KR101433908B1 - Method and system for data quality check of gnss observation - Google Patents

Abstract

The present invention relates to a method of evaluating the quality of global navigation satellite system (GNSS) data and a system thereof and, more specifically, to a method of evaluating the quality of GNSS data capable of evaluating the quality of GNSS data in each ground station by providing comprehensive quality data such as the number of cycle slips in a carrier wave of GNSS data, number of outliers, number of short arcs, receiver noise, multi-path error amount of ionospheric layer delay errors of code and smoothed code, and ratio of measured data, and a system thereof. According to the present invention, by providing comprehensive quality data such as the number of cycle slips in a carrier wave of GNSS data, number of outliers, number of short arcs, receiver noise, multi-path error amount of ionospheric layer delay errors of code and smoothed code, and ratio of measured data, it is possible to evaluate the quality of GNSS data in each ground station.

Description

METHOD AND SYSTEM FOR DATA QUALITY CHECK OF GNSS OBSERVATION [0002]

The present invention relates to a method and system for evaluating data quality of a global navigation satellite system (GNSS), and more particularly, to a method and system for evaluating data quality of a global navigation satellite system (GNSS) the number of short arcs, the receiver noise, the multipath error of the code observations, the smoothed code multi-path error amount of the ionospheric delay error, and the ratio of the observed data to the GNSS data of each ground station The present invention relates to a method and system for evaluating GNSS data quality.

The ground augmentation system (GBAS) is a system developed for precise airport access and automatic landing of aircraft by providing users with GNSS error correction information and integrity information. If severe Ionospheric storms occur during operation of the system, the ionospheric delay value changes rapidly, and when the user of the reinforcement system uses the correction information when such ionospheric anomaly occurs, the accuracy of the user's position estimate is significantly degraded.

Users can be at great risk if the ionospheric anomalies falling within the category of the ionosphere threat model are not detected and notified in time by ground monitoring. As the next solar peak (2013-2015) approaches, we need to verify the threat model that is currently developed through continuous ionospheric analysis. In order to operate a safe GNSS reinforcement system around the world, we will develop a global and regional ionospheric threat model It should be developed.

Since the ionosphere and threat model development of the GNSS reinforcement system is based on GNSS observation data, the data quality of each station affects the performance of the whole system. Therefore, it is possible to improve the reliability of the threat model to be developed by evaluating the quality of the earth stations prior to the ionospheric analysis and removing the poor quality data in advance. Therefore, techniques should be developed to assess the quality of each ground-based GNSS data and provide quality information.

)와 반송파(

) 데이터는 다음과 같이 표현될 수 있다.There are TEQC (Translation, Editing, and Quality Check) software developed by UNAVCO (University Navstar Consortium), which is widely used to evaluate the quality of GNSS data. The TEQC software detects the cycle slip using the GNSS code and the carrier observation data. GNSS code (

) And a carrier wave

) The data can be expressed as follows.

은 k번째 위성과 i번째 수신기의 실제 거리, 대류층 지연 오차, 수신기 시계 오차 및 위성시계 오차의 합을 나타낸다. I는 전리층 지연 오차, M _Li 는 코드의 다중경로 오차, m _Li 는 반송파의 다중경로 오차를 나타낸다. 반송파 측정치는 모호정수 N _Li 를 포함하고 있으나, 코드 측정치보다 작은 잡음을 가지고 있다(

). 이중 주파수 반송파 관측치를 이용하여 다음 식과 같이 반송파 데이터를 이용한 전리층 지연 오차(반송파 전리층 지연 오차) I _Φ 와 전리층 지연오차의 시간 변화량 IOD를 산출할 수 있다. TEQC에서는 IOD가 분당 400cm를 넘어가면 사이클 슬립이라 판단하여 검출한다. IOD를 이용하여 검출한 사이클 슬립을 IOD 사이클 슬립이라 한다.

Represents the sum of the actual distance, the convective layer delay error, the receiver clock error, and the satellite clock error of the kth satellite and the ith receiver. I is the ionospheric delay error, M _Li is the multipath error of the code, and m _Li is the multipath error of the carrier. Carrier measurements contain a null integer N _Li , but have a noise less than the code measurement (

). Using the dual frequency carrier observations, we can calculate the ionospheric delay error (carrier ionospheric delay error) I _Φ using the carrier data and the time variation IOD of the ionospheric delay error as follows: In TEQC, if the IOD exceeds 400cm / min, it is judged to be a cycle-slip and detected. The cycle slip detected using the IOD is called an IOD cycle slip.

The techniques of the TEQC software also estimate the number of multipath (MP) cycle slips, the ratio of observed data, and multipath errors. The MP cycle slip represents the total cycle slip that occurred in the carrier data as a sum of IOD cycle slip and MP cycle slip due to additional cycle slip detected using multipath errors of L1 and L2 frequencies. The MP slip is detected through a linear combination of code and carrier observations. The linear combination of code and carrier is as follows.

When the cycle slip occurs, the slip of the MP is detected by measuring the change amounts of MP1 and MP2 as the values of the bias terms B ₁ and B ₂ are changed.

TEQC software distinguishes each data after each cycle slip after cycle slip detection. In each of the separated MP1 and MP2 data, the bias terms B ₁ and B ₂ are treated as constants, and then the multi-path error is estimated by taking RMS (root mean square) of MP 1 and MP 2 . TEQC also calculates the ratio of the observed data, which is the ratio of the number of observable data and the number of actually observed L1 / L2 codes and carrier data, considering the observed time.

However, TEQC's quality assessment has limitations in quality assessment for ionospheric analysis. In the event of ionospheric anomalies, the ionosphere fluctuates significantly in a short period of time, so the cycle slip detection process using the variation of ionospheric delay error (IOD) must be further refined. In addition, the software only calculates the multi-path error of the receiver, so that information on the receiver noise can not be known. Therefore, methods and systems should be developed to provide more detailed and comprehensive quality information for ionospheric analysis.

KR 10-2009-0042193 A

SUMMARY OF THE INVENTION The present invention has been devised to solve the above problems, and it is an object of the present invention to provide a method and apparatus for estimating the number of cycle slips of carrier cycles of GNSS data of each ground station, the number of outliers, A GNSS data quality evaluation system that can evaluate the GNSS data quality of each ground station by providing comprehensive quality information such as the amount of multi-path error of the smoothed code ionospheric delay error and the ratio of the observed data The purpose is to provide.

In order to achieve the above object, a method for evaluating a global navigation satellite system (GNSS) data quality of each ground station according to the present invention comprises the steps of: (a) obtaining GNSS data consisting of code data and carrier data from a ground station; Receiving; (b) detecting a cycle slip (hereinafter referred to as 'IOD cycle slip') using the variation amount (IOD) of the ionospheric delay error from the received GNSS data; (c) detecting an outlier from the received GNSS data; (d) detecting, in the ionospheric delay error estimation value data, a data interval (hereinafter referred to as 'short arc') in which the number of consecutive data is equal to or less than a predetermined value; And (e) estimating a multi-path error of the smoothed code ionospheric delay error for a data interval (hereinafter referred to as a 'long arc') in which the number of consecutive data is equal to or greater than a predetermined value, in the ionospheric delay error estimation value data .

The IOD cycle slip detection of step (b) may include detecting a loss of lock indicator (LLI) information included in the data received in step (a), indicating that the IOD exceeds a predetermined sleep threshold, If there is a data gap in both the code and the carrier data, it can be determined that the IOD cycle slip has occurred.

In order to detect an apparent cycle slip, the IOD cycle slip detection in the step (b) may be performed by detecting an IOD that is longer than a predetermined length, checking data within a predetermined time before and after the IOD cycle, If the predetermined length is not exceeded, the point can be judged as cycle slip.

The step (e) includes the steps of: (e1) calculating smoothed data of a code ionospheric delay error using a carrier ionospheric delay error; (e2) calculating a linear combination term using the smoothened code ionospheric delay error and the carrier ionospheric delay error; And

(e3) estimating the multi-path error of the smoothed code ionospheric delay error by obtaining the root mean square (RMS) of the remaining data after removing the algebraic combination term in the linear combination term.

에 의해 결정되고, 여기서 필터의 길이 N _s 는,

와 같이 나타내어지며,

는 시간상수 , T _s 는 데이터 비율, t는 시간,

는 코드 전리층 지연오차,

는 반송파 전리층 지연오차,

는 평활화된 코드 전리층 지연오차의 다중경로 오차,

는 평활화된 코드 전리층 지연오차의 수신기 잡음을 나타낸다.The _smoothed data ( I? _Smoothed ) of the code ionospheric delay error is converted into the _smoothed data

, Where the length of the filter, N _s ,

Lt; / RTI >

T _s is the data rate, t is the time,

Is the code ionospheric delay error,

Is the carrier ionospheric delay error,

Is the multi-path error of the smoothed code ionospheric delay error,

Represents the receiver noise of the smoothed code ionospheric delay error.

Wherein the linear combination term includes:

에 의해 결정되고,

는 모호정수 결합 항,

는 반송파 다중경로오차의 결합 항,

는 평활화된 코드 전리층 지연오차의 수신기 잡음,

는 반송파 전리층 지연오차의 수신기 잡음이다.

Lt; / RTI >

Is an ambiguous integer combining term,

Is a combination term of the carrier multipath error,

Is the receiver noise of the smoothed code ionospheric delay error,

Is the receiver noise of the carrier ionospheric delay error.

(F) estimating the number of MP (multipath) cycle slips, the ratio of the observed data, and multipath errors of the code data from the received GNSS data after step (a).

After step (f), (g) estimating the receiver noise of the ground station using the code of two consecutive days (2 days) and the linear combination term of the carrier observation can be further included.

According to another aspect of the present invention, a system for evaluating a global navigation satellite system (GNSS) data quality of each ground station includes: a GNSS data receiving module that receives GNSS data consisting of code data and carrier data from a ground station; An IOD cycle slip detection module for detecting a cycle slip (hereinafter, referred to as 'IOD cycle slip') using the variation amount (IOD) of the ionospheric delay error from the received GNSS data; An outlier detection module for detecting an outlier from the received GNSS data; (Hereinafter referred to as 'short arc') in which the number of consecutive data is equal to or less than a constant value and a data interval (hereinafter referred to as 'long arc' ) &Quot;) < / RTI > A multipath error estimation module of a smoothed code ionospheric delay error estimating a multipath error of a smoothed code ionospheric delay error for the long call; And a controller for controlling each of the modules of the GNSS data quality assessment system to perform a series of processes related to GNSS data quality evaluation.

The GNSS data quality evaluation system includes an MP cycle slip number calculation module for calculating the number of MP (multipath) cycle slips from the received GNSS data; A data rate calculating module for calculating a ratio of the observed data; And a code data multipath error estimation module for estimating a multipath error of the code data.

The GNSS data quality assessment system may further comprise a receiver noise estimation module for estimating receiver noise of the ground station using a code of two consecutive days (2 days) and a linear combination of carrier observations.

According to the present invention, the multiplexing of the number of carrier cycle slips, the number of outliers, the number of short calls, the receiver noise, and the smoothed code ionospheric delay error of GNSS data of each ground station It is possible to evaluate the GNSS data quality of each ground station by providing comprehensive quality information such as the amount of path error and the ratio of observed data.

BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 is a diagram of a process of a method for evaluating GNSS data quality according to the present invention.
2 shows an example of an apparent cycle slip;
3 is a diagram showing a configuration of a GNSS data quality evaluation system according to the present invention.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. Prior to this, terms and words used in the present specification and claims should not be construed as limited to ordinary or dictionary terms, and the inventor should appropriately interpret the concepts of the terms appropriately It should be interpreted in accordance with the meaning and concept consistent with the technical idea of the present invention based on the principle that it can be defined. Therefore, the embodiments described in this specification and the configurations shown in the drawings are merely the most preferred embodiments of the present invention and do not represent all the technical ideas of the present invention. Therefore, It is to be understood that equivalents and modifications are possible.

FIG. 1 is a diagram showing a process of a method for evaluating a GNSS data quality according to the present invention, and FIG. 2 is a diagram showing an example of an apparent cycle slip. Hereinafter, description will be made with reference to Figs. 1 and 2. Fig.

The comprehensive GNSS data quality evaluation system according to the present invention is a method of analyzing GNSS data composed of code data and carrier data to provide quality information. Receiver Independent Exchange Format (RINEX) dual frequency observation data observed at each station is used as an input value of the algorithm (S110), and the output value is data quality information of the station. As shown in FIG. 1, the algorithm is largely composed of four elements.

As a first component, we use the preprocessing process of the ionosphere analysis algorithm. In this process, the IOD cycle slip (S210), the singularity point (S220), and the number of short calls are provided as quality information. Secondly, we use the algorithm of TEQC quality evaluation software. Through this algorithm implementation, we estimate multi-path error of code data, ratio of observed data, and MP cycle slip. Third, an adaptive filter is used to calculate the receiver noise. Finally, we estimate the multi-path error of the code ionospheric delay error that has undergone the smoothing process.

In the preprocessing process of the existing ionospheric analysis algorithm, the variation of the carrier ionospheric delay error estimation value and the cycle slip of the carrier data detected using the IOD are referred to as IOD (derivative of ionospheric delay) cycle slip. In the preprocessing process, if the IOD exceeds the sleep threshold, eg, 2 m (interval of 30 seconds), or a Loss of Lock Indicator (LLI) information included in the RINEX data is displayed, or there is a data blank in both the code and the carrier observations If it exists, it is judged as a cycle slip. In the present invention, one more criterion is added here. This is to detect an apparent cycle slip. As shown in FIG. 2, an apparent cycle slip is a cycle slip having a small IOD value, but a cycle slip in which a difference in value is significant when compared with other surrounding values. In order to detect such a cycle slip, an IOD having a predetermined length, for example, 0.5 m or more is detected, and data within a predetermined time, for example, 15 minutes, , It is determined that this point is the cycle slip (S210).

The singular point generated in the ionospheric delay error estimation is also used as an index for evaluating the quality of observation data since it is an important factor that degrades the analysis performance in the process of analyzing the ionosphere (S220). The singular point detection is performed by performing polynomial fitting on data of consecutive specified intervals in the ionospheric delay error data and deriving a point of time in which the difference between the polynomial joint value and the ionospheric delay error data value is largest in the interval, Determining a point of time when the difference value at that point exceeds a preset reference value as a first point of singular point candidate and calculating an outlier factor for each data value of the interval, Determining a point of time as a second singular point candidate point and determining the point of time as a singular point when the first abnormal point candidate point and the second abnormal point candidate point are at the same point in time, ,

, And W _pq is calculated by:

Information on continuous arcs, that is, information on short arcs and information on long arcs are also calculated in the preprocessing step (S230). Continuous data from the ionospheric delay error estimation value data until there is a change in the ambiguity constant due to the cycle slip, that is, a continuous data interval having an ambiguous integer of the same size, is defined as an arc. A short call is defined as a short call for a short data interval of 10 or less (less than 300 seconds), and a long call for a longer data interval, and the algorithm detects it. Since leveling of carrier data is performed for each call, a short call with a small number of data may cause a large leveling error. The more frequently a cycle slip occurs, the higher the probability that a short call will occur. Therefore, the number of short calls and the number of cycle slips have a large correlation with each other. In the ionospheric delay error estimation value data, for long arc data, the multi-path error of the smoothed code ionospheric delay error is estimated as described later in the description of step S240.

Secondly, the algorithm of the TEQC quality evaluation software is used (S310, S320, S330). The TEQC software algorithm and the receiver noise estimation process may be performed separately from the preprocessing process.

Implement the technique of the TEQC software to estimate the number of MP (multipath) cycle slips (S310), the ratio of observed data (S320), and the multipath error (S330). The ratio of the observed data is the ratio of the number of observable data, the L1 / L2 code and the number of actually observed data in consideration of the observed time, and the MP cycle slip uses the multipath error of L1 and L2 frequencies And the number of total cycle slips generated in the carrier data by the sum of the IOD cycle slip and the MP cycle slip is calculated. As described in the related art, the MP cycle slip is estimated through the linear combination term of the code of Equation (8) to Equation (12) and the carrier data, and the multipath error of the code data is estimated by removing the constant term of the linear combination.

The third adaptive filter is designed to estimate the receiver noise (S340). The input of the adaptive filter uses two consecutive days of code and the linear combination of the carrier observations. By removing the bias terms in Equations (8) and (9), it is possible to easily estimate a value composed of only multipath errors and receiver noise as shown in the following Equation (15).

In the case of multipath errors, the multipath errors of two consecutive days are highly correlated because of the ambient environment of the station, while the receiver noise of the two days is less correlated. Thus, the adaptive filter can distinguish correlated multi-path errors and non-correlated receiver noise on two consecutive days. However, there is a case where the correlation between multipath errors is not well known depending on the environment around the station and the type of receiver / antenna. In this case, since the receiver noise can not be distinguished, the quality information on the receiver noise is indicated as N / A (not available).

Finally, the multi-path error of the smoothed code ionospheric delay error is calculated (S240). The calculation of the multi-path error of the smoothed code ionospheric delay error can be performed after the above-described preprocessing steps (S210, S220, S230). The smoothing of the code ionospheric delay error is calculated using the carrier ionospheric delay error as follows.

Where the length N _s of the filter,

, 데이터 비율 T _{s ,} 로 이루어져 있으며, t는 시간,

는 코드 전리층 지연오차,

는 반송파 전리층 지연오차이다., N _s is the time constant

, Consists of the data rate T _s,, t is time,

Is the code ionospheric delay error,

Is the carrier ionospheric delay error.

는 평활화된 코드 전리층 지연오차의 다중경로 오차,

는 평활화된 코드 전리층 지연오차의 수신기 잡음을 나타낸다. 평활화된 코드 전리층 지연오차를 구한 후 평활화된 코드 전리층 지연오차와 반송파 전리층 지연 오차를 이용하여 다음과 같은 선형결합 항,

를 산출한다.

Is the multi-path error of the smoothed code ionospheric delay error,

Represents the receiver noise of the smoothed code ionospheric delay error. The smoothed code ionospheric delay error is obtained, and then the smoothed code ionospheric delay error and the carrier ionospheric delay error are used to calculate the following linear combination term,

.

에서 모호정수 결합항인

는 상수로 취급하여 제거한 후 남은 데이터의 RMS를 구함으로 평활화된 코드 전리층 지연오차의 다중경로 오차를 추정한다.

는 반송파 다중경로오차의 결합 항,

는 평활화된 코드 전리층 지연오차의 수신기 잡음,

는 반송파 전리층 지연오차의 수신기 잡음이다.

Is an ambiguous integer combining term

Is treated as a constant, and the RMS of the remaining data is obtained. The multi-path error of the smoothed code ionospheric delay error is estimated.

Is a combination term of the carrier multipath error,

Is the receiver noise of the smoothed code ionospheric delay error,

Is the receiver noise of the carrier ionospheric delay error.

Quality information Yes Explanation Date 19 June
2004 Date the data was collected Station ID DANG Receiver type TRIMBLE
4000SSI Antenna type Unknown
External Possible observation (> 10deg) 22951 Number of observable data considering observation time Complete observations (> 10deg) 22387 The number of data that the L1 / L2 code and the carrier data actually observed Percentage of observations 98% (Complete observation / possible observation) x 100 Mean of SNR on L1 (> 10 deg) N / A SNR (Signal to Noise) average value of L1 code Mean of SNR on L2 (> 10deg) N / A SNR (Signal to Noise) average value of L2 code # of IOD slips (> 10.0 deg) 46 The total number of IOD cycle slips on all satellites during the observed time # of MP slips (> 10.0 deg) 16 The total number of MP cycle slips that occurred on all satellites during the observed time # of outliers (> 10.0deg) 8 The total number of singularities generated by all satellites during the observed time # of short arcs (> 10.0deg) 22 The total number of short calls that occurred on all satellites during the time observed. Mean of multipath on L1 code (> 10deg) 0.0962 (m) Average value of L1 code multipath error Mean of multipath on L2 code (> 10deg) 0.4624 (m) Average value of L2 code multipath error Mean MP smoothed with 150s (> 10deg) 0.2331 (m) Mean value of multipath error of smoothed code ionospheric delay error using a 150 second smoothing filter Mean MP smoothed with 300s (> 10deg) 0.1566 (m) Mean value of multipath error of smoothed code ionospheric delay error using a 300 second smoothing filter Receiver noise on L1 code (> 10deg) 0.0486 (m) Average value of L1 code receiver noise Receiver noise on L2 code (> 10deg) N / A Average value of L2 code receiver noise

Table 1 shows an example of the output value of the data quality evaluation algorithm. It shows the quality information of the data collected at the DANG observatory on June 19, 2004. The receiver type and antenna type can be confirmed in the header part of the collected RIINEX file, and the SNR (Signal to Noise) value is also recorded in the RINEX observation data. However, according to the RINEX version, SNR recording method is different, and SNR is recorded only in some observatories. Since the signals of low altitude satellites contain weak signal strength and relatively large signal errors and errors, it is difficult to reflect the different quality characteristics of each station. Therefore, the altitude angle of GPS data was limited to 10 degrees in the process of data quality evaluation. The number of IOD cycle slip, short arc, and singular point were calculated by preprocessing algorithm of ionospheric analysis algorithm. The ratio of observed data, multipath error of code, and number of MP cycle slip were calculated using TEQC technique. The multi-path error of the smoothed code ionospheric delay error provides the error information when using the 150 second smoothing filter and the 300 second smoothing filter as quality information. Finally, the receiver noise of the recorded code was calculated using an adaptive filter.

3 is a diagram illustrating a configuration of a global navigation satellite system (GNSS) data quality assessment system 100 according to the present invention.

The method performed by the GNSS data quality assessment system 100 has been described in detail with reference to FIGS. 1 and 2. Therefore, only the function of each module performing such a method will be briefly described below.

The control unit 101 controls the following modules of the GNSS data quality assessment system 100 to perform a series of processes related to GNSS data quality evaluation.

The GNSS data reception module 102 receives GNSS data composed of code data and carrier data from a ground station.

The IOD cycle slip detection module 103 detects a cycle slip (hereinafter referred to as "IOD cycle slip") using the variation amount (IOD) of the ionospheric delay error from the received GNSS data. Various methods of detecting the IOD cycle slip have been described above with reference to FIG.

The outlier detection module 104 detects an outlier from the received GNSS data.

The continuous arc detection module 105 detects a data interval (hereinafter referred to as a short arc) in which the number of consecutive data is less than a predetermined value (hereinafter referred to as a short arc) (Hereinafter referred to as a " long arc ") of a predetermined value or more.

The multi-path error estimation module 106 of the smoothed code ionospheric delay error estimates multi-path error of the smoothed code ionospheric delay error for the long call. The multipath error estimation method includes calculating smoothed data of a code ionospheric delay error using a carrier ionospheric delay error and calculating a linear combination term using the smoothed code ionospheric delay error and carrier ionospheric delay error And estimating a multi-path error of the smoothed code ionospheric delay error by obtaining a root mean square (RMS) of the remaining data after removing the algebraic combination term in the linear combination term, (16) to (19).

Also, a module for executing the TEQC algorithm includes an MP cycle slip number calculation module 107 for calculating the number of MP (multipath) cycle slips from the received GNSS data, a data rate calculation module 108 for calculating the ratio of the observed data And a code data multi-path error estimation module 109 for estimating a multi-path error of the code data. The code data multi-path error estimation module 109 estimates the multi-path error of the code data using the code of the two consecutive dates (2 days) And a receiver noise estimation module 110 for estimating a receiver noise of the receiver.

100: GNSS data quality evaluation system

Claims (11)

As a method for the GNSS data quality evaluation system to evaluate the global navigation satellite system (GNSS) data quality of each ground station,
(a) receiving GNSS data consisting of code data and carrier data from a ground station;
(b) detecting a cycle slip (hereinafter referred to as 'IOD cycle slip') using the variation amount (IOD) of the ionospheric delay error from the received GNSS data;
(c) detecting an outlier from the received GNSS data;
(d) detecting, in the ionospheric delay error estimation value data, a data interval (hereinafter referred to as 'short arc') in which the number of consecutive data is equal to or less than a predetermined value; And
(e) estimating a multi-path error of the smoothed code ionospheric delay error for a data interval (hereinafter referred to as a 'long arc') in which the number of consecutive data is equal to or greater than a predetermined value, in the ionospheric delay error estimation value data
/ RTI > The method according to claim 1,
The IOD cycle slip detection of step (b)
If the IOD exceeds a predetermined sleep threshold,
A signal lapse may be displayed in a loss of lock indicator (LLI) information included in the data received in the step (a)
If there is a data gap in both the code and the carrier data,
Judging that IOD cycle slip has occurred
Gt; a < / RTI > GNSS data quality evaluation method. The method according to claim 1,
The IOD cycle slip detection of step (b)
To detect an apparent cycle slip,
After detecting an IOD that is longer than a predetermined length, the data within a predetermined time before and after the detected IOD are checked, and when the surrounding IOD does not exceed the predetermined length, it is determined that the point is cycle slip
Gt; a < / RTI > GNSS data quality evaluation method. The method according to claim 1,
The step (e)
(e1) calculating smoothed data of a code ionospheric delay error using a carrier ionospheric delay error;
(e2) calculating a linear combination term using the smoothened code ionospheric delay error and the carrier ionospheric delay error; And
(e3) estimating the multi-path error of the smoothed code ionospheric delay error by obtaining the root mean square (RMS) of the remaining data after removing the ambiguous integer combining term in the linear combination term
Gt; a < / RTI > GNSS data quality evaluation method. The method of claim 4,
The _smoothed data ( I? _Smoothed ) of the code ionospheric delay error is converted into the _smoothed data

Lt; / RTI >
Where the length N _s of the filter,

Lt; / RTI >

T _s is the data rate, t is the time,

Is the code ionospheric delay error,

Is the carrier ionospheric delay error,

Is the multi-path error of the smoothed code ionospheric delay error,

Represents the receiver noise of the smoothed code ionospheric delay error
Gt; a < / RTI > GNSS data quality evaluation method. The method of claim 5,
Wherein the linear combination term includes:

Lt; / RTI >

Is an ambiguous integer combining term,

Is a combination term of the carrier multipath error,

Is the receiver noise of the smoothed code ionospheric delay error,

Is the receiver noise of the carrier ionospheric delay error
Gt; a < / RTI > GNSS data quality evaluation method. The method according to claim 1,
After step (a)
(f) estimating, from the received GNSS data, the number of MP (multipath) cycle slips, the ratio of the observed data, and the multipath error of the code data
Further comprising the step of: [Claim 7]
After the step (f)
(g) estimating the receiver noise of the ground station using the code of two consecutive days (2 days) and the linear combination term of the carrier observations
Further comprising the step of: As a system for evaluating the global navigation satellite system (GNSS) data quality of each ground station,
A GNSS data receiving module for receiving GNSS data consisting of code data and carrier data from a ground station;
An IOD cycle slip detection module for detecting a cycle slip (hereinafter, referred to as 'IOD cycle slip') using the variation amount (IOD) of the ionospheric delay error from the received GNSS data;
An outlier detection module for detecting an outlier from the received GNSS data;
(Hereinafter referred to as 'short arc') in which the number of consecutive data is equal to or less than a constant value and a data interval (hereinafter referred to as 'long arc' ) &Quot;)< / RTI >
A multipath error estimation module of a smoothed code ionospheric delay error estimating a multipath error of a smoothed code ionospheric delay error for the long call; And
A control unit for controlling the respective modules of the GNSS data quality evaluation system to perform a series of processes related to GNSS data quality evaluation
And the GNSS data quality evaluation system. The method of claim 9,
An MP cycle slip number calculation module for calculating the number of MP (multipath) cycle slips from the received GNSS data;
A data rate calculating module for calculating a ratio of the observed data; And
A code data multipath error estimation module for estimating a multipath error of code data
Wherein the GNSS data quality evaluation system further comprises: The method of claim 9,
A receiver noise estimation module for estimating receiver noise of a ground station using a code of two consecutive days (2 days) and a linear combination term of a carrier observation
Wherein the GNSS data quality evaluation system further comprises:

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