A method for estimating DCB of a GNSS station receiver

Abstract

The present invention provides a method for estimating the receiver DCB of a GNSS station, comprising the following steps: 1. obtaining observation data for each GNSS station and classifying it; 2. classifying each GNSS station; 3. estimating a first ionospheric model and the receiver DCB of each selected Class A GNSS station; 4. obtaining the receiver DCBs of the remaining Class A and all Class B GNSS stations; 5. constructing a second ionospheric model; 6. obtaining the receiver DCB of each Class C GNSS station; 7. constructing a third ionospheric model within the coverage area of ​​all GNSS stations; and 8. obtaining a final receiver DCB for each GNSS station. The present invention classifies the GNSS stations and obtains the ionospheric model and the receiver DCB of each GNSS station through a step-by-step, sequential refinement process, thereby improving computational efficiency while effectively increasing the accuracy of the receiver DCB.

Description

Technical Field

[0001] The invention relates to a method for estimating a DCB of a receiver of a GNSS site, and belongs to the technical field of navigation and positioning. Background Art

[0002] GNSS receiver intersymbol bias (DCB) is a significant error source in GNSS positioning, and its accurate estimation is crucial for precision positioning and ionospheric modeling. Ionospheric delay and DCB parameters are coupled, and traditional DCB estimation methods can be generally categorized into two types: 1. Using inter-frequency differential observations of carrier-phase smoothed pseudoranges (i.e., P4 observations) as observations, DCB and ionospheric model coefficients are estimated simultaneously; 2. Using a known global or regional ionospheric model, DCB is estimated using the undifferenced, non-combined PPP method.

[0003] my country has built over 10,000 GNSS base stations and over 100,000 GNSS monitoring stations. With such a large number of densely populated GNSS stations, the above approach faces the following difficulties:

[0004] 1. If the DCB parameters and ionospheric model parameters are solved simultaneously, the number of parameters to be solved is huge, the calculation is not only time-consuming, but also requires high computing performance.

[0005] 2. If the non-differential non-combined PPP method is used, although parallel calculations are possible and the calculation efficiency is high, a relatively accurate ionospheric model is required. The accuracy of the ionospheric model in the Chinese region of the global ionospheric model is significantly lower than that of the ionospheric model in the European and American regions with a higher station density.

[0006] It can be seen that for my country's dense and huge number of GNSS stations, there is a lack of an efficient and high-precision receiver DCB estimation method. Summary of the Invention

[0007] The present invention provides a method for estimating the receiver DCB of a GNSS site based on site grading and step-by-step refinement, which can improve the receiver DCB estimation accuracy and estimation efficiency of densely populated GNSS sites.

[0008] In order to solve the above technical problems, the present invention provides a method for estimating the DCB of a GNSS station receiver, comprising the following steps:

[0009] Step 1: Obtain observation data from each GNSS station, and perform data quality analysis on the observation data from each GNSS station to classify the observation data from each GNSS station;

[0010] Step 2: Classify each GNSS station into grades according to the grade information of the observation data of each GNSS station. The grades of GNSS stations can be graded as A, B, or C.

[0011] Step 3: Select multiple Class A GNSS stations and use the carrier phase smoothed pseudorange method to estimate the first ionospheric model of the coverage area of ​​all the selected Class A GNSS stations and the receiver DCB of each selected Class A GNSS station;

[0012] Step 4: Based on the first ionospheric model, the undifferenced, non-combined PPP method is used to obtain the receiver DCB of each Class A GNSS station that did not obtain the receiver DCB in Step 3 and all Class B GNSS stations;

[0013] Step 5. Based on the observation data of each Class A GNSS station and each Class B GNSS station, the inter-frequency difference of each Class A GNSS station and each Class B GNSS station is calculated by the carrier phase smoothed pseudorange method. The inter-frequency difference of each Class A GNSS station and each Class B GNSS station is used as the observation value of the corresponding GNSS station. According to the satellite DCB and the receiver DCB of each Class A GNSS station and each Class B GNSS station obtained in Steps 3 and 4, the ionospheric STEC in the coverage area of ​​all Class A GNSS stations and all Class B GNSS stations is calculated and converted into ionospheric VTEC to construct a second ionospheric model for the coverage area of ​​all Class A GNSS stations and all Class B GNSS stations.

[0014] Step 6: Based on the second ionospheric model, the undifferenced non-combined PPP method is used to obtain the receiver DCB of each Class C GNSS station;

[0015] Step 7: Based on the observation data of each GNSS station, the inter-frequency difference of each GNSS station is calculated using the carrier phase smoothed pseudorange method. The inter-frequency difference of each GNSS station is used as the observation value of the corresponding GNSS station. Based on the satellite DCB and the receiver DCB of each GNSS station, the ionospheric STEC in the coverage area of ​​all GNSS stations is calculated and converted into the ionospheric VTEC to construct the third ionospheric model in the coverage area of ​​all GNSS stations.

[0016] Step 8: Based on the third ionospheric model, the final receiver DCB of each GNSS station is obtained using the non-differenced non-combined PPP method.

[0017] In a specific embodiment, the observation data of each GNSS site includes data integrity rate, pseudorange multipath error and cycle slip ratio, and the pseudorange multipath error includes a first frequency multipath error mp1 and a second frequency multipath error mp2.

[0018] In a specific embodiment, the data quality analysis of the observation data of each GNSS station described in step 1 is performed to classify the observation data of each GNSS station. Specifically, the data integrity rate, pseudorange multipath error, and cycle slip ratio of each GNSS station are classified according to preset values. The steps are as follows:

[0019] 1.1 A first preset value and a second preset value are set, where the first preset value is greater than the second preset value. If the data integrity rate of a GNSS station is not less than the first preset value, the data integrity rate of the GNSS station is rated as excellent. If the data integrity rate of the GNSS station is not greater than the second preset value, the data integrity rate of the GNSS station is rated as poor. If the data integrity rate of the GNSS station is between the first preset value and the second preset value, the data integrity rate of the GNSS station is rated as medium.

[0020] 1.2 A third preset value and a fourth preset value are set, where the third preset value is greater than the fourth preset value. If the cycle slip ratio of the GNSS station is not greater than the fourth preset value, the cycle slip ratio of the GNSS station is rated as excellent. If the cycle slip ratio of the GNSS station is not less than the third preset value, the cycle slip ratio of the GNSS station is rated as poor. If the cycle slip ratio of the GNSS station is between the third preset value and the fourth preset value, the cycle slip ratio of the GNSS station is rated as medium.

[0021] 1.3 A fifth preset value, a sixth preset value, a seventh preset value, and an eighth preset value are set, where the fifth preset value is greater than the sixth preset value, and the seventh preset value is greater than the eighth preset value. If the multipath error mp1 of the first frequency of the GNSS station is not greater than the sixth preset value, and the multipath error mp2 of the second frequency is not greater than the eighth preset value, the pseudorange multipath error level of the GNSS station is excellent. If the multipath error mp1 of the first frequency of the GNSS station is between the fifth and sixth preset values, and the multipath error mp2 of the second frequency of the GNSS station is between the seventh and eighth preset values, the pseudorange multipath error level of the GNSS station is medium. If the multipath error mp1 of the first frequency of the GNSS station is not less than the fifth preset value, the pseudorange multipath error level of the GNSS station is poor. If the multipath error mp2 of the second frequency of the GNSS station is not less than the seventh preset value, the pseudorange multipath error level of the GNSS station is poor.

[0022] In a specific embodiment, in step 2, each GNSS station is graded according to the grade information of the observation data of each GNSS station. The grade of the GNSS station can be grade A, grade B, or grade C. Specifically, each GNSS station is graded according to the grade of the data integrity rate, the grade of the pseudorange multipath error, and the grade of the cycle slip ratio of each GNSS station, as follows:

[0023] If two or three of the data integrity rate, pseudorange multipath error, and cycle slip ratio levels of a GNSS station are rated as excellent, the GNSS station is rated A. If two or three of the data integrity rate, pseudorange multipath error, and cycle slip ratio levels of a GNSS station are rated as medium, the GNSS station is rated B. If two or three of the data integrity rate, pseudorange multipath error, and cycle slip ratio levels of a GNSS station are rated as poor, the GNSS station is rated C. If one of the data integrity rate, pseudorange multipath error, and cycle slip ratio levels of a GNSS station is rated as excellent, one is rated as medium, and one is rated as poor, the GNSS station is rated C.

[0024] In a specific embodiment, the method for selecting multiple Class A GNSS sites in step 3 is as follows: a ninth preset value is set. If the number of Class A GNSS sites is not less than the ninth preset value, the ninth preset number of Class A GNSS sites are selected; if the number of Class A GNSS sites is less than the ninth preset value, all Class A GNSS sites are selected.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] The present invention divides high-density GNSS sites into Class A GNSS sites, Class B GNSS sites, and Class C GNSS sites according to the level of observation data, and uses the level of observation data to refine the receiver DCB and ionosphere model of the GNSS sites step by step. First, multiple Class A GNSS sites are selected to perform a first ionosphere model and estimate the receiver DCB of each selected Class A GNSS site. Then, based on the first ionosphere model, the receiver DCB of each Class B GNSS site and each remaining Class A GNSS site is estimated, and then the first ionosphere model is refined to obtain a second ionosphere model. Then, based on the second ionosphere model, the receiver DCB of each Class B GNSS site and each remaining Class A GNSS site is estimated. The ionospheric model estimates the receiver DCB of Class C GNSS sites, and then refines the second ionospheric model to obtain a third ionospheric model. Finally, based on the third ionospheric model, the DCBs of all GNSS sites are re-estimated to obtain the final receiver DCB of each GNSS site. The present invention avoids directly solving the receiver DCBs of all GNSS sites as unknowns. Instead, the GNSS sites are classified and the ionospheric model and the receiver DCB of each GNSS site are obtained through a step-by-step and sequential refinement process. This improves computational efficiency while effectively improving the accuracy of the receiver DCB. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 A flowchart of a method for estimating DCB of a GNSS station receiver provided by an embodiment of the present invention is provided. DETAILED DESCRIPTION

[0028] The present invention will be described in detail below with reference to the embodiments and accompanying drawings. It should be noted that the embodiments and features of the embodiments of the present invention can be combined with each other without conflict.

[0029] refer to Figure 1 A method for estimating a DCB of a GNSS station receiver comprises the following steps:

[0030] Step 1: Obtain observation data from each GNSS station, and perform data quality analysis on the observation data from each GNSS station to grade the observation data from each GNSS station.

[0031] Preferably, the observation data of each GNSS site includes data integrity rate, pseudorange multipath error and cycle slip ratio, and the pseudorange multipath error includes a multipath error mp1 of a first frequency and a multipath error mp2 of a second frequency.

[0032] Observation data from more than 100,000 GNSS stations in the China Land Status Network and geological disaster monitoring stations were collected, and the data integrity rate, pseudorange multipath error (MP1, MP2) and cycle slip ratio of each GNSS station were calculated using TEQC or ANUBIS software.

[0033] Step 2: Classify each GNSS station according to the grade information of the observation data of each GNSS station. The grade of the GNSS station can be A, B, or C.

[0034] Preferably, the data quality analysis of the observation data of each GNSS station described in step 1 is performed to grade the observation data of each GNSS station. Specifically, the data integrity rate, pseudorange multipath error and cycle slip ratio of each GNSS station are graded according to pre-set values. The steps are as follows:

[0035] 1.1 Set a first preset value and a second preset value, where the first preset value is greater than the second preset value. If the data integrity rate of a GNSS station is not less than the first preset value, the data integrity rate of the GNSS station is rated as excellent. If the data integrity rate of the GNSS station is not greater than the second preset value, the data integrity rate of the GNSS station is rated as poor. If the data integrity rate of the GNSS station is between the first preset value and the second preset value, the data integrity rate of the GNSS station is rated as medium. The first preset value is 95%, and the second preset value is 80%.

[0036] 1.2 A third preset value and a fourth preset value are set, where the third preset value is greater than the fourth preset value. If the cycle slip ratio of the GNSS station is not greater than the fourth preset value, the cycle slip ratio of the GNSS station is rated as excellent. If the cycle slip ratio of the GNSS station is not less than the third preset value, the cycle slip ratio of the GNSS station is rated as poor. If the cycle slip ratio of the GNSS station is between the third preset value and the fourth preset value, the cycle slip ratio of the GNSS station is rated as medium. The third preset value is 0.5, and the fourth preset value is 0.1.

[0037] 1.3 Set the fifth preset value, the sixth preset value, the seventh preset value, and the eighth preset value. The fifth preset value is greater than the sixth preset value, and the seventh preset value is greater than the eighth preset value. If the multipath error mp1 of the first frequency of the GNSS station is not greater than the sixth preset value and the multipath error mp2 of the second frequency is not greater than the eighth preset value, the level of the pseudorange multipath error of this GNSS station is excellent. If the multipath error mp1 of the first frequency of the GNSS station is between the fifth and sixth preset values ​​and the multipath error mp2 of the second frequency is within the seventh preset value, the level of the pseudorange multipath error of this GNSS station is excellent. If the multipath error mp1 of the first frequency of the GNSS station is not less than the fifth preset value, the level of the pseudorange multipath error of this GNSS station is poor; if the multipath error mp2 of the second frequency of the GNSS station is not less than the seventh preset value, the level of the pseudorange multipath error of this GNSS station is poor. The fifth preset value is 1.0, the sixth preset value is 0.5, the seventh preset value is 1.2, and the eighth preset value is 0.6.

[0038] Preferably, in step 2, each GNSS station is graded according to the grade information of the observation data of each GNSS station. The grade of the GNSS station can be grade A, grade B, or grade C. Specifically, each GNSS station is graded according to the grade of the data integrity rate, the grade of the pseudorange multipath error, and the grade of the cycle slip ratio of each GNSS station, as follows:

[0039] If two or three of the data integrity rate, pseudorange multipath error, and cycle slip ratio levels of a GNSS station are rated as excellent, the GNSS station is rated A. If two or three of the data integrity rate, pseudorange multipath error, and cycle slip ratio levels of a GNSS station are rated as medium, the GNSS station is rated B. If two or three of the data integrity rate, pseudorange multipath error, and cycle slip ratio levels of a GNSS station are rated as poor, the GNSS station is rated C. If one of the data integrity rate, pseudorange multipath error, and cycle slip ratio levels of a GNSS station is rated as excellent, one is rated as medium, and one is rated as poor, the GNSS station is rated C.

[0040] Step 3: Select multiple Class A GNSS stations and use the carrier phase smoothed pseudorange method to estimate the first ionospheric model of the coverage area of ​​all selected Class A GNSS stations and the receiver DCB of each selected Class A GNSS station.

[0041] Preferably, the method for selecting multiple Class A GNSS sites in step 3 is as follows: a ninth preset value is set; if the number of Class A GNSS sites is not less than the ninth preset value, the ninth preset number of Class A GNSS sites are selected; if the number of Class A GNSS sites is less than the ninth preset value, all Class A GNSS sites are selected, and the value of the ninth preset value is 500.

[0042] Phase-smoothed pseudorange inter-frequency deviations are used as observation values, and satellite DCBs are obtained from the European Orbit Determination Center (CODE). A fifth-order polynomial model is used to express the ionospheric TEC in the Chinese region. The receiver DCB of each selected Class-A GNSS station is used as an unknown parameter. The coefficients of the fifth-order polynomial model and the receiver DCB of each selected Class-A GNSS station are estimated simultaneously. The first ionospheric model of the coverage area of ​​all selected Class-A GNSS stations and the receiver DCB of each selected Class-A GNSS station are obtained.

[0043] Step 4: Based on the first ionospheric model, the undifferenced, non-combined PPP method is used to obtain the receiver DCB of each Class A GNSS station that did not obtain the receiver DCB through step 3 and all Class B GNSS stations.

[0044] Using undifferenced, non-combined observation equations and a static positioning method, the tropospheric static delay is calculated using an empirical model. A random walk constraint is imposed on the tropospheric wet delay, along with an a priori ionospheric model constraint. With fixed satellite ephemeris and precise clock errors, coordinate parameters, tropospheric delay parameters, and DCB parameters are estimated. The receiver DCB is obtained for each Class B GNSS station and for each Class A GNSS station that did not obtain a receiver DCB in step 3. Because the receiver DCB estimates for each GNSS station are independent, a 16-thread parallel computing method is used to improve computational efficiency.

[0045] Step 5. Based on the observation data of each Class A GNSS station and each Class B GNSS station, the inter-frequency difference of each Class A GNSS station and each Class B GNSS station is calculated by the carrier phase smoothed pseudorange method, and the inter-frequency difference of the GNSS station and each Class B GNSS station is used as the observation value of the corresponding GNSS station respectively. According to the satellite DCB and the receiver DCB of each Class A GNSS station and each Class B GNSS station obtained by steps 3 and 4, the ionospheric STEC in the coverage area of ​​all Class A GNSS stations and all Class B GNSS stations is calculated and converted into ionospheric VTEC. Preferably, the puncture point position and satellite elevation angle are calculated, and the ionospheric STEC in the coverage area of ​​all Class A GNSS stations and all Class B GNSS stations is converted into ionospheric VTEC in the coverage area of ​​all Class A GNSS stations and all Class B GNSS stations by the projection function, and a second ionospheric model of the coverage area of ​​all Class A GNSS stations and all Class B GNSS stations is constructed.

[0046] Step 6: Based on the second ionospheric model, the undifferenced non-combined PPP method is used to obtain the receiver DCB of each Class C GNSS station.

[0047] Step 7: Based on the observation data of each GNSS station, the inter-frequency difference of each GNSS station is calculated using the carrier phase smoothed pseudorange method. The inter-frequency difference of each GNSS station is used as the observation value of the corresponding GNSS station. Based on the satellite DCB and the receiver DCB of each GNSS station, the ionospheric STEC in the coverage area of ​​all GNSS stations is calculated and converted into the ionospheric VTEC to construct the third ionospheric model in the coverage area of ​​all GNSS stations.

[0048] Step 8: Based on the third ionospheric model, the final receiver DCB of each GNSS station is obtained using the non-differenced non-combined PPP method.

[0049] The above content is a further detailed description of the present invention in conjunction with specific preferred embodiments, and the specific implementation of the present invention should not be considered to be limited to these descriptions. For those skilled in the art of the present invention, several simple deductions and substitutions can be made without departing from the concept of the present invention, and all of these should be considered to fall within the scope of protection of the present invention.

Claims

1. A method for estimating DCB of a GNSS station receiver, characterized in that: The following steps are involved: Step 1: Obtain observation data from each GNSS station, and perform data quality analysis on the observation data from each GNSS station to classify the observation data from each GNSS station; Step 2: Classify each GNSS station into grades according to the grade information of the observation data of each GNSS station. The grades of GNSS stations can be graded as A, B, or C. Step 3: Select multiple Class A GNSS stations and use the carrier phase smoothed pseudorange method to estimate the first ionospheric model of the coverage area of ​​all the selected Class A GNSS stations and the receiver DCB of each selected Class A GNSS station; Step 4: Based on the first ionospheric model, the undifferenced, non-combined PPP method is used to obtain the receiver DCB of each Class A GNSS station that did not obtain the receiver DCB in Step 3 and all Class B GNSS stations; Step 5. Based on the observation data of each Class A GNSS station and each Class B GNSS station, the inter-frequency difference of each Class A GNSS station and each Class B GNSS station is calculated by the carrier phase smoothed pseudorange method. The inter-frequency difference of each Class A GNSS station and each Class B GNSS station is used as the observation value of the corresponding GNSS station. According to the satellite DCB and the receiver DCB of each Class A GNSS station and each Class B GNSS station obtained in Steps 3 and 4, the ionospheric STEC in the coverage area of ​​all Class A GNSS stations and all Class B GNSS stations is calculated and converted into ionospheric VTEC to construct a second ionospheric model for the coverage area of ​​all Class A GNSS stations and all Class B GNSS stations. Step 6: Based on the second ionospheric model, the undifferenced non-combined PPP method is used to obtain the receiver DCB of each Class C GNSS station; Step 7: Based on the observation data of each GNSS station, the inter-frequency difference of each GNSS station is calculated using the carrier phase smoothed pseudorange method. The inter-frequency difference of each GNSS station is used as the observation value of the corresponding GNSS station. Based on the satellite DCB and the receiver DCB of each GNSS station, the ionospheric STEC in the coverage area of ​​all GNSS stations is calculated and converted into the ionospheric VTEC to construct the third ionospheric model in the coverage area of ​​all GNSS stations. Step 8: Based on the third ionospheric model, the final receiver DCB of each GNSS station is obtained using the non-differenced non-combined PPP method.

2. The method for estimating the DCB of a GNSS station receiver according to claim 1, wherein: The observation data of each GNSS site includes a data integrity rate, a pseudorange multipath error, and a cycle slip ratio. The pseudorange multipath error includes a multipath error mp1 of a first frequency and a multipath error mp2 of a second frequency.

3. The method for estimating the DCB of a GNSS station receiver according to claim 2, wherein: In step 1, the observation data of each GNSS station is analyzed for data quality to classify the observation data of each GNSS station. Specifically, the data integrity rate, pseudorange multipath error, and cycle slip ratio of each GNSS station are classified according to pre-set values. The steps are as follows: 1.1 A first preset value and a second preset value are set, where the first preset value is greater than the second preset value. If the data integrity rate of a GNSS station is not less than the first preset value, the data integrity rate of the GNSS station is rated as excellent. If the data integrity rate of the GNSS station is not greater than the second preset value, the data integrity rate of the GNSS station is rated as poor. If the data integrity rate of the GNSS station is between the first preset value and the second preset value, the data integrity rate of the GNSS station is rated as medium. 1.2 A third preset value and a fourth preset value are set, where the third preset value is greater than the fourth preset value. If the cycle slip ratio of the GNSS station is not greater than the fourth preset value, the cycle slip ratio of the GNSS station is rated as excellent. If the cycle slip ratio of the GNSS station is not less than the third preset value, the cycle slip ratio of the GNSS station is rated as poor. If the cycle slip ratio of the GNSS station is between the third preset value and the fourth preset value, the cycle slip ratio of the GNSS station is rated as medium. 1.3 A fifth preset value, a sixth preset value, a seventh preset value, and an eighth preset value are set, where the fifth preset value is greater than the sixth preset value, and the seventh preset value is greater than the eighth preset value. If the multipath error mp1 of the first frequency of the GNSS station is not greater than the sixth preset value, and the multipath error mp2 of the second frequency is not greater than the eighth preset value, the pseudorange multipath error level of the GNSS station is excellent. If the multipath error mp1 of the first frequency of the GNSS station is between the fifth and sixth preset values, and the multipath error mp2 of the second frequency of the GNSS station is between the seventh and eighth preset values, the pseudorange multipath error level of the GNSS station is medium. If the multipath error mp1 of the first frequency of the GNSS station is not less than the fifth preset value, the pseudorange multipath error level of the GNSS station is poor. If the multipath error mp2 of the second frequency of the GNSS station is not less than the seventh preset value, the pseudorange multipath error level of the GNSS station is poor.

4. The method for estimating the DCB of a GNSS station receiver according to claim 2, wherein: In step 2, each GNSS station is graded according to the grade information of the observation data of each GNSS station. The grade of the GNSS station can be A, B, or C. Specifically, each GNSS station is graded according to the grade of the data integrity rate, the grade of the pseudorange multipath error, and the grade of the cycle slip ratio of each GNSS station, as follows: If two or three of the data integrity rate, pseudorange multipath error, and cycle slip ratio levels of a GNSS station are rated as excellent, the GNSS station is rated A. If two or three of the data integrity rate, pseudorange multipath error, and cycle slip ratio levels of a GNSS station are rated as medium, the GNSS station is rated B. If two or three of the data integrity rate, pseudorange multipath error, and cycle slip ratio levels of a GNSS station are rated as poor, the GNSS station is rated C. If one of the data integrity rate, pseudorange multipath error, and cycle slip ratio levels of a GNSS station is rated as excellent, one is rated as medium, and one is rated as poor, the GNSS station is rated C.

5. The method for estimating the DCB of a GNSS station receiver according to claim 2, wherein: The method for selecting multiple Class A GNSS sites in step 3 is as follows: a ninth preset value is set. If the number of Class A GNSS sites is not less than the ninth preset value, the ninth preset number of Class A GNSS sites are selected. If the number of Class A GNSS sites is less than the ninth preset value, all Class A GNSS sites are selected.

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