CN112558124A - Data quality analysis system and method of global satellite navigation system - Google Patents

Data quality analysis system and method of global satellite navigation system Download PDF

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CN112558124A
CN112558124A CN202011378691.0A CN202011378691A CN112558124A CN 112558124 A CN112558124 A CN 112558124A CN 202011378691 A CN202011378691 A CN 202011378691A CN 112558124 A CN112558124 A CN 112558124A
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data
module
unit
multipath
satellite
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张亮
吕增利
李兴斌
龚致远
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Dongfanghong Satellite Mobile Communication Co Ltd
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Dongfanghong Satellite Mobile Communication Co Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/396—Determining accuracy or reliability of position or pseudorange measurements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/03—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers
    • G01S19/07—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers providing data for correcting measured positioning data, e.g. DGPS [differential GPS] or ionosphere corrections
    • G01S19/072—Ionosphere corrections

Abstract

The invention belongs to the field of satellite navigation, and particularly relates to a data quality analysis system and a data quality analysis method of a global satellite navigation system, wherein the system comprises a data format conversion module, a data reading and storing module, a data processing module, a data statistical analysis module, a graph visualization module and a report output module; on one hand, the system can process BDS-3 data, and makes up for the functional deficiency of the existing software; on the other hand, the data quality analysis and the standard single-point positioning can be carried out on the GPS, the GLONASS, the BDS and the Galileo, and the data quality analysis and the standard single-point positioning can also be carried out on the QZSS and the IRNSS of the regional satellite navigation system.

Description

Data quality analysis system and method of global satellite navigation system
Technical Field
The invention belongs to the field of Satellite Navigation, and particularly relates to a data quality analysis System and a data quality analysis method of a Global Navigation Satellite System (Global Navigation Satellite System).
Background
Under the great trend of developing commercial aerospace, low-orbit satellites become research hotspots, and low-orbit satellite navigation enhancement is a great direction for future development in the field of satellite navigation. The low-orbit satellite navigation enhancement is based on a GNSS system, the current GNSS navigation system develops towards a multi-system multi-frequency multi-mode direction and comprises a GPS in the United states, a BDS in China, a GLONASS in Russia and a Galileo global satellite navigation system in Europe; countries are also developing their own regional satellite navigation systems, such as quasi-zenith satellite navigation system QZSS in japan, IRNSS in india; the quality of GNSS observation data directly influences positioning accuracy, the requirement of the high-precision positioning field on the data quality is higher, and meanwhile, the quality of the observation data can reflect the performance of a receiver and the rationality of site selection, so that the quality analysis of the GNSS observation data is necessary. Standard single-point positioning is widely used in fields where the positioning accuracy is not too high, such as: car, ship navigation, and field surveys.
However, the conventional GNSS data processing software Rtklib, Teqc and other software do not have the capability of full-system data quality analysis and standard single-point positioning, and meanwhile, a great deal of energy is consumed for troubleshooting by technical personnel in the field under the condition of poor positioning results.
Disclosure of Invention
In order to analyze the data quality of all frequency points of the existing satellite navigation system GPS, BDS, GLONASS, Galileo, QZSS and IRNSS, the invention provides a data quality analysis system and a method of a global satellite navigation system, wherein the system comprises a data format conversion module, a data reading and storage module, a data processing module, a data statistical analysis module, a graph visualization module and a report output module, wherein:
the data format conversion module comprises a data source judgment unit and a data calling unit, wherein the data source judgment unit is used for judging a data source and judging whether the data is from an IGS observation network or a receiver, and the data calling unit is used for calling CRX2RNX software to perform data format conversion on the data from the IGS observation network and calling a self format conversion tool of the receiver to perform data format conversion on the data from the receiver;
the data reading and storing module comprises a reading unit and a storing unit, wherein the reading unit comprises observation data reading and navigation data reading, the reading unit needs to read the file header information and the file body information of each kind of data, and the storing module stores the read information into a structural body corresponding to the information;
the data processing module is used for calculating to obtain a positioning result and outputting the positioning result to the data statistical analysis module, the graph visualization module and the report output module;
the data statistical analysis module is used for judging whether the positioning precision meets the standard or not according to the positioning result and the ICD file of the system;
the graph visualization module is used for returning a receipt chart according to the output results of the data processing module and the data statistical analysis module according to the time sequence;
and the report output module is used for summarizing the output results of the data processing module, the data statistical analysis module and the graph visualization module into a document and pushing the document to a user.
Furthermore, the data processing module comprises a visible satellite number calculating unit, a PDOP value calculating unit, a multipath calculating unit, a ranging noise unit and a signal-to-noise ratio extracting unit; wherein:
and the visible satellite number calculating unit calculates the visible satellite number of each time point at the current position according to the altitude angle by using the satellite number of each moment in the observation data.
The PDOP value calculation unit is used for calculating the PDOP value of the current moment according to the calculated position of the current satellite and the ground station position and a PDOP calculation formula;
the multipath calculation unit is used for solving a multipath value of each epoch of each satellite according to a multipath calculation formula according to a pseudo-range observation value and a carrier phase observation value of each epoch of each satellite in an observation file;
the ranging noise unit is used for solving the ranging noise of each epoch of each satellite according to the pseudo-range observed value of each epoch of each satellite in the measured file and the carrier phase observed value and the difference between the epochs after CC combination;
and the signal-to-noise ratio extraction unit is obtained by extracting signal-to-noise ratio original data in the observation file.
Further, the multipath calculating unit is configured to calculate results of different frequency point combinations, and then the pseudo-range multipath of the frequency point i is represented as:
Figure BDA0002808800880000031
wherein, PiThe pseudo range observed value is the frequency point i; l isiThe carrier phase observed value is the frequency point i; f. ofiFrequency of carrier phase being frequency point i, BiFor superposition of phase ambiguity parameters, hardware delay and multipath effects, i and j are two different frequency points, i is not equal to j.
Further, due to BiNot straightforward to calculate, in order to eliminate it from MPiInfluence of the value, calculating MPiThe sequence is obtained by averaging continuous arc segments, the length of the arc segment is set to 120 epochs, and the original MP is usediSubtracting the sequence to obtain a superposition B for removing the phase ambiguity parameter, the hardware delay and the multipath effectiInfluencing MPiAnd (4) sequencing.
Further, the configuration of each system in the global satellite navigation system in communication with the data quality analysis system includes:
the QZSS system adopts a QZST time system, and a coordinate system is JGS, which is similar to WGS-84;
the IRNSS system adopts an IRNSST time system, and the starting time is 1999/8/2200: 00:00, 13s earlier than UTC, with the coordinate system WGS-84;
the BDS system adopts a BDST time system, the starting time is UTC 2006/1/100: 00:00, and the coordinate system is CGCS 2000;
the GPS system adopts a GPST time system, the starting time is UTC 1980/1/600: 00:00, and the coordinate system is WGS-84;
the GLONASS system adopts a GLOT time system, and a coordinate system is PZ 90;
the Galileo system adopts a GST time system, the starting time is 1999/8/2200: 00:00 in world coordination, which is earlier than UTC13s, and the coordinate system is a GTRF coordinate system;
and converting all the time of each system into UTC for resolving, converting the coordinates of each system according to a 7-parameter conversion model, and converting all the coordinates into a WGS-84 coordinate system.
Further, when the data processing module carries out positioning in a single-frequency standard, the IRNSS system adopts a GPS K8 ionosphere model, the Galileo system adopts a Nequick ionosphere model, the BDS system adopts a BDSK9 ionosphere model, and the QZSS system adopts a broadcast ionosphere correction model.
The invention also provides a data quality analysis method of the global satellite navigation system, which comprises a data quality analysis system of the global satellite navigation system and carries out the following operations in the system:
s1, the data format conversion module of the system receives the data and converts the received data into RINEX format;
s2, reading data of the system according to a RINEX version data instruction manual and different navigation systems, and storing the read data into a corresponding structural body;
s3, calculating the number of visible satellites, a PDOP value, multipath, ranging noise and a signal-to-noise ratio according to the acquired data, and calculating to acquire a positioning result;
s4, counting the number of visible satellites in an observation time period and the maximum, minimum and average values of PDOP values, calculating the root mean square and standard deviation of multipath and ranging noise, and acquiring 95% positioning accuracy and the root mean square of positioning results in E, N, U three directions;
and S5, drawing graphs according to time sequence by using MATLAB according to the output results of the steps S3-S4, and summarizing the drawn graphs into a document to be pushed to a user.
1. The conventional GNSS data processing software cannot process the BDS-3 data, the BDS-3 data processing modules are added to the data quality analysis module and the standard single-point positioning module, the BDS-3 data can be processed, and the functional defects of the conventional software are overcome.
2. The ionosphere models are built in, and the correction effects of different ionosphere models in the same site can be compared.
3. At present, the commonly used GNSS data processing software can only perform data quality analysis and standard single-point positioning on some of the four systems, namely the GPS, the GLONASS, the BDS and the Galileo, but the system cannot perform data quality analysis and standard single-point positioning on the four systems and also brings the regional satellite navigation system QZSS and the IRNSS into the processing category.
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FIG. 1 is a flow chart of an implementation of a GNSS system data quality analysis system of the present invention;
FIG. 2 is a diagram illustrating positioning accuracy of a GNSS system data quality analysis system.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a data quality analysis system of a global satellite navigation system, which comprises a data format conversion module, a data reading and storing module, a data processing module, a data statistical analysis module, a graph visualization module and a report output module, wherein:
the data format conversion module comprises a data source judgment unit and a data calling unit, wherein the data source judgment unit is used for judging a data source and judging whether the data is from an IGS observation network or a receiver, and the data calling unit is used for calling CRX2RNX software to perform data format conversion on the data from the IGS observation network and calling a self format conversion tool of the receiver to perform data format conversion on the data from the receiver;
the data reading and storing module comprises a reading unit and a storing unit, wherein the reading unit comprises observation data reading and navigation data reading, the reading unit needs to read the file header information and the file body information of each kind of data, and the storing module stores the read information into a structural body corresponding to the information;
the data processing module is used for calculating to obtain a positioning result and outputting the positioning result to the data statistical analysis module, the graph visualization module and the report output module;
the data statistical analysis module is used for judging whether the positioning precision meets the standard or not according to the positioning result and the ICD file of the system;
the graph visualization module is used for returning a receipt chart according to the output results of the data processing module and the data statistical analysis module according to the time sequence;
and the report output module is used for summarizing the output results of the data processing module, the data statistical analysis module and the graph visualization module into a document and pushing the document to a user.
Example 1
In this embodiment, unifying the coordinates and time of the satellite navigation system accessing the system of the present invention specifically includes:
GS-84 is similar; the IRNSS system adopts an IRNSST time system, and the starting time is 1999/8/2200: 00:00, 13s earlier than UTC, with the coordinate system WGS-84;
the BDS system adopts a BDST time system, the starting time is UTC 2006/1/100: 00:00, and the coordinate system is CGCS 2000;
the GPS system adopts a GPST time system, the starting time is UTC 1980/1/600: 00:00, and the coordinate system is WGS-84;
the GLONASS system adopts a GLOT time system, and a coordinate system is PZ 90;
the Galileo system adopts a GST time system, the starting time is 1999/8/2200: 00:00 in world coordination, which is earlier than UTC13s, and the coordinate system is a GTRF coordinate system;
before inputting the data quality analysis system, the time and the coordinates acquired by each satellite navigation system need to be unified, in the embodiment, the time is all converted into UTC for resolving, the coordinate system can be converted through a 7-parameter conversion model, and the coordinates can be all converted into a WGS-84 coordinate system for facilitating resolving.
In the data processing module, when single-frequency standard positioning is carried out, the high-precision ionosphere model can reduce ionosphere errors and improve positioning precision, a proper ionosphere model can be selected, a GPS K8 ionosphere model commonly used by GPS, GLONASS and IRNSS, a Nequick ionosphere model commonly used by Galileo, a BDSK9 ionosphere model used by BDS and a QZSS broadcast ionosphere correction model commonly used by QZSS, and the system can select a proper ionosphere model to carry out correction according to different systems.
Example 2
In this embodiment, the data processing module is further described, and the data processing module includes a visible satellite number calculating unit, a PDOP value calculating unit, a multipath calculating unit, a ranging noise unit calculating unit, and a signal-to-noise ratio extracting unit.
When multipath calculation is carried out, the result of different frequency point combinations is given by adopting a multipath calculation formula, the multipath sizes of the different frequency point combinations are convenient to compare, and the pseudo-range multipath of the frequency point i is expressed as follows:
Figure BDA0002808800880000071
wherein, PiThe pseudo range observed value is the frequency point i; l isiThe carrier phase observed value is the frequency point i; f. ofiFrequency of carrier phase being frequency point i, BiFor superposition of phase ambiguity parameters, hardware delay and multipath effects, i and j are two different frequency points, i is not equal to j.
Due to BiNot good calculation, in order to reject BiFor the influence of pseudo-range multipath effect error, firstly, the non-subtracted BiOriginal MP ofiThe sequence adopts a continuous arc segment averaging mode, and is noteworthy that the length of the arc segment is set to be 120 epochs, and then the original MP is carried outiAnd subtracting the value from the sequence to obtain the pseudo-range multipath effect error.
Example 3
The conventional open source GNSS data processing software does not have the BDS-3B1C and B2a frequency point data processing capacity, and the invention is improved aiming at the point. In the embodiment, the two frequency points should be corrected for group delay in the standard single-point positioning.
And correcting pseudo-range observed values of the two frequency points, wherein when the two frequency points are pilot frequency components, the method comprises the following steps:
pB2adc＝pB2ap-c*TGDB2ap；
pB1cpc＝pB1Cp-c*TGDB1Cp；
when two frequency points are data components, there are:
pB2adC＝pB2ad-c*(TGDB2ad+ISCB2ad)；
pB1CdC＝pB1Cd-c*(TGDB1Cd+ISCB1Cd)；
wherein, TGDB2apIs the B2a pilot component delay difference, TGDB1CpIs the B1C pilot component delay difference; ISCB2adFor the delay correction term of the B2a data component relative to the B2a pilot component, ISCB1CdA delay correction term for the B1C data component relative to the B1C pilot component; p is a radical ofB2apCIs a pilot frequency component pseudo range observed value p after group delay correction of a B2a frequency pointB2adCThe pseudo-range observed value of the data component after group delay correction of the B2a frequency point is obtained; p is a radical ofB2apIs a raw pseudo range observed value, p, of a pilot frequency component of a frequency point B2aB2adThe original pseudo range observed value is a data component of a B2a frequency point; p is a radical ofB1CpCIs a pilot frequency component pseudo range observed value p after group delay correction of the B1C frequency pointB1CdCThe pseudo-range observed value of the data component after group delay correction of the frequency point B1C is obtained; p is a radical ofB1CpIs a raw pseudo range observed value, p, of a pilot frequency component of a frequency point B1CB1CdThe original pseudorange observation is taken as the pilot data component of the frequency point B1C, and c is the speed of light, as shown in fig. 2, which illustrates the positioning error of the frequency point data in three aspects of high level, horizontal and three dimensions in one embodiment.
Example 4
This embodiment provides a specific implementation of the ranging noise unit.
In this embodiment, the difference between epochs after CC combination is adopted as the method for obtaining the ranging noise, and the CC combination can be expressed as follows:
Figure BDA0002808800880000081
wherein the content of the first and second substances,
Figure BDA0002808800880000082
the pseudo range observation value of the i-number satellite at the time t is represented;
Figure BDA0002808800880000083
representing the observed value of the carrier phase of the satellite I at the time t; i represents an ionospheric delay error; mp represents a multipath error; n represents carrier phase ambiguity; ε represents the sum of other measurement noise; λ represents a wavelength.
The obtained CC combination sequence cannot be directly used for evaluating pseudorange measurement accuracy, and further processing is required to obtain clean noise. Due to the position of the ground station and the truncation angle, the ground station can only observe a part of arc sections of the i-number satellite, theoretically, the ground station can receive all data of the part of arc sections, the data are lost due to a receiver or the satellite, when the data vacancy is less than 10 epochs, a difference sequence is obtained by adopting a staggered subtraction method, and when the data vacancy is more than 10 epochs, a segmented difference form is adopted, so that the obtained difference sequence can reflect the real situation.
Example 5
The present example presents an embodiment of a combination of a method and a system.
The system in the embodiment comprises a data format conversion module, a data reading and storing module, a data processing module, a data statistical analysis module, a graph visualization module and a report output module, and the method comprises the following six steps:
step 1 data format conversion
Because the data sources are different, the adopted data format conversion methods are different, but the data formats are required to be converted into a uniform RINEX format finally, if the data are from an IGS observation network, CRX2RNX software is called to carry out data format conversion, if the data are from a certain brand receiver, a brand self-contained format conversion tool is called to carry out data format conversion, and the converted data in the uniform format are output to a data reading and storing module.
Step 2, data reading and storing
And reading data according to the corresponding RINEX version data instruction manual and different navigation systems, and dividing the data into an observation data reading part and a navigation data reading part. The observation data and navigation data reading part comprises file header information reading and file body information reading, and different information is stored in different structural bodies.
And step 3: data processing
The part comprises visible satellite number calculation, PDOP value calculation, multipath calculation, ranging noise calculation and signal-to-noise ratio extraction, and the result obtained by calculation is output to a data statistical analysis module and a graph visualization module.
And performing data processing according to the standard single-point positioning process and outputting the obtained positioning result to a data statistical analysis module, a graph visualization module and a report output module.
And 4, step 4: statistical analysis of data
Counting and calculating the maximum, minimum and average values of the number of visible satellites and the PDOP value in the observation time period; multipath, RMS of ranging noise, and STD. And (4) counting 95% positioning accuracy and RMS of the standard single-point positioning result in E, N, U three directions, and outputting the calculated result to a graph visualization module and a report output module.
And 5: graphical visualization
And (4) utilizing MATLAB to carry out drawing display on the results obtained in the steps (3) and (4) according to a time sequence, and storing and outputting the pictures to a report output module.
Step 6: report output
And summarizing the data statistical analysis result obtained in the step 4 and the image obtained in the step 5 to the same document, so that the user can conveniently check the data.
The invention can more intuitively observe the positioning result and the data quality index condition at a certain moment, and can quickly position the cause of the problem when the positioning result of a certain station is abnormal.
In the present invention, unless otherwise expressly stated or limited, the terms "mounted," "disposed," "connected," "fixed," "rotated," and the like are to be construed broadly, e.g., as meaning fixedly connected, detachably connected, or integrally formed; can be mechanically or electrically connected; the terms may be directly connected or indirectly connected through an intermediate, and may be communication between two elements or interaction relationship between two elements, unless otherwise specifically limited, and the specific meaning of the terms in the present invention will be understood by those skilled in the art according to specific situations.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.

Claims (10)

1. A data quality analysis system of a global satellite navigation system is characterized by comprising a data format conversion module, a data reading and storing module, a data processing module, a data statistical analysis module, a graph visualization module and a report output module, wherein:
the data format conversion module comprises a data source judgment unit and a data calling unit, wherein the data source judgment unit is used for judging a data source and judging whether the data is from an IGS observation network or a receiver, and the data calling unit is used for calling CRX2RNX software to perform data format conversion on the data from the IGS observation network and calling a self format conversion tool of the receiver to perform data format conversion on the data from the receiver;
the data reading and storing module comprises a reading unit and a storing unit, wherein the reading unit comprises observation data reading and navigation data reading, the reading unit needs to read the file header information and the file body information of each kind of data, and the storing module stores the read information into a structural body corresponding to the information;
the data processing module is used for calculating to obtain a positioning result and outputting the positioning result to the data statistical analysis module, the graph visualization module and the report output module;
the data statistical analysis module is used for judging whether the positioning precision meets the standard or not according to the positioning result and the ICD file of the system;
the graph visualization module is used for returning a receipt chart according to the output results of the data processing module and the data statistical analysis module according to the time sequence;
and the report output module is used for summarizing the output results of the data processing module, the data statistical analysis module and the graph visualization module into a document and pushing the document to a user.
2. The system of claim 1, wherein the data processing module comprises a visible satellite number calculating unit, a PDOP value calculating unit, a multipath calculating unit, a ranging noise unit, and a signal-to-noise ratio extracting unit; wherein:
and the visible satellite number calculating unit calculates the visible satellite number of each time point at the current position according to the altitude angle by using the satellite number of each moment in the observation data.
The PDOP value calculation unit is used for calculating the PDOP value of the current moment according to the calculated position of the current satellite and the ground station position and a PDOP calculation formula;
the multipath calculation unit is used for solving a multipath value of each epoch of each satellite according to a multipath calculation formula according to a pseudo-range observation value and a carrier phase observation value of each epoch of each satellite in an observation file;
the ranging noise unit is used for solving the ranging noise of each epoch of each satellite according to the pseudo-range observed value of each epoch of each satellite in the measured file and the carrier phase observed value and the difference between the epochs after CC combination;
and the signal-to-noise ratio extraction unit is obtained by extracting signal-to-noise ratio original data in the observation file.
3. The system according to claim 2, wherein the multipath calculating unit is configured to calculate results of different frequency point combinations, and the pseudo-range multipath at frequency point i is represented as:
Figure FDA0002808800870000021
wherein, PiThe pseudo range observed value is the frequency point i; l isiThe carrier phase observed value is the frequency point i; f. ofiFrequency of carrier phase being frequency point i, BiFor superposition of phase ambiguity parameters, hardware delay and multipath effects, i and j are two different frequency points, i is not equal to j.
4. The system of claim 3, wherein the computing MP is a MPiThe sequence is obtained by averaging continuous arc segments, the length of the arc segment is set to 120 epochs, and the original MP is usediSubtracting the sequence to obtain a superposition B for removing the phase ambiguity parameter, the hardware delay and the multipath effectiInfluencing MPiAnd (4) sequencing.
5. The system according to claim 3 or 4, wherein the pseudo-range observations of two frequency points are corrected, and when the two frequency points are pilot components, the pseudo-range observations are:
pB2adc＝pB2ap-c*TGDB2ap；
pB1cpc＝pB1Cp-c*TGDB1Cp；
when two frequency points are data components, there are:
pB2adC＝pB2ad-c*(TGDB2ad+ISCB2ad)；
pB1CdC＝pB1Cd-c*(TGDB1Cd+ISCB1Cd)；
wherein, TGDB2apIs the B2a pilot component delay difference, TGDB1CpIs the B1C pilot component delay difference; ISCB2adFor the delay correction term of the B2a data component relative to the B2a pilot component, ISCB1CdA delay correction term for the B1C data component relative to the B1C pilot component; p is a radical ofB2apCIs a pilot frequency component pseudo range observed value p after group delay correction of a B2a frequency pointB2adCThe pseudo-range observed value of the data component after group delay correction of the B2a frequency point is obtained; p is a radical ofB2apIs a raw pseudo range observed value, p, of a pilot frequency component of a frequency point B2aB2adThe original pseudo range observed value is a data component of a B2a frequency point; p is a radical ofB1CpCIs a pilot frequency component pseudo range observed value p after group delay correction of the B1C frequency pointB1CdCThe pseudo-range observed value of the data component after group delay correction of the frequency point B1C is obtained; p is a radical ofB1CpIs a raw pseudo range observed value, p, of a pilot frequency component of a frequency point B1CB1CdAnd c is the light speed, and the original pseudo range observed value is the pilot data component of the frequency point B1C.
6. The system of claim 2, wherein the ranging noise unit employs difference between epochs after CC combination, and when the data vacancy is less than 10 epochs, the difference sequence is obtained by using a staggered subtraction method, and when the data vacancy is more than 10 epochs, the difference sequence is in a segmented difference form.
7. The system of claim 6, wherein the CC combination is expressed as:
Figure FDA0002808800870000031
wherein, Pt iThe pseudo range observation value of the i-number satellite at the time t is represented;
Figure FDA0002808800870000032
representing the observed value of the carrier phase of the satellite I at the time t; i represents an ionospheric delay error; mp represents a multipath error; n represents carrier phase ambiguity; ε represents the sum of other measurement noise; λ represents a wavelength.
8. The system of claim 1, wherein the configuration of each system in the global satellite navigation system in communication with the data quality analysis system comprises:
the QZSS system adopts a QZSST time system, and the coordinate system is JGS;
the IRNSS system adopts an IRNSST time system, and the starting time is 1999/8/2200: 00:00, 13s earlier than UTC, with the coordinate system WGS-84;
the BDS system adopts a BDST time system, the starting time is UTC 2006/1/100: 00:00, and the coordinate system is CGCS 2000;
the GPS system adopts a GPST time system, the starting time is UTC 1980/1/600: 00:00, and the coordinate system is WGS-84;
the GLONASS system adopts a GLOT time system, and a coordinate system is PZ 90;
the Galileo system adopts a GST time system, the starting time is 1999/8/2200: 00:00 in world coordination, which is earlier than UTC13s, and the coordinate system is a GTRF coordinate system;
and converting all the time of each system into UTC for resolving, converting the coordinates of each system according to a 7-parameter conversion model, and converting all the coordinates into a WGS-84 coordinate system.
9. The system of claim 1, wherein the data processing module employs a GPS K8 ionosphere model for IRNSS, a Nequick ionosphere model for Galileo, a BDSK9 ionosphere model for BDS, and a broadcast ionosphere correction model for QZSS when performing positioning based on single frequency standard.
10. A method for data quality analysis of a global satellite navigation system, comprising any one of the systems of claims 1-9, the method comprising the steps of:
s1, the data format conversion module of the system receives the data and converts the received data into RINEX format;
s2, reading data of the system according to a RINEX version data instruction manual and different navigation systems, and storing the read data into a corresponding structural body;
s3, calculating the number of visible satellites, a PDOP value, multipath, ranging noise and a signal-to-noise ratio according to the acquired data, and calculating to acquire a positioning result;
s4, counting the number of visible satellites in an observation time period and the maximum, minimum and average values of PDOP values, calculating the root mean square and standard deviation of multipath and ranging noise, and acquiring 95% positioning accuracy and the root mean square of positioning results in E, N, U three directions;
and S5, drawing graphs according to time sequence by using MATLAB according to the output results of the steps S3-S4, and summarizing the drawn graphs into a document to be pushed to a user.
CN202011378691.0A 2020-12-01 2020-12-01 Data quality analysis system and method of global satellite navigation system Pending CN112558124A (en)

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