KR102537326B1 - Apparatus and method for predicting rts correction considering gnss broadcast ephemeris at iod change - Google Patents

Abstract

An apparatus and method for predicting RTS correction information considering IOD change of a GNSS navigation message are disclosed. An RTS correction information prediction method considering IOD change of a GNSS navigation message according to an embodiment of the present invention includes: (a) associated with a GNSS navigation message Collecting the navigation message and RTS correction information in consideration of the update time of IOD (Issue of Data), (b) processing input data for building a signal prediction model based on the navigation message and the RTS correction information (c) generating the signal prediction model based on the processed input data; and (d) predicting the disconnected RTS correction information based on the signal prediction model when the RTS correction information is disconnected. steps may be included.

Description

Apparatus and method for predicting RTS correction information considering IOD change of GNSS navigation message

The present invention relates to an apparatus and method for predicting RTS correction information considering IOD change of a GNSS navigation message. For example, the present invention relates to a method and apparatus for predicting IGS RTS correction information combined with GNSS navigation message information at an IOD change time point.

Ships, aviation, and geodetic fields require precise location of a user, and currently, a method using a global navigation satellite system (GNSS) is mainly used. The position of the GNSS receiver is estimated using the position of the navigation satellite transmitting the GNSS satellite signal and the distance information to the GNSS receiver.

Specifically, location information of GNSS navigation satellites is transmitted through a navigation message included in a GNSS signal. Because the error of the atomic clock mounted on the navigation satellite affects the distance information to the GNSS receiver, the navigation message also includes information about the error of the atomic clock. The navigation message is generated by the ground control center that operates the GNSS and transmitted to the navigation satellite. Since communication between the ground transmission station and the navigation satellite is limited, the same navigation message is broadcast for a certain period of time. US GPS (Global Positioning System) navigation satellites update navigation messages every 2 hours, and Europe's Galileo and China's BeiDou operate similarly.

In addition, the location information of the GPS navigation message is transmitted in the form of a Kepler orbital element, and if this is used, the motion of the satellite can be expressed for a long time with a small amount of data. Clock information is transmitted in the form of polynomial coefficients.

On the other hand, when the navigation message is updated, Kepler orbit elements and polynomial coefficients expressing orbit and clock information are changed, which causes a discontinuity in orbit and clock information at the update time. In the case of GPS, each navigation message is distinguished by assigning a different IOD (Issue of Data) to each updated navigation message.

In other words, since the location and clock information transmitted in the navigation message is updated at regular intervals, the accuracy is not high, and the orbit error of the GPS navigation message is known to be on the order of 1-2 m. With such low accuracy, only meter-level receiver positioning is possible, and high-accuracy navigation satellite position and clock information is required to obtain high positioning accuracy.

In this regard, among navigation satellite location and clock information generated by the International GNSS Service (IGS), information generated by the IGS in real time and provided over the Internet is referred to as RTS (Real-Time Service) correction information. The update cycle of the RTS correction information is 60 seconds for the orbit and 10 seconds for the clock, which is very fast compared to the navigation message.

Specifically, the RTS correction information provides a correction value for location information transmitted in a navigation message instead of an absolute value of a location of a navigation satellite. That is, if RTS correction information is added to the location transmitted in the navigation message, the navigation satellite location with cm-level accuracy can be obtained, and the accuracy of the navigation satellite clock correction information is similar to this.

As described above, since the renewal cycles of the navigation message and the RTS correction information are different, the IOD information of the applied navigation message is provided together with the RTS correction information. Therefore, even if the updated navigation message is received, if the received RTS correction information has the IOD information before the update, the RTS correction information must be applied to the navigation message received before the update to calculate accurate navigation satellite position and clock information. For this reason, the RTS correction information has a rapid discontinuity every 2 hours, which is the navigation message update period.

Since RTS can be received in real time, it is widely used in fields where real-time precise location is required, but the signal may be disconnected due to transmission problems in the Internet environment or IGS institutions, or problems in receiving hardware. If the RTS signal is disconnected, the positioning accuracy of the receiver is rapidly reduced because it has to determine the position only with the navigation message.

In preparation for RTS signal disconnection, many studies have been conducted to predict RTS correction information during the signal disconnection period. Various methods such as polynomials, harmonic functions, and machine learning have been tried as prediction techniques, but these conventional prediction methods commonly analyze RTS correction information before signal disconnection to create an RTS prediction model.

In this regard, the model used for RTS correction information analysis commonly assumes a continuous time-series signal. That is, since a prediction model is generated and predicted in a section where the navigation message is not updated, in the case of the conventional prediction method, a new prediction model must be created from the time the navigation message is updated. There was a problem that RTS correction information received during

Therefore, in the conventional prediction methods, if the time point at which the RTS signal is disconnected is immediately before the navigation message update time, there is a limit in that it is impossible to predict RTS correction information since the prediction model cannot be used after the update.

The background technology of the present application is disclosed in Korean Patent Registration No. 10-1419339.

The present invention is to solve the above-mentioned problems of the prior art, and GNSS navigation overcomes the limitations of the conventional prediction technique in which RTS correction information cannot be predicted when the IGS RTS correction information signal is disconnected due to proximity to the IOD change time of the navigation message. An object of the present invention is to provide an apparatus and method for predicting RTS correction information considering IOD change of a message.

However, the technical problem to be achieved by the embodiments of the present application is not limited to the technical problems described above, and other technical problems may exist.

As a technical means for achieving the above technical problem, the RTS correction information prediction method considering the IOD change of the GNSS navigation message according to an embodiment of the present invention includes (a) IOD (Issue of Data) associated with the GNSS navigation message Collecting the navigation message and RTS correction information in consideration of update time, (b) processing input data for building a signal prediction model based on the navigation message and the RTS correction information, (c) processing the input data generating the signal prediction model based on the received input data; and (d) predicting the disconnected RTS correction information based on the signal prediction model when the RTS correction information is disconnected.

In addition, the step (a) includes (a1) dividing and storing a first navigation message, which is a navigation message received before the update point in time, and a second navigation message, which is a navigation message received after the update point in time, and (a2) ) dividing and storing first RTS information, which is RTS correction information received before the update point in time, and second RTS information, which is RTS correction information received after the update point in time.

Further, in the step (b), the input data corresponds to the first RTS information in a section before the update point, and the second RTS information, the first navigation message, and the second RTS information in a section after the update point in time. It can be processed into time-series data corresponding to the corrected RTS information derived based on the trajectory difference of the navigation message.

Also, the corrected RTS information may be derived to be continuous with the first RTS information based on the update time point.

In the step (b), the corrected RTS information may be derived based on Equation 1 below.

In the step (b), the trajectory difference may be derived based on Equation 2 below.

Also, the signal prediction model may be a time series prediction model.

In the step (c), coefficients of the time series prediction model may be calculated through a fitting algorithm based on the processed input data.

In the step (d), the predicted RTS correction information corresponding to the disconnected RTS correction information may be derived by reflecting the trajectory difference in the output data of the signal prediction model.

On the other hand, the apparatus for predicting RTS correction information in consideration of the IOD change of the GNSS navigation message according to an embodiment of the present invention considers the renewal time of the IOD (Issue of Data) associated with the GNSS navigation message to calculate the navigation message and the RTS correction information A receiving unit that collects, a shaping unit that processes input data for constructing a signal prediction model based on the navigation message and the RTS correction information, a fitting unit that generates the signal prediction model based on the processed input data, and the RTS When the correction information is disconnected, an estimator for predicting the disconnected RTS correction information based on the signal prediction model may be included.

In addition, the receiver separates and stores the first navigation message, which is a navigation message received before the update point in time, and the second navigation message, which is a navigation message received after the update point in time, and corrects the RTS received before the update point in time. First RTS information, which is information, and second RTS information, which is RTS correction information received after the update time point, may be separately stored.

In addition, the shape unit determines that a section before the update time corresponds to the first RTS information, and a section after the update time is based on the second RTS information and a trajectory difference between the first navigation message and the second navigation message. The input data may be processed into time-series data corresponding to the derived corrected RTS information.

Also, the shape unit may derive the corrected RTS information based on Equation 1 below.

In addition, the shape unit may derive the trajectory difference based on Equation 2 below.

In addition, the fitting unit may calculate coefficients of the time series prediction model through a fitting algorithm based on the processed input data.

In addition, the estimator may derive predicted RTS correction information corresponding to the disconnected RTS correction information by reflecting the trajectory difference in output data of the signal prediction model.

The above-described problem solving means are merely exemplary and should not be construed as intended to limit the present disclosure. In addition to the exemplary embodiments described above, additional embodiments may exist in the drawings and detailed description of the invention.

According to the above-described means for solving the problem of the present application, when the IGS RTS correction information signal is disconnected close to the time point of the IOD change of the navigation message, the IOD change of the GNSS navigation message overcomes the limitations of the conventional prediction technique in which the RTS correction information cannot be predicted. It is possible to provide an apparatus and method for predicting RTS correction information considering .

According to the above-described problem solving means of the present application, by applying the difference value of each satellite orbit calculated by the updated GNSS navigation message and the GNSS navigation message before the update to the RTS orbit correction information, a continuous RTS signal is obtained even after the IOD change and time series prediction based on continuous RTS signals.

According to the above-described problem solving means of the present application, even if the disconnection of the RTS correction signal occurs close to the IOD update time point, since the RTS signal can be predicted, the location estimation accuracy can be continuously maintained.

However, the effects obtainable herein are not limited to the effects described above, and other effects may exist.

1 is a schematic configuration diagram of an apparatus for predicting RTS correction information considering an IOD change of a GNSS navigation message according to an embodiment of the present invention.
2 is a diagram exemplarily illustrating a discontinuous change of RTS correction information by updating IOD (Issue of Data) of a GNSS navigation message.
FIG. 3 is a diagram for explaining a receiving unit of an RTS correction information prediction apparatus considering an IOD change of a GNSS navigation message according to an embodiment of the present invention.
FIG. 4 is a diagram for explaining the shape of the RTS correction information predicting device considering the IOD change of the GNSS navigation message according to an embodiment of the present invention.
5 is a diagram illustratively illustrating input data processed by a shape unit of an RTS correction information predicting device in consideration of an IOD change of a GNSS navigation message according to an embodiment of the present invention.
6 is a diagram for explaining an appropriate part of an apparatus for predicting RTS correction information considering an IOD change of a GNSS navigation message according to an embodiment of the present invention.
7 is a diagram for explaining an estimator of an apparatus for predicting RTS correction information considering an IOD change of a GNSS navigation message according to an embodiment of the present invention.
8A and 8B are graphs showing a comparison of errors in prediction results of RTS correction information according to types of signal prediction models.
9 is an operational flowchart of a method for predicting RTS correction information considering IOD change of a GNSS navigation message according to an embodiment of the present invention.

Hereinafter, embodiments of the present application will be described in detail so that those skilled in the art can easily practice with reference to the accompanying drawings. However, the present disclosure may be implemented in many different forms and is not limited to the embodiments described herein. And in order to clearly describe the present application in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification.

Throughout the present specification, when a part is said to be “connected” to another part, it is not only “directly connected”, but also “electrically connected” or “indirectly connected” with another element in between. "Including cases where

Throughout the present specification, when a member is referred to as being “on,” “above,” “on top of,” “below,” “below,” or “below” another member, this means that a member is located in relation to another member. This includes not only the case of contact but also the case of another member between the two members.

Throughout the present specification, when a certain component is said to "include", it means that it may further include other components without excluding other components unless otherwise stated.

The present invention relates to an apparatus and method for predicting RTS correction information considering IOD change of a GNSS navigation message. For example, the present invention relates to a method and apparatus for predicting IGS RTS correction information combined with GNSS navigation message information at an IOD change time point.

In more detail, the present application obtains a continuous RTS signal by applying the difference between each satellite orbit calculated with the GNSS navigation message updated at the time of IOD change and the GNSS navigation message before the update to the RTS correction information, and then obtains the RTS signal prediction model. It relates to a method and apparatus for generating and predicting when an RTS signal is disconnected.

1 is a schematic configuration diagram of an apparatus for predicting RTS correction information considering an IOD change of a GNSS navigation message according to an embodiment of the present invention.

Referring to FIG. 1, an RTS correction information prediction device 100 (hereinafter, referred to as 'prediction device 100') considering the IOD change of a GNSS navigation message according to an embodiment of the present invention includes a receiver 110, a shape It may include a unit 120 , a fitting unit 130 and an estimating unit 140 .

In the description of the embodiment of the present application, the prediction device 100 may communicate with a navigation satellite (not shown), a control center server (not shown), and the like associated with a GNSS navigation system (global navigation satellite system) through a network. A network refers to a connection structure capable of exchanging information between nodes such as terminals and servers, and examples of such networks include a 3rd Generation Partnership Project (3GPP) network, a Long Term Evolution (LTE) network, and 5G Network, WIMAX (World Interoperability for Microwave Access) network, Internet (Internet), LAN (Local Area Network), Wireless LAN (Wireless Local Area Network), WAN (Wide Area Network), PAN (Personal Area Network), wifi network, A Bluetooth network, a satellite broadcasting network, an analog broadcasting network, a Digital Multimedia Broadcasting (DMB) network, etc. are included, but are not limited thereto.

On the other hand, the prediction device 100 disclosed herein may be mounted on a user terminal (not shown) to more accurately obtain location information of a predetermined user terminal (not shown) through a GNSS navigation system. but not limited to

User terminals (not shown) include, for example, a smart phone, a smart pad, a tablet PC, and the like and PCS (Personal Communication System), GSM (Global System for Mobile communication), PDC (Personal Digital Cellular), PHS (Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), Wibro (Wireless Broadband Internet) It may be any kind of wireless communication device such as a terminal.

Hereinafter, a precise position estimation process using GNSS and RTS correction information used therein will be described first.

IGS RTS correction information is provided in the form of RTCM SSR (state space representation), and the user can receive such RTS correction information in a networked transport of RTCM via internet protocol (NTRIP) method.

This RTS correction information is divided into GNSS satellite orbit correction information and clock correction information, and the user can selectively use data calculated by a desired institution. Illustratively, among various products provided by various organizations, IGS03 may include correction information of GLONASS satellites, orbit correction information and clock correction information are usually provided in units of m, orbit correction information is 60 seconds, and clock correction information is provided. Information may be newly transmitted (updated) at intervals of 10 seconds. For example, the accuracy of the orbit correction information is about 0.05 m (RMS) level.

Meanwhile, the RTS trajectory correction information is provided in R (radial), A (along-track), and C (cross-track) directions, unlike the coordinates of the trajectory calculated in the navigation message. Therefore, conversion to ECEF (earth-centered earth-fixed) coordinate system must be preceded in order to be applied to the navigation message.

In addition, the origin of the coordinate system to which correction information is applied may be set to APC (antenna phase center) or satellite center of mass (CoM) according to each type of data. can be based on

Meanwhile, issue of data (IOD) information may be included in the navigation message and RTS correction information transmitted by the GNSS. IOD means the issue number for the transmitted message, and the IOD information can be divided into IOD ephemeris (IODE), which is an IOD value for orbit, and IOD clock (IOD clock), which is an IOD value for clock, for example, every 2 hours. The value may change as the navigation message is updated. In other words, the renewal period of the navigation message (eg, 2 hours) is relative to the aforementioned update period of the RTS correction information (eg, 60 seconds for trajectory correction information, 10 seconds for clock correction information, etc.) It can be set to a very long value, and the satellite trajectory calculated by the navigation message and the RTS correction information change discontinuously at the time when the IOD changes.

In this regard, since it is very difficult to predict correction information when an RTS signal is disconnected at a time when the IOD changes, conventional studies have mainly adopted a method of simply testing prediction at a time when the IOD does not change.

In addition, the above-described IOD information may be included in the RTS trajectory correction information. The IOD value included in the correction information specifies the navigation message to which the correction information is applied. When the IOD of the correction information matches the IODE of the navigation message, the correction information should be applied. That is, if the IOD of the navigation message is updated but the IODE of the correction information is not updated, the correction information should be applied to the previous navigation message. Since the IODC, the IOD of the navigation message clock, overlaps with the IODE, the IOD is transmitted only for the RTS trajectory correction information, and the RTS trajectory and clock use the same IOD.

2 is a diagram exemplarily illustrating a discontinuous change of RTS correction information by updating IOD (Issue of Data) of a GNSS navigation message.

Referring to FIG. 2, the orbit correction information continuously changes, and the correction value greatly changes as the IOD is updated at every update period. That is, a discontinuous change may occur at every renewal period (for example, a 2-hour period, etc.) of the navigation message. At this time, the change amount of the correction value is not constant, and the change amount is different according to the IOD change time and trajectory direction.

In the case of the clock correction information, a change may occur at the time of the IOD change, but there may be relatively no change or a very small amount of change compared to the trajectory correction information. As such, when the orbit and clock correction information are disconnected at the time when the IOD changes, it becomes difficult to predict the correction information.

FIG. 3 is a diagram for explaining a receiving unit of an RTS correction information prediction apparatus considering an IOD change of a GNSS navigation message according to an embodiment of the present invention.

Referring to FIG. 3 , the receiving unit 110 may receive (collect) a navigation message 1 and RTS correction information 2 in consideration of an issue of data (IOD) update point associated with a GNSS navigation message. Exemplarily, the receiving unit 110 may receive the GNSS navigation message 1 through the GNSS receiver and RTS correction information 2 provided by the IGS through the Internet. Since the information acquisition method of the receiving unit 110 is obvious to those skilled in the art, a detailed description thereof will be omitted.

In addition, according to an embodiment of the present application, the receiving unit 110 receives the first navigation message 3, which is a navigation message received before the IOD (Issue of Data) update point, and the IOD (Issue of Data) update point after the update point. The second navigation message 4, which is the received navigation message, can be classified and stored.

In addition, according to an embodiment of the present application, the receiving unit 110 may receive first RTS information 5, which is RTS correction information received before an issue of data (IOD) update time and after an issue of data (IOD) update time. The second RTS information (6), which is the RTS correction information received at , can be separately stored.

In other words, the prediction device 100 may store both the first navigation message 3 before the update of IOD (Issue of Data) and the second navigation message 4 after the update of IOD (Issue of Data), Similarly, in the case of RTS correction information (2), first RTS information (5) before IOD (Issue of Data) update and second RTS information (6) after IOD (Issue of Data) update can both be stored. .

FIG. 4 is a diagram for explaining the shape of the RTS correction information predicting device considering the IOD change of the GNSS navigation message according to an embodiment of the present invention.

Referring to FIG. 4 , the shaping unit 120 may process input data 12 for constructing a signal prediction model based on the navigation message 1 and RTS correction information 2 . That is, the shaping unit 120 may be a component that generates input data 12 of a model for shaping a signal prediction model for RTS correction information.

In this regard, as described above, both the RTS correction information and the navigation message change discontinuously at the time the IOD changes, and since time series prediction is impossible with discontinuous data, prediction is made only with the short-term data received immediately after the IOD change. However, if the number of received data is small, the predictive performance is significantly degraded.

In consideration of this, the prediction apparatus 100 disclosed herein combines RTS correction information and navigation messages in response to the IOD change (update) time, and processes and uses the calculated satellite trajectory to continuously change, even at the time of IOD change. Continuous signals can be obtained, and based on this, a signal prediction model capable of time-series signal prediction can be constructed.

Specifically, in the shape unit 120, the interval before the update of IOD (Issue of Data) corresponds to the first RTS information 5, and the interval after the update of IOD (Issue of Data) corresponds to the input data 12. Receiver 110 to include time-series data corresponding to corrected RTS information 11 derived based on the difference between the second RTS information 6 and the trajectories of the first navigation message 3 and the second navigation message 4 The collected navigation message (1) and RTS correction information (2) can be processed.

5 is a diagram illustratively illustrating input data processed by a shape unit of an RTS correction information predicting device in consideration of an IOD change of a GNSS navigation message according to an embodiment of the present invention.

Referring to FIG. 5 , the shaping unit 120 may derive corrected RTS information 11 to continue with the first RTS information based on an issue of data (IOD) renewal time point.

시점은 항법메시지(1)가 갱신되기 이전 시점,

시점은 항법메시지(1)가 갱신된 시점,

은 항법메시지(1)가 갱신된 이후 시점을 각각 나타낸다. NAV의 하첨자 1과 2는 각각 IOD 변화 이전과 이후에 각각 수신된 항법메시지(달리 말해, 제1항법메시지(3) 및 제2항법메시지(4) 등)를 의미할 수 있다.Specifically, in FIG. 5, the dotted line represents the change in the satellite orbit calculated from the navigation message (1), and the solid line represents the change in orbit when the RTS correction information (2) is applied to the navigation message (1). also,

The point in time is the time before the navigation message (1) is updated,

The point in time is when the navigation message (1) is updated,

Denotes a point in time after the navigation message 1 is updated. Subscripts 1 and 2 of the NAV may mean navigation messages received before and after the IOD change (in other words, the first navigation message 3 and the second navigation message 4, etc.), respectively.

시점에서 갱신된 항법메시지로 계산한 궤도(

)와 갱신 이전 항법메시지로 계산한 궤도(

)에 불연속적인 변화가 발생하는 것을 확인할 수 있으며, 이 때 갱신된 항법메시지(

)와 갱신된 RTS 보정정보가 결합되면, 갱신 이전 항법메시지(

)에 갱신 이전 RTS 보정정보를 결합한 신호와 연속적으로 변화할 수 있게 된다. 이는 갱신된 RTS 보정정보에 갱신 이전 RTS 보정정보에 갱신 전/후 항법메시지의 차이를 반영하는 방식으로 갱신 이전 RTS 보정정보와 연속적인 신호를 얻을 수 있음을 의미한다.Referring to Figure 5,

The trajectory calculated from the navigation message updated at the point in time (

) and the trajectory calculated by the navigation message before update (

), it can be confirmed that a discontinuous change occurs, and at this time, the updated navigation message (

) and the updated RTS correction information are combined, the navigation message before the update (

) can be continuously changed with the signal combining the RTS correction information before updating. This means that the RTS correction information before the update and the continuous signal can be obtained by reflecting the difference between the navigation message before and after the update in the updated RTS correction information.

In this regard, the signal prediction model disclosed herein may be a model based on various techniques that enable prediction of time series data (sequence data), and when the RTS correction signal is disconnected at the time of IOD change, the input of the signal prediction model The data 12 may consist of two different parts (forms). First, the first RTS information 5 before the update of the IOD is included in the input data 12 of the model as the received value, and the second RTS information 6 after the update of the IOD is the first RTS information before the update ( It can be converted into the corrected RTS information 11, which is a form capable of maintaining continuity with the value of 5), and reflected in the input data 12 of the model.

In other words, the corrected RTS information 11 can be derived to correct a discontinuous change in the RTS correction information occurring immediately after the IOD change.

Specifically, the shape unit 120 may derive corrected RTS information 11 based on Equation 1 below.

[Equation 1]

In Equation 1, t ₁ is an arbitrary time after the update of IOD (Issue of Data), r (t ₁ ) is corrected RTS information 11, and RTS (t ₁ ) is second RTS information (6), and δNAV(t ₁ ) may be the difference between the trajectories of the first navigation message (3) and the second navigation message (4).

In addition, the shape unit 120 may derive a trajectory difference between the first navigation message 3 and the second navigation message 4 based on Equation 2 below.

[Equation 2]

In Equation 2, NAV ₂ (t ₁ ) is the orbit of the satellite calculated based on the second navigation message (4), and NAV ₁ (t ₁ ) is the satellite calculated based on the first navigation message (3). may be the orbit of

6 is a diagram for explaining an appropriate part of an apparatus for predicting RTS correction information considering an IOD change of a GNSS navigation message according to an embodiment of the present invention.

Referring to FIG. 6 , the fitting unit 130 may generate a signal prediction model based on the input data 12 processed by the shaping unit 120 . Specifically, the fitting unit 130 may generate a time series prediction model as a signal prediction model.

In addition, the fitting unit 130 may calculate the model coefficient 22 of the time series prediction model through the fitting (learning) algorithm 21 based on the input data processed by the shape unit 120 . In other words, the fitting unit 130 may be a component that calculates the model coefficient 22 from the input data 12 of the signal prediction model (time series prediction model).

According to an embodiment of the present application, the signal prediction model may be a polynomial model constructed to predict the RTS correction information at the time of IOD change, and the fitting unit 130 exemplarily corrects the RTS information 11 to the time series prediction model. ) to calculate the model coefficient 22 through the fitting algorithm 21.

Meanwhile, the calculation method of the model coefficient 22 may be determined differently depending on the type of time series prediction model, and when a polynomial model is used as a time series prediction model, the model coefficient 22 may be calculated through the least squares method. but not limited to

On the other hand, the polynomial model of the prediction device 100 may be constructed to be used when estimating the value of orbit and clock correction information with time as an input, and optimization of the order and fitting period of the polynomial is required. Depending on an example, the degree and fitting period of the polynomial model may be determined with various values, and the change in prediction performance according to the change in the parameter associated with the polynomial model will be described later with reference to FIGS. 8A and 8B.

7 is a diagram for explaining an estimator of an apparatus for predicting RTS correction information considering an IOD change of a GNSS navigation message according to an embodiment of the present invention.

Referring to FIG. 7 , when disconnection of the received RTS correction information 2 occurs, the estimator 140 may predict the disconnected RTS correction information based on the generated signal prediction model.

Specifically, the estimator 140 reflects the difference between the trajectories derived from the first navigation message 3 and the second navigation message 4 in the model output data 31 of the signal prediction model to correspond to the disconnected RTS correction information. Predictive RTS correction information 32 can be derived.

In other words, the estimator 140 derives the model output data 31, which is the predicted value of the model, from the model input data 12 and the model coefficient 22 calculated in the fitting unit 130, and the model output data 31 ) into a form conforming to the RTS correction information and outputting the predicted RTS correction information 32.

In this case, the predicted RTS correction information 32 may include a predicted value for RTS trajectory correction information and a predicted value for RTS clock correction information.

On the other hand, the model output data 31, which is the predicted value of the model, is a form in which the trajectory difference between the navigation messages before and after the IOD update is applied to the RTS correction information, as can be understood through the above-mentioned Equation 1, so before and after the IOD update. By additionally performing a process of adding the trajectory difference between navigation messages again, the predicted RTS correction information 32 can be finally obtained.

Hereinafter, when a polynomial model is used as a signal prediction model, an optimization process for the degree and fitting period of the polynomial associated with the polynomial model will be described.

The polynomial model can be used when estimating the value of orbit and clock correction information with time as an input. Optimization of the order of the polynomial and the fitting period is required. The 3rd order is applied, and the 0th or 1st order is used for the clock correction information. Since the clock correction information includes stochastic changes accumulated over time and also has some white noise characteristics, the latest value is mainly used rather than the polynomial (0th order polynomial). In addition, in relation to the polynomial model, it is also necessary to optimize not only the polynomial order but also the length (fitting period) of data to be fitted for each order.

In an experimental example linked to the RTS correction information prediction method considering the IOD change of the GNSS navigation message according to an embodiment of the present application, data used for polynomial model optimization was collected during the period from August 12 to 16, 2020 , First, to determine the optimal fitting period, the fitting period was set at 5-minute intervals to a maximum of 20 minutes, and it was assumed that the signal loss of the correction information occurred 3 minutes immediately after the change (update) of the IOD, and immediately after the signal loss occurred. predictions were made from In addition, when the navigation message is updated every 2 hours, the IOD changes 12 times a day, and fitting and prediction are performed with a prediction period of 15 minutes at all IOD change points.

At this time, since the reception intervals (cycles) of the orbit correction information and the clock correction information were 60 seconds and 10 seconds, respectively, 15 orbit data and 90 clock data were predicted.

Looking at the average value of the prediction error of the trajectory correction information according to the fitting length and polynomial order derived from the above test method, first, when the fitting length is 1 order, the prediction error in the R direction decreases as the fitting length increases, whereas in the A direction, the fitting length is 10 It was found that the prediction error rather increased when the number of minutes was exceeded. In addition, the prediction error was found to be the lowest when the fitting length was 20 minutes in the case of order 2, and when the fitting length was 15 minutes in the case of order 3.

In addition, when all orders were comprehensively considered, the optimal fitting length was 15 minutes, and the first-order polynomial model showed the smallest error at the corresponding fitting length. The prediction error of the first-order polynomial model for the optimal variable was 0.010m for the R-direction trajectory, 0.052m for the A-direction, and 0.026m for the C-direction. m level.

In summary, at least one of the order of the polynomial and the fitting length (period) of the signal prediction model based on the polynomial model according to an embodiment of the present application is the update period of the navigation message (1) and the reception (update) of the RTS correction information (2). ) may be optimized based on the period.

Hereinafter, an experimental example of a result of analyzing performance of precision point positioning (PPP) based on the predicted RTS correction information 32 provided by the prediction apparatus 100 will be described.

In this experimental example, after applying the predicted RTS correction information (32) predicted by the first-order polynomial model to the GNSS navigation message (1), PPP was performed using gLAB (GNSS-lab tool).

Here, gLAB may mean a commercial program commonly used for GNSS trajectory accuracy analysis and location estimation.

In addition, dual frequencies were used to eliminate ionospheric errors, and the weight of the carrier observation value was set to 100 times the code, and observation data provided at 30-second intervals were used.

To analyze the PPP performance of the predicted value, the PPP performance of the RTS original signal received during the same period was compared. A polynomial model with a total of three different model variables (order, fit, length of prediction interval, etc.) was used for estimation.

First, Case 1 is a first-order polynomial model with a fitting length of 15 minutes, and Case 2 is a second-order polynomial model with a fitting length of 15 minutes. The predicted RTS correction information was obtained by adding the trajectory difference between the navigation messages derived through Equation 2 above to the corrected RTS, and Case 3 uses only the RTS data received immediately after the IOD changes, as in previous studies. Prediction was performed with a first-order polynomial model. Also, since it is assumed that signal loss occurs 3 minutes after the IOD changes, the length of the input fitting data in Case 3 is 3 minutes in total.

8A and 8B are graphs showing a comparison of errors in prediction results of RTS correction information according to types of signal prediction models.

8A and 8B show that PPP is performed for each case (Case 1 to Case 3) and horizontal and vertical position errors are calculated, respectively. Prediction was carried out for a total of 15 minutes from 14,580 seconds to 15,480 seconds, and vertical error is error In order to compare the size of , the absolute value was taken and expressed.

Referring to FIGS. 8A and 8B , in Case 3 using only the current IOD information after updating, the position error increases rapidly as the prediction length increases. This means that it may show less than typical PPP performance when forecasting. On the other hand, in the case of Case 1, it can be seen that the horizontal and vertical errors are similar to the position errors of the RTS original signal even if the prediction interval becomes longer. Case 2, which used a second-order polynomial model, showed intermediate performance between Cases 1 and 3.

In addition, since the RTS prediction error affects the filter covariance and the estimated value, if the error is large after 15,480 seconds, the RTS original signal and PPP performance are not the same even if it is out of the prediction interval, and an additional convergence period is required.

Hereinafter, based on the details described above, the operation flow of the present application will be briefly reviewed.

9 is an operational flowchart of a method for predicting RTS correction information considering IOD change of a GNSS navigation message according to an embodiment of the present invention.

The method of predicting RTS correction information in consideration of the IOD change of the GNSS navigation message shown in FIG. 9 can be performed by the prediction device 100 described above. Therefore, even if omitted below, the description of the prediction device 100 can be equally applied to the description of the RTS correction information prediction method considering the IOD change of the GNSS navigation message.

Referring to FIG. 9, in step S11, the receiving unit 110 (a) receives the navigation message (1) and the RTS correction information (2) in consideration of the renewal time of the IOD (Issue of Data) associated with the GNSS navigation message ( can be collected).

Specifically, in step S11, the receiving unit 110 receives (a1) the first navigation message 3, which is a navigation message received before the IOD (Issue of Data) update point, and the IOD (Issue of Data) update point after the update point. The second navigation message 4, which is a navigation message, may be classified and stored.

In addition, in step S11, the receiving unit 110 receives (a2) first RTS information 5, which is the RTS correction information received before the IOD (Issue of Data) update time and after the IOD (Issue of Data) update time. The second RTS information 6, which is the corrected RTS information, may be separately stored.

Next, in step S12, the shaping unit 120 may process input data for constructing a signal prediction model based on (b) the collected navigation message (1) and RTS correction information (2).

Specifically, in step S12, the shaping unit 120 determines that the interval before the IOD (Issue of Data) update corresponds to the first RTS information 5, and the interval after the IOD (Issue of Data) update corresponds to the second RTS Input data (12) is processed to include time-series data corresponding to information (6) and corrected RTS information (11) derived based on the trajectory difference between the first navigation message (3) and the second navigation message (4). can do.

Next, in step S13, the fitting unit 130 may generate a signal prediction model based on the input data 12 processed in step S12 (c).

Specifically, in step S13 , the fitting unit 130 may calculate coefficients of the time series prediction model through the fitting algorithm 21 based on the processed input data 12 .

Next, in step S14, the estimator 140 can predict (d) the disconnected RTS correction information based on the signal prediction model generated through step S13 when disconnection of the received RTS correction information 2 occurs.

Specifically, in step S14, the estimator 140 reflects the trajectory difference derived based on the first navigation message 3 and the second navigation message 4 in the model output data 31 of the signal prediction model, and then the disconnected RTS. The predicted RTS correction information 32 corresponding to the correction information may be derived.

In the foregoing description, steps S11 to S14 may be further divided into additional steps or combined into fewer steps, depending on an embodiment of the present invention. Also, some steps may be omitted if necessary, and the order of steps may be changed.

The RTS correction information prediction method considering the IOD change of the GNSS navigation message according to an embodiment of the present invention may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer readable medium. The computer readable medium may include program instructions, data files, data structures, etc. alone or in combination. Program instructions recorded on the medium may be those specially designed and configured for the present invention or those known and usable to those skilled in computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. - includes hardware devices specially configured to store and execute program instructions, such as magneto-optical media, and ROM, RAM, flash memory, and the like. Examples of program instructions include high-level language codes that can be executed by a computer using an interpreter, as well as machine language codes such as those produced by a compiler. The hardware devices described above may be configured to act as one or more software modules to perform the operations of the present invention, and vice versa.

In addition, the above-described method for predicting RTS correction information considering the IOD change of the GNSS navigation message may be implemented in the form of a computer program or application stored in a recording medium and executed by a computer.

The above description of the present application is for illustrative purposes, and those skilled in the art will understand that it can be easily modified into other specific forms without changing the technical spirit or essential features of the present application. Therefore, the embodiments described above should be understood as illustrative in all respects and not limiting. For example, each component described as a single type may be implemented in a distributed manner, and similarly, components described as distributed may be implemented in a combined form.

The scope of the present application is indicated by the following claims rather than the detailed description above, and all changes or modifications derived from the meaning and scope of the claims and equivalent concepts thereof should be construed as being included in the scope of the present application.

100: RTS correction information prediction device considering IOD change of GNSS navigation message
110: receiver
120: shape part
130: conforming part
140: estimation unit
1: GNSS navigation messages
2: RTS correction information
11: Corrected RTS information
12: input data
32: Predictive RTS correction information

Claims (15)

As a method of predicting RTS correction information considering IOD change of GNSS navigation message,
(a) collecting the navigation message and RTS correction information in consideration of the renewal time of IOD (Issue of Data) associated with the GNSS navigation message;
(b) processing input data for constructing a signal prediction model based on the navigation message and the RTS correction information;
(c) generating the signal prediction model based on the processed input data; and
(d) if the RTS correction information is disconnected, predicting the disconnected RTS correction information based on the signal prediction model;
including,
In step (a),
(a1) dividing and storing a first navigation message, which is a navigation message received before the update point in time, and a second navigation message, which is a navigation message received after the update point in time; and
(a2) dividing and storing first RTS information, which is RTS correction information received before the update point in time, and second RTS information, which is RTS correction information received after the update point in time;
including,
The RTS correction information prediction method of claim 1 , wherein the input data includes a signal for a satellite orbit processed to continuously change based on an update time of the IOD. delete According to claim 1,
By the step (b), the input data,
The section before the update time corresponds to the first RTS information, and the section after the update time corresponds to corrected RTS information derived based on the second RTS information and the trajectory difference between the first navigation message and the second navigation message. To be processed into time series data corresponding to, RTS correction information prediction method. According to claim 3,
The corrected RTS information,
Based on the update time point, the RTS correction information prediction method is derived to be continuous with the first RTS information. According to claim 3,
In step (b),
The corrected RTS information is derived based on Equation 1 below,
[Equation 1]

Here, t ₁ is an arbitrary time after the update point, r(t ₁ ) is the corrected RTS information, RTS(t ₁ ) is the second RTS information,

NAV (t ₁ ) is the trajectory difference, RTS correction information prediction method. According to claim 5,
In step (b),
The trajectory difference is derived based on Equation 2 below,
[Equation 2]

Here, NAV ₂ (t ₁ ) is the orbit of the satellite calculated based on the second navigation message, and the NAV ₁ (t ₁ ) is the orbit of the satellite calculated based on the first navigation message. Correction information prediction method. According to claim 1,
The signal prediction model is a time series prediction model,
In step (c),
Calculating coefficients of the time series prediction model through a fitting algorithm based on the processed input data, RTS correction information prediction method. According to claim 3,
In step (d),
and deriving predicted RTS correction information corresponding to the disconnected RTS correction information by reflecting the trajectory difference in output data of the signal prediction model. An apparatus for predicting RTS correction information considering the IOD change of a GNSS navigation message,
a receiving unit that collects the navigation message and RTS correction information in consideration of an update time of IOD (Issue of Data) associated with the GNSS navigation message;
a shape unit processing input data for constructing a signal prediction model based on the navigation message and the RTS correction information;
an adapting unit generating the signal prediction model based on the processed input data; and
If the RTS correction information is disconnected, an estimator predicting the disconnected RTS correction information based on the signal prediction model;
including,
the receiver,
The first RTS information, which is the RTS correction information received before the update point, and the second navigation message, which is the navigation message received after the update point, are separated and stored. And dividing and storing second RTS information, which is RTS correction information received after the update time,
The input data includes a signal for a satellite orbit processed to continuously change based on the update time of the IOD, the RTS correction information prediction apparatus. delete According to claim 9,
The shape part,
The section before the update time corresponds to the first RTS information, and the section after the update time corresponds to corrected RTS information derived based on the second RTS information and the trajectory difference between the first navigation message and the second navigation message. Processing the input data into time series data corresponding to RTS correction information prediction apparatus. According to claim 11,
The corrected RTS information,
The apparatus for predicting RTS correction information, which is derived to be continuous with the first RTS information based on the update time point. According to claim 11,
The shape part,
The corrected RTS information is derived based on Equation 1 below,
[Equation 1]

Here, t ₁ is an arbitrary time after the update point, r(t ₁ ) is the corrected RTS information, RTS(t ₁ ) is the second RTS information,

NAV (t ₁ ) is the trajectory difference, RTS correction information prediction apparatus. According to claim 13,
The shape part,
The trajectory difference is derived based on Equation 2 below,
[Equation 2]

Here, NAV ₂ (t ₁ ) is the orbit of the satellite calculated based on the second navigation message, and the NAV ₁ (t ₁ ) is the orbit of the satellite calculated based on the first navigation message. Correction information prediction device. According to claim 9,
The signal prediction model is a time series prediction model,
The suitable part,
Calculating coefficients of the time series prediction model through a fitting algorithm based on the processed input data;
The estimator,
And deriving predicted RTS correction information corresponding to the disconnected RTS correction information by reflecting the trajectory difference in output data of the signal prediction model.

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