기 바이어스 값이다.

는 시간에 따라 미소하게 변하는 바이어스 값으로 여기서 제거하고자 하는 대상이다.

is an ideal value without error, and when the gyro sensor measures

Wow

is included

is the initial bias value calculated by averaging the measured values of a certain period in which the sensor does not move.

is a bias value that slightly changes with time and is an object to be removed here.

)에는 민감하게 반응해야 하고 큰 오차(자이로 센서가 회전하여 발생하는 실제 값의 변화)에는 둔감하게 반응해야 한다. 그래서 오차의 부호만을 고려한다.Binary I-controller has a small error (

) should respond sensitively and insensitively respond to large errors (changes in actual values caused by rotation of the gyro sensor). Therefore, only the sign of the error is considered.

Binary I-controller works as follows.

는 는 상수이고 SIGN()함수는 다음과 같이 동작한다.here

is a constant, and the SIGN() function operates as follows.

Now, with reference to the complementary filter 230 in FIG. 3 , the latter processes will be described.

The inclination for each axis output from the complementary filter 230 undergoes orthogonality correction in the correction unit 240 , and the Euler angle is calculated in the calculator 250 . The calculated Euler angle is transmitted to the communication unit 260 . Preferably, the communication unit may use a CAN or RS-232 protocol. A more detailed description is given below.

Complementary Filter (230)

The gyro sensor has a bias, but because it responds sensitively to changes in angle, a high pass filter is used. low pass filter) is used.

는 자이로 센서 값에서 바이어스를 제거한 값이고,

는 가속도 센서로부터 측정한 각도다. 위 식을 다시 쓰면,here

is the value after removing the bias from the gyro sensor value,

is the angle measured by the accelerometer. If we rewrite the above expression,

am. It is shown in a block diagram as shown in FIG. 8A.

)와의 차를 이득 1/a를 곱하여

에 적분한다. 그리고 자이로 센서로부터 측정한 각속도(

)는

에 그대로 적분한다. 여기서 주의할 점은,

는 센서 좌표계를 기준으로 하는 각속도 값이고,

는 전역 전역 좌표계를 기준으로 하는 각도 값이라는 점이다. 이 때문에 적분하는 방법에 차이가 있다.Looking at the block diagram of FIG. 8A, the angle measured from the accelerometer (

) by multiplying the difference with the gain 1/a

integrate into And the angular velocity measured from the gyro sensor (

)Is

Integrate as it is It should be noted here,

is the angular velocity value relative to the sensor coordinate system,

is the angular value relative to the global global coordinate system. Because of this, there is a difference in the integration method.

A rotation matrix is used to handle the sensor's attitude angle in 3D space. This is because the rotation matrix can easily calculate the sum and difference of angles compared to Euler angles.

rotation matrix

에 의한 회전행렬

은 다음과 같이 정의된다.Euler angle

rotation matrix by

is defined as

(Note that the rotation order is the z-axis, y-axis, and x-axis order)

로부터 오일러각을 다음과 같이 계산할 수 있다.rotation matrix

The Euler angle can be calculated as

는 행렬

의 i 행과 j 열의 원소이다.

is the matrix

is an element in row i and column j of

filter implementation

를 측정하고, 가속도 센서로부터 가속도

를 측정하여 센서의 자세각을 계산하는 과정이다.Here is the angular velocity from the gyro sensor

is measured and the acceleration from the accelerometer

It is the process of calculating the attitude angle of the sensor by measuring

gyro Bias value of the sensor

An ideal gyro sensor should output 0 when it is not moving, but most real sensors output a non-zero biased value. So it is necessary to remove the biased value from the value measured by the sensor. The next step is to find the average of the measured signals to act like a low pass filter.

n is the number of averages, and it should be limited so that it does not become larger than a certain value. That is, until n reaches a specific value, it increases by 1 every time it is averaged, and when it reaches a specific value, a fixed value is used.

integral of angular velocity

The process of integrating the angular velocity is indicated by a dotted line box in the block diagram (FIG. 8B).

와

의 평균

간의 차를 계산함으로 자이로 센서의 바이어스를 제거한 각속도

를 계산한다.

는 각속도 센서의 데이터 측정 주기이다.First, the angular velocity measured from the gyro sensor

Wow

average of

Angular velocity with the bias of the gyro sensor removed by calculating the difference between

to calculate

is the data measurement period of the angular velocity sensor.

은 현재 센서의 자세각을 표현하는 행렬이다. 자이로 센서로부터 읽은 각속도를 회전행렬의 변위

로 바꾸어

에다가 적분(회전 행렬간의 곱) 한다. rotation matrix

is a matrix representing the attitude angle of the current sensor. The angular velocity read from the gyro sensor is the displacement of the rotation matrix.

change to

Integrate (multiplication between rotation matrices).

with gravitational acceleration detailed angle correction

The process of correcting the posture angle with the acceleration of gravity is indicated by a dotted line box in the block diagram of FIG. 8C .

을 보정할 수 있다. 하지만 이러한 조건은 가속도 센서에 작용하는 힘이 오직 중력만 있을 때 가능하다. 중력가속도와 이러한 힘을 분리하여 측정할 수 없기 때문에, 중력가속도 외 다른 힘이 작용하고 있는 조건은

인지 확인해 보는 것이 제일 간단한 방법이다.Since gravitational acceleration always points toward the center of the earth, g = (0,0,-9.81) is measured when no other force is applied to the accelerometer. By comparing the acceleration measured by the accelerometer and the acceleration due to gravity,

can be corrected. However, this condition is possible only when the force acting on the accelerometer is only gravity. Since gravitational acceleration and these forces cannot be measured separately, the conditions under which forces other than gravitational acceleration are acting are

The simplest way is to check if it is.

에는 중력가속도와 센서의 가속에 의한 다양한 종류의 가속도가 포함되어있다. 이를 식으로 나타내면 다음과 같다.Acceleration measured by the accelerometer

includes various types of acceleration caused by gravity acceleration and sensor acceleration. Expressing this as an expression:

는 선가속도이며

는 관성좌표계에서 중력가속도 값 (0, 0, -9.81)을 가진다.here

is the linear acceleration

has the value of gravitational acceleration (0, 0, -9.81) in the inertial coordinate system.

가 0이고 각속도

가 0일 때는 다음과 같이 간단히 쓸 수 있다.Linear acceleration in the above equation

is 0 and the angular velocity

When is 0, it can be simply written as:

In terms of Euler angles, we get:

로

을 계산하고

을 다음과 같이 업데이트 한다.saved here

as

to calculate

is updated as follows.

는 중력으로 찾은 각도의 오차를 업데이트하는 비율(이득)이다. 중력벡터의 크기가 1g 근처일때 이득이 커야하고 1g에서 멀어질수록 이득이 적어야 한다. 그래서 이득을 다음과 같이 계산하도록 하였다.

is the rate (gain) updating the error of the angle found by gravity. When the magnitude of the gravity vector is near 1g, the gain should be large, and the gain should be small as the magnitude of the gravity vector is near 1g. So, the gain was calculated as follows.

compensator (240)

.If the rotation matrix is continuously updated, the orthogonality of the matrix is not satisfied because small errors in numerical calculations are accumulated.

.

In order to maintain the orthogonality of the matrix, the rotation matrix is corrected using the following equation.

calculator (250)

로부터 계산할 수 있다. 다음 식에서 사용되는

는 행렬

의 i 행과 j 열의 원소이다.rotation matrix

can be calculated from used in the following expression

is the matrix

is an element in row i and column j of

The following equations for calculating Euler angles are derived for z-y-x rotation.

가

일 때:i)

go

when:

가

일 때:ii)

go

when:

A description of the communication unit 260 will be omitted.

The above description is merely illustrative of the technical spirit of the present invention, and various modifications and variations will be possible without departing from the essential characteristics of the present invention by those skilled in the art to which the present invention pertains. Accordingly, the embodiments disclosed in the present invention are not intended to limit the technical spirit of the present invention, but to explain, and the scope of the technical spirit of the present invention is not limited by these embodiments. The protection scope of the present invention should be construed by the following claims, and all technical ideas within the scope equivalent thereto should be construed as being included in the scope of the present invention.

10: PCB board 12: Main IMU sensor
14: auxiliary IMU sensor 16: temperature sensor
20: peltier module 30: fan driven cooler
40: wireless communication module 50: GPS sensor module
62, 64: antenna 70: smart device
80: virtual base station 90: main control unit
100: position measuring device 200: overall operation algorithm of the position measuring device
210: gyroscope 211, 221: calibration unit
212: dynamic drift reduction unit 222: dynamic scale factor adjustment unit
230: complementary filter 240: correction unit
250: calculation unit 260: communication unit
300, 400: Calibration unit operation algorithm

Claims (7)

A method for measuring position, comprising:
preparing a PCB board including a primary MEMS-based IMU sensor and a plurality of secondary MEMS-based IMU sensors;
obtaining an average of the values measured by the plurality of auxiliary MEMS-based IMU sensors;
Correcting the value measured by the main MEMS-based IMU sensor based on the average value; Containing,
How to measure position. A method for measuring position, comprising:
preparing a PCB board including a primary MEMS-based IMU sensor and a plurality of secondary MEMS-based IMU sensors;
obtaining a standard deviation of values measured by the plurality of auxiliary MEMS-based IMU sensors;
Correcting the value measured by the main MEMS-based IMU sensor based on the standard deviation;
How to measure position. 3. The method according to claim 1 or 2,
measuring a temperature of a substrate on which the main MEMS-based IMU sensor and a plurality of auxiliary MEMS-based IMU sensors are disposed;
Further comprising; adjusting the temperature of the substrate based on the measured temperature;
How to measure position. A position measuring device comprising:
as a PCB substrate;
main MEMS-based IMU sensor;
a plurality of secondary MEMS-based IMU sensors; and
comprising a temperature sensor;
PCB board;
Including cooling means disposed under the PCB substrate,
position measuring device. 5. The method of claim 4,
8 of said plurality of secondary MEMS-based IMU sensors;
position measuring device. 6. The method of claim 5,
wherein the plurality of MEMS-based IMU sensors are disposed around the primary MEMS-based IMU sensor;
position measuring device. 5. The method of claim 4,
The cooling means includes a Peltier module disposed under the PCB substrate and a fan-driven cooler disposed under the Peltier module,
position measuring device.

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