CN111505686B - Coarse difference elimination method based on Beidou navigation system - Google Patents

Coarse difference elimination method based on Beidou navigation system Download PDF

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CN111505686B
CN111505686B CN202010304738.2A CN202010304738A CN111505686B CN 111505686 B CN111505686 B CN 111505686B CN 202010304738 A CN202010304738 A CN 202010304738A CN 111505686 B CN111505686 B CN 111505686B
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CN111505686A (en
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韩军强
涂锐
卢晓春
张睿
范丽红
张鹏飞
刘金海
王星星
洪菊
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National Time Service Center of CAS
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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
    • G01S19/42—Determining position
    • G01S19/43—Determining position using carrier phase measurements, e.g. kinematic positioning; using long or short baseline interferometry
    • 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
    • G01S19/13—Receivers
    • G01S19/14—Receivers specially adapted for specific applications
    • 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
    • G01S19/13—Receivers
    • G01S19/20—Integrity monitoring, fault detection or fault isolation of space segment

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Abstract

The invention discloses a coarse difference elimination method based on a Beidou navigation system, which comprises the following steps of: data collection, data preprocessing, terrain environment modeling, rough difference elimination of an original observed value, positioning application and terrain environment model updating. According to the method, a receiver antenna terrain environment model is constructed by mainly utilizing the head and tail points of the Beidou satellite observation arc section, a pseudo range and phase observation value gross error identification is carried out by deducing a stop altitude angle based on the terrain through the environment model, a traditional constant stop altitude angle method is replaced, and the precision during positioning calculation can be greatly improved. Aiming at a complex environment, the method realizes effective identification of the rough difference of the original observed value by using a convenient method without increasing additional cost, and improves the positioning accuracy of the Beidou navigation system.

Description

Coarse difference elimination method based on Beidou navigation system
Technical Field
The invention belongs to the technical field of satellite positioning, and particularly relates to a coarse error rejection method based on a Beidou navigation system.
Background
Satellite positioning is realized by observing multiple satellites in the zenith direction through a receiver, and generating pseudo-range and phase observation values to determine the space position. Therefore, in order to obtain a receiver antenna position on the order of centimeters or even millimeters, the receiver is generally installed on the ground without any obstruction on the periphery. With the vigorous implementation and promotion of national disaster reduction and prevention projects, the precision positioning technology is applied in large scale in related fields, and the common measurement type Beidou receiver is deployed and applied in large area in environments such as high mountains and canyons. The big dipper antenna is in the complex environment (hereinafter referred to as complex environment) that big mountain shelters from and the large tracts of land vegetation of earth's surface influences on a large scale around, and the observation quality of big dipper part satellite this moment is influenced by reflection and diffraction factor and produces great gross error, if not by accurate discernment and rejection, this gross error will produce decimetre or even meter level influence to the positioning result. Currently, the positioning result of a cut-off altitude method adopted by the receiver interior and the traditional positioning processing method in a complex environment has many defects of low precision, poor reliability and the like.
By 2020, Beidou III in China has been networked and provides global service, and the satellite system consists of 3GEO +3IGSO +24MEO satellites at that time. How to realize effective elimination of original observed values of complex environments based on the Beidou satellite navigation system in China, the positioning precision is improved, implementation is convenient, additional economic cost is not increased, and the method has important value for large-scale application of Beidou third-generation navigation based on the complex environments.
Disclosure of Invention
Aiming at the defect that a rough tolerance processing algorithm based on a constant cut-off altitude angle in the existing Beidou navigation system positioning algorithm is in the high mountain canyon, a terrain environment model for establishing a survey area shield based on the observation information of the Beidou third-generation satellite navigation system is provided, and further a rough tolerance eliminating method based on the Beidou navigation system is provided.
The technical scheme of the invention is as follows: a coarse difference elimination method based on a Beidou navigation system comprises the following steps:
s1: data collection
Acquiring required data information by using a deployed Beidou third-generation navigation system to obtain an original observation value;
s2: data pre-processing
Based on the broadcast ephemeris, performing integrity check on the original observation value acquired by S1, calculating the satellite position by using the broadcast ephemeris, calculating the satellite azimuth angle and altitude angle information of each epoch by using the receiver approximate coordinate after the satellite position is completed, summarizing the satellite sight line information, and outputting a continuous observation arc-segment observation value, wherein the initial observation value and the final observation value of the arc-segment observation value are marked as head and tail points;
s3: modeling a terrain environment
Processing the arc observation values output by the S2, constructing an observation equation by using the processed multiple arc observation values, selecting a least square criterion to solve by using a fitting system, evaluating the fitting precision by using head and tail point vectors by using an index RMSE (RMSE), finally solving a fitting coefficient, and establishing a terrain environment model by using the fitting coefficient from 0 to 360 degrees by using 0.5 degree as a step length;
s4: raw observation gross error rejection
Repeating S2 to obtain the arc observation value again, deducing a cut-off height angle based on the terrain by using the terrain environment model obtained in S3, and performing gross error elimination on the arc observation value obtained again to obtain clean data;
s5: positioning applications
Positioning calculation is carried out by using the clean data processed by the S4, and the clean data is used for obtaining a high-precision positioning coordinate higher than the approximate coordinate;
s6: terrain environment model update
And after obtaining the high-precision positioning coordinates by utilizing S5, repeating S2-S3, updating the terrain environment model, and adjusting the cut-off angle constant for further positioning application.
Further, the data information in S1 includes pseudorange/phase raw data, ephemeris data, receiver approximate coordinates, and antenna height.
Further, the method for processing the arc segment observed value in S3 includes: deleting head and tail points caused by data transmission interruption, determining the azimuth ranges of all the head and tail points to be between 0 and 360 degrees, and carrying out background constraint on points outside the ranges to meet the condition that the ranges of the head and tail points are full of 0 to 360 degrees, thereby realizing head and tail connection.
Further, the method for constructing the terrain environment model in S3 includes the following steps:
s31: the observation equation is constructed by using the formula (1):
Figure GDA0003284786410000031
in the formula (1), n represents the fitting order, ai、bi、ciDenotes the fitting coefficient, exRepresenting the measurement height angle, x representing exA corresponding azimuth angle;
s32: selecting a least square criterion to solve a fitting system, evaluating fitting precision by using head and tail point vectors by adopting an index RMSE of a formula (2), and finally solving a fitting coefficient;
Figure GDA0003284786410000032
in the formula (2), e'iRepresenting the virtual satellite altitude using the model coefficient back-stepping, n is 360/0.5, i is {0,0.5, …,360 };
s33: from 0 to 360 degrees, taking 0.5 degrees as a step size, and establishing a terrain environment model by using the fitting coefficient, as shown in formula (3):
Figure GDA0003284786410000033
in equation (3), a 'model coefficient vector, e'iRepresenting the virtual satellite altitude using the model coefficients back-deducted, i ═ 0,0.5, …, 360.
Further, the gross error rejection method in S4 includes: and (3) replacing the traditional gross error rejection method with formulas (4) and (5), marking and rejecting the observed value by gross error, wherein the formulas (4) and (5) are as follows:
ex＜e′x+ethreshold……(4)
Figure GDA0003284786410000034
in formulas (4) and (5), exRepresenting the calculated value of the satellite altitude corresponding to the satellite azimuth x; e'xRepresenting interpolated values of altitude based on a model of the terrain environment, ethresholdRepresents a cut-off angle constant, and the initial modeling is generally 7 degrees; x is the number ofi＜x≤xi+ 0.5; when e isxIs less than e'x+ethresholdAnd eliminating the corresponding observation epoch.
Further, the positioning solution in S5 adopts an RTK positioning technique, that is, a short baseline is used to perform high-precision deformation monitoring, and during monitoring, a reference station and a monitoring station are respectively subjected to terrain environment modeling, and high-precision positioning is performed based on a terrain environment model.
The invention has the beneficial effects that: compared with the traditional gross error rejection method based on the independent Beidou system, the method still has the problems of low recognition rate and poor positioning accuracy in a complex environment, the method mainly utilizes the head and tail points of the Beidou satellite observation arc section to construct a receiver antenna terrain environment model, derives the cut-off altitude angle based on the terrain through the environment model to carry out pseudo-range and phase observation value gross error recognition, replaces the traditional constant cut-off altitude angle method, and further can greatly improve the accuracy during positioning resolving. Aiming at a complex environment, the method realizes effective identification of the rough difference of the original observed value by using a convenient method without increasing additional cost, and improves the positioning accuracy of the Beidou navigation system.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a flowchart of a method of example 1 of the present invention;
fig. 2 is a graph comparing the modeling results of the Beidou satellite observation arc segment and the Beidou terrain environment for 24 hours at a certain valley terrain reference station and a monitoring station in embodiment 2 of the invention.
Detailed Description
Example 1: in the embodiment, a rough error rejection method based on a Beidou navigation system is designed, is mainly suitable for complex terrains such as high mountain canyons and the like, and is specifically explained based on a method flow chart of fig. 1.
S1: data collection
And acquiring required data information including pseudo range/phase original data, ephemeris data, receiver approximate coordinates, antennas and the like by using the deployed Beidou third-generation navigation system to obtain an original observation value.
S2: data pre-processing
Based on the broadcast ephemeris, performing integrity check on the original observation value acquired by S1, calculating the satellite position by using the broadcast ephemeris, calculating the satellite azimuth angle and altitude angle information of each epoch by using the receiver approximate coordinate after the satellite position is completed, summarizing the satellite sight line information, and outputting a continuous observation arc-segment observation value, wherein the initial observation value and the final observation value of the arc-segment observation value are marked as head and tail points;
s3: modeling a terrain environment
Processing the arc segment observation value output by the step S2, wherein the processing method comprises the following steps: deleting head and tail points interrupted by data transmission, determining that the azimuth ranges of all the head and tail points are between 0 and 360 degrees, performing background constraint on the points outside the range to meet the condition that the range of the head and tail points is full of 0 to 360 degrees, realizing head and tail connection, obtaining processed arc section observed values, establishing an observation equation by using the processed arc section observed values, selecting a least square criterion to solve, evaluating the fitting precision by using head and tail point vectors by using an index RMSE, finally solving a fitting coefficient, taking 0.5 degree as a step length, and establishing a terrain environment model by using the fitting coefficient;
the construction method of the terrain environment model comprises the following steps:
s31: the observation equation is constructed by using the formula (1):
Figure GDA0003284786410000051
in the formula (1), n represents the fitting order, ai、bi、ciDenotes the fitting coefficient, exRepresenting the measurement height angle, x representing exA corresponding azimuth angle;
s32: selecting a least square criterion to solve a fitting system, evaluating fitting precision by using head and tail point vectors by adopting an index RMSE of a formula (2), and finally solving a fitting coefficient;
Figure GDA0003284786410000052
in the formula (2), e'iRepresenting the virtual satellite altitude using the model coefficient back-stepping, n is 360/0.5, i is {0,0.5, …,360 };
s33: from 0 to 360 degrees, taking 0.5 degrees as a step size, and establishing a terrain environment model by using the fitting coefficient, as shown in formula (3):
Figure GDA0003284786410000061
in equation (3), a 'model coefficient vector, e'iRepresenting the virtual satellite altitude using the model coefficients back-deducted, i ═ 0,0.5, …, 360.
S4: raw observation gross error rejection
Repeating S2 to obtain the arc observation value again, deriving a cut-off height angle based on the terrain by using the terrain environment model obtained in S3, and performing gross error elimination on the arc observation value obtained again, wherein the gross error elimination method comprises the following steps: and (3) replacing the traditional gross error rejection method with formulas (4) and (5), marking and rejecting the observed value by gross error, wherein the formulas (4) and (5) are as follows:
ex＜e′x+ethreshold……(4)
Figure GDA0003284786410000062
in formulas (4) and (5), exRepresenting the calculated value of the satellite altitude corresponding to the satellite azimuth x; e'xRepresenting interpolated values of altitude based on a model of the terrain environment, ethresholdRepresents a cut-off angle constant, and the initial modeling is generally 7 degrees; x is the number ofi＜x≤xi+ 0.5; when e isxIs less than e'x+ethresholdAnd then, removing the corresponding observation epoch to obtain clean data.
S5: positioning applications
And positioning calculation is carried out by using the clean data processed by the S4, RTK positioning technology is adopted in the positioning calculation, namely high-precision deformation monitoring is carried out by using a short baseline, terrain environment modeling is respectively carried out on the reference station and the monitoring station during monitoring, high-precision positioning is carried out based on a terrain environment model, and the high-precision positioning coordinate higher than the rough coordinate is obtained.
S6: terrain environment model update
And after obtaining the high-precision positioning coordinates by utilizing S5, repeating S2-S3, updating the terrain environment model, and adjusting the cut-off angle constant for further positioning application, wherein the specific adjustment method is to use the cut-off angle constant, namely e in the formula (4)thresholdThe setting is 5 degrees for further positioning applications.
Example 2: in this embodiment, the method in embodiment 1 is used for actual measurement, the Beidou satellite observation data and the terrain environment modeling result of 24 hours at a certain valley terrain reference station and a monitoring station are used, the result is shown in fig. 2, a closed circular line segment in the two modeling result graphs of the reference station and the monitoring station is a Beidou terrain environment model curve, an internal arc line segment is an observation arc segment of the Beidou satellite, the quality of an observed value in the arc segments gradually becomes poor from inside to outside, and meanwhile, the Beidou terrain environment model curve and the edge of the arc segment have good overlapping degree, so that a reasonable cut-off height angle e is set according to an empirical valuethresholdAnd then, the poor observed value of the arc segment edge can be subjected to anisotropic elimination processing through formulas (4) and (5).
Example 3: this example is used for further verification processing of the method of example 1 by using positioning data, and using the conventional gross error rejection method as the data before model optimization and the gross error rejection method of example 1 as the data after model optimization, the total positioning comparison results of 6 days of statistics 2020/01/02-2020/01/07 are shown in table 1:
TABLE 1 comparison of pre-model and post-model optimization data
Figure GDA0003284786410000071
As can be seen from Table 1, the indexes RMSE before optimization are improved in the 2D and U directions, the successful fixation rate of the epoch is averagely improved to more than 99%, and the reliability of the positioning result is greatly improved.
It should be noted that: it can be understood by those skilled in the art that all or part of the steps of the above embodiments may be accomplished by equivalent substitution, and the present invention may be applied to the positioning of complex terrains such as high mountains and canyons, and may also be applied to other fields or situations requiring the present invention, and the claims of the present invention should be included in the present invention.

Claims (6)

1. A coarse difference elimination method based on a Beidou navigation system is characterized by comprising the following steps:
s1: data collection
Acquiring required data information by using a deployed Beidou third-generation navigation system to obtain an original observation value;
s2: data pre-processing
Based on the broadcast ephemeris, performing integrity check on the original observation value acquired by S1, calculating the satellite position by using the broadcast ephemeris, calculating the satellite azimuth angle and altitude angle information of each epoch by using the receiver approximate coordinate after the satellite position is completed, summarizing the satellite sight line information, and outputting a continuous observation arc-segment observation value, wherein the initial observation value and the final observation value of the arc-segment observation value are marked as head and tail points;
s3: modeling a terrain environment
Processing the arc observation values output by the S2, constructing an observation equation by using the processed multiple arc observation values, selecting a least square criterion to solve by using a fitting system, evaluating the fitting precision by using head and tail point vectors by using an index RMSE (RMSE), finally solving a fitting coefficient, and establishing a terrain environment model by using the fitting coefficient from 0 to 360 degrees by using 0.5 degree as a step length;
s4: raw observation gross error rejection
Repeating S2 to obtain the arc observation value again, deducing a cut-off height angle based on the terrain by using the terrain environment model obtained in S3, and performing gross error elimination on the arc observation value obtained again to obtain clean data;
s5: positioning applications
Positioning calculation is carried out by using the clean data processed by the S4, and the clean data is used for obtaining a high-precision positioning coordinate higher than the approximate coordinate;
s6: terrain environment model update
And after obtaining the high-precision positioning coordinates by utilizing S5, repeating S2-S3, updating the terrain environment model, and adjusting the cut-off angle constant for further positioning application.
2. The Beidou navigation system based gross error rejection method of claim 1, wherein in S1, the data information comprises pseudorange and phase raw data, ephemeris data, receiver approximate coordinates and antenna height.
3. The coarse difference elimination method based on the Beidou navigation system according to claim 1, wherein the arc segment observation value in S3 is processed by the following method: deleting head and tail points caused by data transmission interruption, determining the azimuth ranges of all the head and tail points to be between 0 and 360 degrees, and carrying out background constraint on points outside the ranges to meet the condition that the ranges of the head and tail points are full of 0 to 360 degrees, thereby realizing head and tail connection.
4. The method for coarse rejection based on the Beidou navigation system according to claim 1, wherein the method for constructing the terrain environment model in S3 comprises the following steps:
s31: the observation equation is constructed by using the formula (1):
Figure FDA0003336599730000021
in the formula (1), n represents the fitting order, ai、bi、ciDenotes the fitting coefficient, exRepresenting the calculated value of the satellite altitude corresponding to the satellite azimuth x;
s32: selecting a least square criterion to carry out fitting system solution, evaluating fitting precision by using head and tail point vectors by adopting an index RMSE of a formula (2), and finally solving a fitting coefficient;
Figure FDA0003336599730000022
in the formula (2), e'iRepresenting the virtual satellite altitude using the model coefficient back-stepping, n is 360/0.5, i is {0,0.5, …,360 };
s33: from 0 to 360 degrees, taking 0.5 degrees as a step size, and establishing a terrain environment model by using the fitting coefficient, as shown in formula (3):
Figure FDA0003336599730000023
in equation (3), a 'model coefficient vector, e'iRepresenting the virtual satellite altitude using the model coefficients back-deducted, i ═ 0,0.5, …, 360.
5. The method for gross error rejection based on the Beidou navigation system of claim 1, wherein the method for gross error rejection in S4 is as follows: and (3) replacing the traditional gross error rejection method with formulas (4) and (5), marking and rejecting the observed value by gross error, wherein the formulas (4) and (5) are as follows:
ex<e′x+ethreshold······(4)
Figure FDA0003336599730000031
in formulas (4) and (5), exRepresenting the calculated value of the satellite altitude corresponding to the satellite azimuth x; e'xRepresenting interpolated values of altitude based on a model of the terrain environment, ethresholdRepresents a cut-off angle constant, and is modeled as 7 degrees for the first time; x is the number ofi<x≤xi+ 0.5; when e isxIs less than e'x+ethresholdAnd eliminating the corresponding observation epoch.
6. The method for gross error rejection based on the Beidou navigation system according to claim 1, wherein the positioning solution in S5 adopts an RTK positioning technology, that is, a short baseline is used for high-precision deformation monitoring, and when monitoring, the reference station and the monitoring station are respectively modeled in a terrain environment, and high-precision positioning is performed based on the terrain environment model.
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