KR101239864B1 - System for navigation system using multi-sensor and providing method thereof - Google Patents

Abstract

Disclosed are a navigation system using multiple sensors and a method of providing the same. The navigation system using the multiple sensors includes an IMU (Inertial Measurement Unit) for measuring and outputting inertial data according to the movement of a moving object, a GPS module for receiving a GPS (Global Positioning System) signal corresponding to the moving object, and the IMU from the IMU. Navigation for calculating at least one of attitude information, speed information, or position information of the moving object using the measured inertial data, OBD speed information output from the OBD installed in the moving object, and GPS information output from the GPS module. It includes a calculation module.

Description

Navigation system using multi-sensor and its providing method {System for navigation system using multi-sensor and providing method

The present invention relates to a navigation system, and more particularly, to improve performance by using inertial data output from an inertial measurement device and OBD information installed in a mobile body together with GPS information received from a GPS (Global Positioning System) module. A navigation system and a method of providing the same.

In general, navigation systems using GPS signals are widely used. However, since the navigation system is difficult to know the location information when the GPS signal is not received, a navigation system using an inertial sensor or a navigation system that finds the location information of a moving object using the GPS and the inertial sensor has been developed.

Such a navigation system can estimate the position of a moving object using an inertial sensor based on microelectromechanical systems (MEMS) called an inertial measurement unit (IMU). The navigation system finds the position information of the moving object by using a predetermined navigation calculation algorithm. In this case, the position information is obtained by integrating inertial data (eg, acceleration, angular velocity, etc.) obtained in the IMU to obtain a desired physical quantity. As a result, a drift phenomenon in which errors continue to accumulate may occur, thereby degrading the accuracy of the entire system.

In addition, the conventional navigation system determines that the motion (eg, pitch, roll, yaw, etc.) of the movable body is changed due to vibration or noise of the movable body even when the movable body is stationary. Alternatively, it may be determined that there is forward speed. This misjudgment may further increase the error of the location information due to the accumulated drift phenomenon.

Therefore, when calculating the velocity information of the moving object, which is one of the state variables used to estimate the position of the moving object, a system or method for estimating a more accurate position, speed, or attitude by using the information measured by the moving body itself is provided. Required.

The present invention has been proposed to solve the above problems, and provides a navigation system with improved accuracy by using vehicle speed information embedded in a moving body (for example, a vehicle) itself.

In addition, by using a separate altitude sensor (for example, barometer) separate from the altitude information included in the GPS information and to use the same for estimating the position of the vehicle to provide a more accurate navigation system.

Navigation system using a multi-sensor according to the present invention for achieving the above object is an IMU (Inertial Measurement Unit) for measuring and outputting the inertial data according to the movement of the moving object, GPS (Global Positioning System) signal corresponding to the moving object GPS module for receiving a signal, and the inertial data measured from the IMU, the OBD speed information output from the OBD installed in the mobile body, and the GPS information output from the GPS module, the posture information of the mobile body, the speed information, Or a navigation calculation module for calculating at least one of the location information.

The navigation calculation module may be configured to estimate a bias of a gyro sensor included in the IMU based on the first filter module for calculating the attitude information and the speed information of the moving object and the inertial data output from the IMU. A bias estimation module, and a motion module for calculating INS attitude information and INS speed information of the moving body based on a bias value estimated by the bias estimation module, the inertia data, and feedback information of the first filter module. The first filter module reduces noise based on the INS attitude information, INS speed information, OBD speed information, GPS speed information included in the GPS information, and GPS direction information calculated by the motion module. The posture information and the speed information can be calculated.

The navigation calculation module is a second filter for calculating the position information of the moving body based on the attitude information, the speed information, the GPS position information output from the GPS module, and the INS position information calculated by the motion module. The module may further include.

The navigation system using the multiple sensors further includes an altitude sensor for measuring the altitude of the moving object and outputting the measured altitude information to the navigation calculation module, wherein the navigation calculation module is the altitude information output from the altitude sensor. The location information of the moving object may be further calculated using.

The second filter module receives the altitude information from the altitude sensor, and reduces the noise based on the received altitude information, the attitude information, the speed information, the GPS location information, and the INS location information. The location information of can be calculated.

At least one of the first filter module and the second filter module may be implemented as a Kalman filter. In addition, the first filter module may use the following equation as a system model of the Kalman filter.

In addition, the first filter module may use the following two equations as the observation model of the Kalman filter.

및

And

On the other hand, the second filter module,

The following equation can be used as a system model for Kalman filter.

The following equation can be used as the observation model of the Kalman filter.

In addition, the following equation may be further used as an observation model of the Kalman filter.

The navigation system using multiple sensors for solving the technical problem is an IMU for measuring and outputting the inertial data according to the movement of the moving object, GPS module for receiving a GPS (Global Positioning System) signal corresponding to the moving object, the moving object An altitude sensor for measuring corresponding altitude information, a bias estimation module for estimating a bias of a gyro sensor included in the IMU based on the inertial data measured from the IMU, the attitude information of the moving body and the INS attitude information and INS speed information of the moving body are calculated based on a first filter module for calculating speed information, a bias value estimated by the bias estimation module, the inertia data, and feedback information of the first filter module. And a motion module to measure the altitude information, the attitude information, the speed information, and the GPS module. And a second filter module configured to calculate the position information of the moving object with reduced noise based on the GPS position information included in the GPS information output from the control unit and the INS position information calculated by the motion module based on the inertial data. The first filter module may include the INS attitude information calculated by the motion module, the INS speed information, OBD speed information output from an OBD installed in the moving object, GPS speed information included in the GPS information, and GPS progression. The attitude information and the speed information with reduced noise are calculated based on the direction information.

Navigation system using a multi-sensor for solving the technical problem is to receive the OBD speed information from the OBD system installed in the mobile body to output the speed information of the moving object, the received OBD speed information, the GPS information, and the inertia The position information of the mobile body is estimated using data.

To provide a navigation system using multiple sensors to solve the technical problem, the navigation system using multiple sensors measures the inertial data according to the movement of the moving object, and receives a GPS signal corresponding to the moving object, the multi-sensor Receiving OBD speed information from an OBD installed in the moving object by using the navigation system; and using the GPS information included in the inertial data, the OBD speed information, and the GPS signal, the attitude information, the speed information, or Calculating at least one of the location information.

Computing at least one of the attitude information, speed information, or position information of the moving object, estimating a bias value of a gyro sensor included in the IMU based on the inertial data, the bias value, the Calculating INS attitude information and INS speed information of the moving object based on inertia data and feedback information including previous attitude information and previous speed information, and the INS attitude information, INS speed information, the OBD speed information, and Computing the posture information and the speed information of which noise is reduced based on the GPS speed information included in the GPS information and the GPS traveling direction information.

The calculating of at least one of the posture information, the speed information, or the position information of the moving object may include calculating the INS position based on the posture information, the speed information, the GPS position information output from the GPS module, and the inertial data. The method may further include calculating the position information of the moving body based on the information.

The method for providing a navigation system using the multiple sensors further includes measuring altitude information of the moving object through an altitude sensor, and calculating at least one of attitude information, speed information, or position information of the moving object comprises: And calculating location information of the moving object having reduced noise based on the altitude information, the attitude information, the speed information, the GPS location information, and the INS location information measured by the altitude sensor. The navigation system providing method using the multiple sensors may be stored in a computer-readable recording medium recording a program.

The navigation system using the multiple sensors and the method of providing the same according to the present invention use the velocity information measured by the moving body to perform the position estimation of the moving object, thereby making it possible to estimate the position more accurately than the conventional navigation system. have.

In addition, in order to reduce the error of the altitude information included in the GPS signal, the altitude information measured using a separate altitude sensor is used together when performing the position estimation of the moving object, thereby providing a more accurate navigation system. have.

1 shows a schematic configuration of a navigation system using multiple sensors according to an embodiment of the present invention.
2 is a view for explaining a navigation algorithm of the navigation system using multiple sensors according to an embodiment of the present invention.
3 is a view illustrating a filter input / output value when the first filter is implemented as a Kalman filter in a navigation system using multiple sensors according to an embodiment of the present invention.
4 is a view illustrating a filter input / output value when a second filter is implemented as a Kalman filter in a navigation system using multiple sensors according to an exemplary embodiment of the present invention.
5 is a diagram illustrating a performance comparison between a navigation system using multiple sensors and a navigation system using only a GPS device according to an embodiment of the present invention.
6 is a diagram illustrating another performance comparison example of a navigation system using multiple sensors and a navigation system using only a GPS device according to an embodiment of the present invention.

In order to fully understand the present invention, operational advantages of the present invention, and objects achieved by the practice of the present invention, reference should be made to the accompanying drawings and the accompanying drawings which illustrate preferred embodiments of the present invention.

Also, in this specification, when any one element 'transmits' data to another element, the element may transmit the data directly to the other element, or may be transmitted through at least one other element And may transmit the data to the other component.

Conversely, when one element 'directly transmits' data to another element, it means that the data is transmitted to the other element without passing through another element in the element.

BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, the present invention will be described in detail with reference to the preferred embodiments of the present invention with reference to the accompanying drawings. Like reference symbols in the drawings denote like elements.

In the present specification, the following articles may be included as a reference.

[1] PD Groves, Principles of GNSS , Inertial , and Multisensor Integrated Navigation Systems , Artech house, 2007.

[2] RG Brown and PYC Hwang, Introduction to Random Signals and Applied Kalman Filtering , John Wiley & Sons, 1996.

[3] JA Farrell, Aided Navigation : GPS with High Rate Sensor , McGraw Hill, 2007.

[4] JH Wang, Intelligent MEMS INS / GPS Integration for Land Vehicle Navigation , Doctor of Philosophy, University of Calgary, September 2006.

[5] EH Shin, Accuracy Improvement of Low Cost INS / GPS for Land Application , MS Thesis, University of Calgary, December 2001.

[6] A. Solimeno, Low - Cost INS / GPS Data Fusion with Extended Kalman Filter for Airborne Applications , MS Thesis, Instituto Superior Tecnico, July 2007.

1 shows a schematic configuration of a navigation system using multiple sensors according to an embodiment of the present invention.

Referring to FIG. 1, the navigation system 100 using multiple sensors according to an exemplary embodiment of the present invention includes an IMU 110, a GPS module 120, and a navigation calculation module 130. The navigation system 100 using the multiple sensors may further include an altitude sensor 140. The navigation calculation module 130 may receive speed information of the moving object from an on-board diagnostics (200) included in the moving object (eg, a vehicle) itself. To this end, the navigation system 100 using the multiple sensors may further include a predetermined interface device (not shown) for receiving the speed information output from the OBD 200.

In general, the vehicle is equipped with a variety of sensors for measuring the vehicle, these devices are controlled by the ECU (Electronic Control Unit). The vehicle diagnostic system is evolving, and has recently been established as a standardized system called the OBD 200. In the present specification, the OBD 200 refers to the speed information of the moving body measured by the moving body itself. It may be defined as a meaning including all systems that can output to the navigation system 100 using multiple sensors according to the example.

The IMU 110 may include an acceleration sensor 111 and a gyro sensor 112. The GPS module 120 may receive a GPS signal corresponding to the moving object. The GPS module 120 may calculate GPS information including speed information, moving direction information of the moving object, location information of the moving object, and the like based on the received GPS signal.

 The navigation calculation module 130 may include a bias module 131, a motion module 132, and a first filter module 133. The navigation calculation module 130 may further include a second filter module 134. When the second filter module 134 is included, the navigation calculation module 130 may calculate and output position information of the moving object. When the second filter module 134 is not included, the navigation calculation module 130 may calculate and output attitude information and / or speed information of the moving object.

The altitude sensor 140 refers to a sensor capable of measuring altitude information, and may be implemented as a barometer. When the altitude sensor 140 is provided separately as in the navigation system 100 using multiple sensors according to an exemplary embodiment of the present invention, a position more precise than using only altitude information measured by the GPS module 120 is provided. Estimation may be possible. This is disclosed in detail in the Korean patent application (10-2009-0045740, "Reliability navigation system and its providing method", hereinafter referred to as a "previous application") filed by the present applicant, the description and technical spirit disclosed in the previous application Is incorporated by reference herein and may be treated as a description of the invention. Of course, the navigation system 100 using multiple sensors according to an embodiment of the present invention may not necessarily include the altitude sensor 140, and when the altitude sensor 140 is provided, more accurate position estimation may be possible. Can be.

 Herein, a module may mean a functional and structural combination of hardware for carrying out the technical idea of the present invention and software for driving the hardware. For example, the module may mean a logical unit of a predetermined code and a hardware resource for performing the predetermined code, and means a code that is not necessarily physically connected or does not mean a kind of hardware. It can be easily inferred by the average expert in the art.

The IMU 110 may measure inertial data (eg, acceleration, angular velocity, etc.) of the moving object. The measured inertial data may be output to the bias module 131 and the motion module 132 included in the navigation calculation module 130. The IMU 110 may be implemented as a MEMS sensor.

The GPS module 120 may receive a GPS signal from a GPS satellite (not shown) and generate GPS information based on the received GPS signal. The GPS information may include location information of the moving object, speed information, and information about a traveling direction of the vehicle. The GPS information may be output to the navigation calculation module 130 and used to calculate at least one of attitude information, speed information, or position information of the moving object.

The navigation calculation module 130 may calculate at least one of the attitude information, the speed information, or the position information of the moving object through a navigation algorithm. The navigation calculation module 130 calculates at least one of the attitude information, the speed information, or the position information based on the inertial data measured from the IMU 110, and the navigation algorithm includes the motion module 132. Can be applied by In addition, in order to calculate the navigation algorithm, the bias of the gyro sensor 112 included in the IMU 110 may be first estimated by the bias module 131. Then, using the estimated bias, the motion module 132 may first calculate at least one of posture information, speed information, or position information based on inertial data. In this way, the attitude information, the speed information, or the position information calculated by the motion module 132 may be expressed as INS (Inertial Navigation System) attitude information, INS speed information, or INS location information.

The navigation algorithm is an algorithm that calculates information of the Attitude, Velocity, and Position of the antibody using sensor output values obtained from an inertial measurement unit (IMU) of a body frame. The general navigation algorithm calculates the ideal free body movement, taking into account quaternion world equations, Coriolis force and Gravity models.

However, when the moving object is a vehicle, a simpler navigation algorithm may be applied. For example, as is well known in Reference [4], when the moving object is a vehicle, a vehicle-specific algorithm may be applied. The prior art may be incorporated by reference herein.

Vehicle-specific algorithms ignore the Earth rotation and do not use the Gravity model, but instead use gravity as a constant value. When the posture is obtained, Euler angles are used, and the speed may be limited as in Equation 1 in the direction except for the forward velocity.

,

는 각각 동체좌표계에서 y축과 z축 방향의 속도를 의미할 수 있다.here

,

May refer to velocities in the y- and z-axis directions, respectively.

In addition, the direction cosine matrix (DCM) from the fuselage coordinate system to the navigation coordinate system may be represented by Equation 2.

세 요소는 각각 오일러 각도의 롤(Roll), 피치(Pitch), 헤딩(Heading)을 나타낼 수 있다.here

Each of the three elements may represent a roll, pitch, and heading of the Euler angle.

Here, the method of obtaining the posture, velocity, and position of the body using the angular velocity and acceleration values obtained from the 3-axis gyro sensor 112 and the 3-axis acceleration sensor 111 of the IMU 110 is described in [4]. It can be the same as Equation 3.

은 위도, 경도, 고도로 이루어진 곡선 좌표계(Curvilinear frame)의 위치벡터, 은 항법 좌표계(Navigation frame)의 속도벡터,

은 항법 좌표계를 기준으로 동체 좌표계(Body frame)를 바라본 자세벡터를 나타낸다. 그리고

와

는 각각 상기 IMU(110)에서 측정된 각속도(Angular rates)와 가속도(Accelerations) 값이며,

은 동체 좌표계(Body frame)에서 항법 좌표계(Navigation frame)로의 자세 변환식, 그리고

은 항법 좌표계(Navigation frame)에서 곡선 좌표계(Curvilinear frame)로의 변환식을 나타낼 수 있다.here

Is the position vector of the curvilinear frame consisting of latitude, longitude, and altitude, Is the velocity vector of the navigation frame,

Represents a pose vector looking at the body frame with respect to the navigation coordinate system. And

Wow

Are the angular rates and accelerations measured in the IMU 110, respectively.

Is a pose conversion formula from a body frame to a navigation frame, and

May represent a conversion formula from a navigation frame to a curved frame.

Such an algorithm may be performed by the motion module 132, and the algorithm may be illustrated in FIG. 2.

2 is a view for explaining a navigation algorithm of the navigation system using multiple sensors according to an embodiment of the present invention.

및

을 이용하여

즉 이동체의 자세(

)를 업데이트할 수 있고, 그에 따라 다음 연산에 사용되는

및

을 계산할 수 있다. 또한, 상기 IMU(110)에 의해 측정된

를

을 이용하여 좌표계 전환을 수행하여

을 얻을 수 있고, 얻어진 값과 이전 연산에서의

및 수학식 3에 개시된

을 이용하여 속도를 업데이트 할 수 있다. 또한, 업데이트되는 속도와 이전 위치정보(

)를 이용하여 위치정보를 업데이트 할 수 있다.2 and 3, the motion module 132 is measured by the IMU 110.

And

Using

The posture of the moving object (

) Can be updated accordingly

And

Can be calculated. In addition, as measured by the IMU 110

To

Coordinate conversion using

Can be obtained from the previous operation

And disclosed in Equation 3

You can update the speed by using. In addition, the rate at which updates are made and previous location information (

You can update location information by using).

Through such an algorithm, updated attitude information and speed information obtained from the motion module 132, that is, INS attitude information and INS speed information, may be output to the first filter module 133. In addition, the updated position information, that is, the INS position information obtained from the motion module 132 may be output to the second filter module 134.

On the other hand, the motion module 132 as described above has the advantage of good dynamic characteristics by providing a continuous navigation solution at a relatively high speed (for example, about 100Hz), while the error is accumulated by integration in the calculation process time There is a disadvantage that the error increases as time passes. On the other hand, the GPS information obtained by the GPS module 120 provides a relatively accurate navigation solution within a certain range without increasing the error, but the calculation period (eg, about 1 Hz) is relatively lower than that by the motion module 132. . In addition, GPS information has a problem that is difficult to obtain in multipath or underground or structures. Therefore, when the INS information obtained by the motion module 132 and the GPS information obtained by the GPS module are fused, more accurate results can be obtained. In addition, as described above, when the speed information obtained through the vehicle's OBD 200 is further used, the overall system performance may be improved.

To this end, the navigation calculation module 130 may include the first filter module 133 and the second filter module 134, the first filter module 133 by the motion module 132 The INS information obtained, the information obtained from the OBD 200, and the information obtained by the GPS module 120 may be fused to reduce noise on the attitude information and the speed information of the moving object. In addition, the second filter module 134 may reduce the noise of the position information of the moving object by fusing the INS information and the information on the position information among the information obtained by the GPS module 120. The first filter module 133 and / or the second filter module 134 may be implemented as a Kalman filter.

First, referring to the first filter module 133 may be the same as FIG.

3 is a view illustrating a filter input / output value when the first filter is implemented as a Kalman filter in a navigation system using multiple sensors according to an embodiment of the present invention.

1 and 3, the first filter module 133 may be implemented as a Kalman filter for speed and posture. The first filter module 133 may receive INS attitude information and INS speed information from the motion module 132. In addition, OBD rate information may be received from the OBD 200. In addition, the GPS module 120 may receive GPS speed information and heading information, that is, heading information. Therefore, the first filter module 133 may use forward velocity, roll, pitch, heading, and accelerometer's x-axis bias as state variables. . The error model of the filter may be represented by Equation 4 by perturbing the sensor included in the IMU 110 and the attitude and velocity errors.

And, the spectral density matrix of the input white noise u can be expressed by Equation 5.

Equations 4 and 5 are described in Reference [4], and thus detailed descriptions thereof will be omitted.

As such, when a system model of the first filter module 133 is defined, an observation model for information obtained from the GPS module 120 and information obtained from the OBD 200 needs to be defined.

First, the observation model for the information obtained from the GPS module 120, the GPS speed information and the heading information (heading) information can be represented by equation (6) and equation (7), respectively.

Accordingly, the observation model may be the same as Equation 8.

In addition, the measurement noise matrix may be expressed by Equation 9.

On the other hand, the observation model for the OBD speed information obtained from the OBD 200 can be expressed as shown in equation (10).

As such, when the system model and the observation model of the Kalman filter for the first filter module 133, that is, the speed and the attitude, are defined, the first filter module 133 may calculate the speed information and the attitude information with reduced noise. . The calculated speed information and / or attitude information may be output as feedback information to the motion module 132. In addition, the speed information and / or the attitude information may be output to the second filter module 134 and used to calculate position information of the moving object. An input / output value of the second filter module 134 is shown in FIG. 4.

4 is a view illustrating a filter input / output value when a second filter is implemented as a Kalman filter in a navigation system using multiple sensors according to an exemplary embodiment of the present invention.

1 and 4, the second filter module 134 may be implemented as a Kalman filter for a position. The second filter module 134 may receive posture information and speed information from the first filter module 133. In addition, the INS location information may be received from the motion module 132. In addition, GPS location information may be received from the GPS module 120. According to the embodiment, as disclosed in the previous application, the navigation system 100 using the multiple sensors may be provided with an altitude sensor 140 separately, and the altitude information measured from the altitude sensor 140 may be It may be used as an input value of the second filter module 134.

Accordingly, the second filter module 134 may use latitude, longitude, altitude, and speed in each direction of the navigation coordinate system as state variables. Then, the system error model of the second filter module 134 can be obtained by perturbing the INS velocity obtained from the acceleration information of the body, and can be expressed as shown in Equation 11 by expanding the model of reference [4]. have.

The spectral density matrix of the input white noise u may be expressed as in Equation 12.

When the system model of the second filter module 134 is defined as described above, an observation model for information obtained from the GPS module 120 needs to be defined. In addition, when a separate altitude sensor 140 is provided, it is necessary to define an observation model for altitude information obtained from the altitude sensor 140.

First, the observation model for the information obtained from the GPS module 120, the observation model by the GPS information can be expressed as shown in equation (13).

은 위도,

는 경도를 나타낸다. 또한, 상기 다중 센서를 이용한 항법시스템(100)은 상기 고도센서(140)를 추가로 구비할 수 있으며, 상기 고도센서(140)는 기압계(Barometer)로 구현될 수 있음은 전술한 바와 같다. 상기 고도센서(140)에서 얻은 고도(

)와 고도의 변화율(

)을 이용한 관측모델은 수학식 14와 같이 표현될 수 있다.Where P and V are position and velocity, respectively, N is a navigation frame, and n, e, and d are north, east, and down, respectively. therefore,

Latitude,

Indicates hardness. In addition, the navigation system 100 using the multiple sensors may further include the altitude sensor 140, the altitude sensor 140 may be implemented as a barometer as described above. Altitude obtained from the altitude sensor 140 (

) And the rate of change of altitude (

) Can be expressed as shown in Equation 14.

The measurement error matrix at this time may be as shown in Equation 15.

에 매우 큰 값을 대입해줄 수 있다.If the altitude change rate measured by the altitude sensor 140 is more than a certain size

You can assign a very large value to.

As such, when the system model and the observation model of the Kalman filter for the location are defined, the second filter module 134 may calculate location information with reduced noise.

As described above, when the first filter module 133 and the second filter module 134 are defined, the navigation system 100 using the multiple sensors may be implemented in a predetermined manner according to the purpose. For example, the navigation system 100 using the multiple sensors may be embodied as an embedded system, and the navigation calculation module 130 may generate the first navigation information at a calculation period (eg, about 100 Hz) of the motion module 132. The output value of the first filter module 133 and / or the output value of the second filter module 134 may be calculated.

5 is a diagram illustrating a performance comparison between a navigation system using multiple sensors and a navigation system using only a GPS device according to an embodiment of the present invention.

The dotted line illustrated in FIG. 5 represents GPS positioning alone, and the solid line represents a result of fusion of multiple sensor informations of the navigation system 100 using multiple sensors according to an exemplary embodiment of the present invention.

As can be seen from Figure 5, the GPS signal is well received when there is no difference, but next to a high-rise building where the error in the GPS signal due to the multi-path can be confirmed the effect of reducing the error relatively, Ilsan Baekseok Station 1 When the block is repeated 10 times (40 km), the error is improved by 17%. As can be seen from the dotted line of FIG. 5, the vehicle is driving in a normal straight line, whereas the calculation result of the position information using the GPS signal indicates a situation in which the vehicle position is indicated inside the driving road due to the multi-pass fading effect of a high-rise building. You can find it. On the other hand, the navigation system 100 using the multi-sensor according to the embodiment of the present invention can confirm the appearance of restoring the original driving pattern of the vehicle.

6 is a diagram illustrating another performance comparison example of a navigation system using multiple sensors and a navigation system using only a GPS device according to an embodiment of the present invention.

6 shows an experimental result when driving inside a parking lot of a building where GPS signals cannot be received for a long time. The solid line of FIG. 6 shows a navigation system using multiple sensors according to an embodiment of the present invention. (100) shows the location information when driving inside the building parking lot for 5 minutes. As can be seen in FIG. 6A, even when a GPS signal is not received (red dotted line), the navigation system 100 using the multi-sensor according to an embodiment of the present invention calculates the location information of the vehicle even when the location information cannot be calculated anymore. It can be seen that. In addition, when the altitude sensor 140 is used, altitude information may be obtained even when a GPS signal is not received. As shown in FIG. 6B, the position information (trace) of the vehicle may be confirmed in a three-dimensional form. Can be.

Navigation system 100 using multiple sensors according to an embodiment of the present invention may increase the cost slightly in terms of complexity and price compared to the existing system, but the performance is greatly improved and positioning can be possible even if the GPS signal is not received. Can be. In addition, when using the altitude sensor 140, even if the GPS signal is not received there is an effect that can obtain the three-dimensional position information. In addition, there is an effect that the driving state of the moving object can be understood as the calculation period of the INS system (for example, about 100 Hz) instead of the GPS calculation period.

The navigation system providing method using multiple sensors according to an embodiment of the present invention may be implemented as computer readable codes on a computer readable recording medium. A computer-readable recording medium includes all kinds of recording apparatuses in which data that can be read by a computer system is stored. Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, hard disk, floppy disk, optical data storage, and the like, and also in the form of carrier waves (e.g., transmission over the Internet). It also includes implementations. The computer readable recording medium may also be distributed over a networked computer system so that computer readable code can be stored and executed in a distributed manner. And functional programs, codes, and code segments for implementing the present invention can be easily inferred by programmers skilled in the art to which the present invention pertains.

As mentioned above, although this invention was demonstrated in detail using the preferable embodiment, the scope of the present invention is not limited to a specific embodiment, Comprising: It should be interpreted by the attached Claim. In addition, those skilled in the art should understand that many modifications and variations are possible without departing from the scope of the present invention.

Claims (18)

IMU (Inertial Measurement Unit) for measuring and outputting inertial data according to the movement of the moving body;
A GPS module for receiving a Global Positioning System (GPS) signal corresponding to the moving object;
An altitude sensor for measuring altitude information corresponding to the moving object;
A bias estimation module for estimating a bias of a gyro sensor included in the IMU based on the inertial data measured from the IMU;
A first filter module for calculating attitude information and speed information of the moving body;
A motion module for calculating INS attitude information and INS speed information of the moving body based on the bias value estimated by the bias estimation module, the inertia data, and feedback information of the first filter module; And
Noise based on the measured altitude information, the attitude information, the speed information, the GPS location information included in the GPS information output from the GPS module, and the INS location information calculated by the motion module based on the inertial data. Comprising a second filter module for calculating the position information of the reduced body,
The first filter module includes the INS attitude information, INS speed information, OBD speed information output from an OBD installed in the moving object, GPS speed information included in the GPS information, and GPS direction information calculated by the motion module. Navigation system using a multi-sensor to calculate the attitude information and the speed information is reduced noise based on the.
delete delete delete delete The navigation system of claim 1, wherein at least one of the first filter module and the second filter module is implemented as a Kalman filter.
The method of claim 6, wherein the first filter module,
A navigation system using multiple sensors using the following equation as a system model of Kalman filter.

The method of claim 7, wherein the first filter module,
A navigation system using multiple sensors using the following two equations as observation models for Kalman filters.

The method of claim 6, wherein the second filter module,
A navigation system using multiple sensors using the following equation as a system model of Kalman filter.

The method of claim 9, wherein the second filter module,
A navigation system using multiple sensors using the following equations as an observation model for Kalman filters.

The method of claim 10, wherein the second filter module,
A navigation system using multiple sensors that uses the following equations as Kalman filter observation models.

delete delete A navigation system using multiple sensors, using the IMU included in the navigation system using multiple sensors, measuring inertial data according to the movement of a moving object and receiving a GPS signal corresponding to the moving object;
Receiving OBD speed information from an OBD installed in the moving object by the navigation system using the multiple sensors; And
Calculating attitude information and speed information of the moving object using the inertial data, the OBD speed information, and GPS information included in the GPS signal; And
Based on altitude information measured from an altitude sensor included in the navigation system using the multiple sensors, the attitude information, the speed information, GPS location information included in the GPS information, and INS location information calculated based on the inertial data Computing the position information of the moving object is reduced noise,
Computing the attitude information and speed information of the moving body,
Estimating a bias value of a gyro sensor included in the IMU based on the inertial data;
Calculating INS attitude information and INS speed information of the moving body based on the bias value, the inertia data, and feedback information including previous attitude information and previous speed information; And
Calculating the attitude information and the speed information with reduced noise based on the INS attitude information, the INS speed information, the OBD speed information, the GPS speed information included in the GPS information, and the GPS travel direction information. A navigation system providing method using multiple sensors.
delete delete delete A computer-readable recording medium having recorded thereon a program for performing the method of claim 14.

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