All-domain post-processing positioning method and system based on various types of Beidou enhancement services

Abstract

The invention discloses a global post-processing positioning method based on various types of Beidou enhancement services, and the method comprises the steps: obtaining the three-dimensional position information of a moving station at different positions through employing a plurality of positioning modes, and calculating the quality factors of the different positions in various positioning modes; acquiring high-precision three-dimensional positions of the moving station at different positions by using reference equipment; performing classified training on the random forest model by using the three-dimensional position information and quality factors of the moving station at different positions in multiple positioning modes and the high-precision three-dimensional position acquired by the reference equipment; and inputting the quality factors of the moving station at a certain position in various positioning modes into the trained random forest classification model to obtain position variances in various positioning modes, and fusing the three-dimensional position information in various positioning modes by using adaptive weighting to obtain optimal position information. According to the invention, different types of positioning results are fused, and the availability, reliability and positioning precision of Beidou positioning are improved.

Description

Technical Field

[0001] The present invention belongs to the field of satellite navigation and positioning technology, and specifically relates to a global post-processing positioning method and system based on various types of Beidou enhanced services. Background Art

[0002] The BeiDou Navigation Satellite System (BDS) was developed in accordance with the "three-step" strategy. The BeiDou-1 system was put into use in 2000, using an active positioning system to provide Chinese users with pseudo-range single-point positioning, timing, wide-area differential and short message communication services. The BeiDou-2 system was put into use in 2012. On the basis of being compatible with the BeiDou-1 system technical system, it added a passive positioning system to provide positioning, speed measurement, timing and short message communication services for users in the Asia-Pacific region. The BeiDou-3 system was put into use in 2020. On the basis of the BeiDou-2 system, it further improved its performance and expanded its functions to provide a variety of services, including: providing positioning, navigation and timing, global short message communication and international search and rescue services for the whole world; providing satellite-based augmentation, satellite-based precise single-point positioning, ground-based augmentation and regional short message communication services in China and surrounding areas, and supporting post-differential positioning and post-precision single-point positioning services.

[0003] Single Point Positioning (SPP) is a basic service provided by the BeiDou system that uses pseudo-range observations and broadcast ephemeris to achieve positioning. It covers the entire world, with a positioning accuracy of less than 5m. It can be acquired in real time and solved afterwards, and the positioning convergence time is 10 seconds.

[0004] Satellite-based Precise Point Positioning (PPP) uses BeiDou system GEO satellites to broadcast PPP-B2b satellite-based differential corrections, integrity information and other information to provide dual-frequency observation value enhancement services to users in China and surrounding areas. Its coverage area is China and surrounding areas, with a positioning accuracy of less than 0.4m, which can be obtained in real time, and a positioning convergence time of 20 minutes.

[0005] Ground-based enhanced positioning is based on network RTK (Real Time Kinematic) positioning technology. The data processing center processes the synchronous observation data of multiple Beidou system reference stations within a certain range, generates differential data and broadcasts it through mobile communications or the Internet. Users in the area receive satellite signals and differential signals to achieve high-precision real-time dynamic positioning. Its coverage area is the area covered by mobile communications in China and surrounding areas. The positioning accuracy is within 0.05m and can be obtained in real time. The positioning convergence time is 30 seconds.

[0006] Post Process Kinematic (PPK) is a method where users use the multi-frequency pseudo-range and carrier phase data synchronously observed by a single BeiDou system reference station and a mobile station to perform double-difference ionosphere-free combination to weaken the influence of atmospheric errors, thereby achieving high-precision post-processing positioning. Its coverage range is 20km centered on a single BeiDou reference station, with a positioning accuracy of 0.02m+1ppm×distance kilometers. It can be solved after the fact, and there is no positioning convergence time.

[0007] Post-precision single-point positioning (PPP) is a method in which users use the multi-frequency pseudorange and carrier phase observations of the Beidou system mobile station, the IGS precise ephemeris and precise satellite clock errors of the same period to perform non-differential and non-combined observation models, and correct them through a series of precise error correction models to achieve high-precision post-processing positioning. Its coverage is global, the positioning accuracy is within 0.2m, and it can be solved post-processing, with no positioning convergence time.

[0008] Based on pseudo-range single-point positioning, satellite-based precise single-point positioning, ground-based enhanced positioning, post-differential positioning and post-precision single-point positioning, the Beidou system can provide enhanced services and positioning capabilities at meter, decimeter and centimeter levels. However, due to the different coverage, positioning accuracy, convergence time and external dependency conditions of different types of enhanced services, how to make flexible fusion strategies, take advantage of each other to obtain the best comprehensive location information, and improve the availability, reliability and accuracy of Beidou positioning services is an urgent problem to be solved. Summary of the invention

[0009] In view of the problem of insufficient availability, reliability and accuracy of Beidou positioning services caused by the differences in existing positioning technologies, the present invention provides a global post-processing positioning method based on various types of Beidou enhanced services. The method is highly practical and flexible, improves the availability, reliability and positioning accuracy of Beidou positioning, and can be widely used in the field of Beidou navigation and positioning.

[0010] In order to achieve the above object, the technical solution provided by the present invention is a global post-processing positioning method based on various types of Beidou enhanced services, comprising the following steps: Step 1, using multiple positioning modes based on the BeiDou system to obtain the three-dimensional position information of the mobile station at different positions, calculating and recording the quality factors under various positioning modes at different positions, and using reference equipment based on the BeiDou system to obtain the high-precision three-dimensional position of the mobile station at different positions; Step 2, using the three-dimensional position information and quality factor of the mobile station at different positions in multiple positioning modes obtained in step 1, and the high-precision three-dimensional position of the mobile station at different positions obtained by the reference equipment to perform classification training on the random forest model to obtain a trained random forest classification model; Step 3: Input the quality factors of the mobile station in multiple positioning modes at a certain location into the random forest classification model trained in step 2 to obtain the position variance in multiple positioning modes. Use the adaptive weighting method to fuse the three-dimensional position information in various positioning modes to obtain the optimal positioning result at a certain location. Furthermore, the positioning modes in step 1 include two types: real-time positioning and post-processing positioning. Real-time positioning includes three modes: pseudo-range single-point positioning, satellite-based precise single-point positioning and ground-based enhanced positioning. Post-processing positioning includes two modes: post-differential positioning and post-precision single-point positioning. The quality factors of the three modes of pseudo-range single-point positioning, satellite-based precise single-point positioning and ground-based enhanced positioning include the number of satellites used, the standard deviation of the position error, the positioning solution mode, the differential delay and the precision factor. The quality factors of the post-differential positioning mode include the number of satellites used, the standard deviation of the position error, the positioning solution mode, the precision factor, the signal-to-noise ratio, the baseline length, the integrity of the observation data, the multipath error estimate, the carrier phase noise and the ambiguity fixed check ratio. The quality factors of the post-precision single-point positioning mode include the number of satellites used, the standard deviation of the position error, the positioning solution mode, the precision factor, the signal-to-noise ratio, the integrity of the observation data, the multipath error estimate, the carrier phase noise and the ambiguity fixed check ratio.

[0011] Furthermore, in step 2, the three-dimensional position of the mobile station at different positions in the multiple positioning modes obtained in step 1 is subtracted from the high-precision three-dimensional position obtained at the position using the reference device to obtain multiple position deviations, and the position deviations are divided according to the set accuracy classification level to obtain the corresponding position variance. The level division rules are as follows: (7) In the formula, Indicates location p Place i The position variance of the mobile station in the positioning mode is Indicates location p Place i The difference between the three-dimensional position of the mobile station and the high-precision three-dimensional position obtained by the reference equipment in this positioning mode, , , , , are the set position deviation thresholds, n The number of precision classification levels is set.

[0012] The quality factors of the mobile station in various positioning modes at different locations obtained in step 1 and the accuracy classification levels corresponding to the position deviations of the mobile station in various positioning modes at different locations obtained in step 1 are input into the random forest model to train the random forest classifier. At the same time, the classification accuracy of the random forest classifier is evaluated using the five-fold cross-validation method.

[0013] Furthermore, in step 3, the quality factors of the mobile station in different types of positioning modes at a certain position are input into the random forest classification model trained in step 2 to obtain the accuracy classification level of the different types of positioning modes at the position, and then obtain the position variance corresponding to the three-dimensional position information in various positioning modes at the position; assuming that at the position p Place i The adaptive weight of the three-dimensional position information of the mobile station in this positioning mode is , the three-dimensional position information under various positioning modes is independent of each other and is an unbiased estimate of the optimal position information, then: (8) (9) In the formula, represents the mathematical expectation, Respectively indicate the location p The mobile station is i , j The three-dimensional position information under the positioning modes, N represents the number of positioning modes. is the optimal positioning result of the mobile station to be solved; In order to make the fusion variance The Lagrange multiplier method is used to solve the multivariate function extreme value, and the minimum adaptive weight and the minimum fusion variance of different types of positioning modes are obtained. The three-dimensional position information under various positioning modes is multiplied by the corresponding minimum adaptive weight, and the optimal positioning result of the mobile station is obtained by accumulation. , the specific calculation method is as follows: (10) (11) (12) In the formula, Indicates location p Place i The minimum adaptive weight of the positioning mode, represents the variance of the optimal positioning result, For location p Place i The position variance corresponding to the three-dimensional position information in the positioning mode.

[0014] The present invention also provides a global post-processing positioning system based on various types of Beidou enhanced services, which is used to implement the global post-processing positioning method based on various types of Beidou enhanced services as described above.

[0015] Moreover, it includes a processor and a memory, the memory is used to store program instructions, and the processor is used to call the stored instructions in the memory to execute the global post-processing positioning method based on various types of Beidou enhanced services as described above.

[0016] Alternatively, it includes a readable storage medium having a computer program stored thereon, and when the computer program is executed, it implements the global post-processing positioning method based on various types of Beidou enhanced services as described above.

[0017] Compared with the prior art, the present invention has the following advantages: 1) For the pseudo-range single-point positioning, satellite-based precise single-point positioning, ground-based enhanced three-dimensional position information acquired in real time, and the precise single-point positioning and differential positioning three-dimensional position information obtained by post-processing, the applicable scope, positioning accuracy, convergence time, etc. of various types of positioning methods are comprehensively analyzed. According to the various types of three-dimensional position information and their quality factors, machine learning is used to perform accuracy classification, and the optimal comprehensive three-dimensional position information is obtained based on adaptive weighted fusion.

[0018] 2) This method can realize the flexible integration and comprehensive application of different types of positioning methods, improve the availability, reliability and positioning accuracy of Beidou positioning, and can be widely used in Beidou navigation and positioning fields such as land measurement, aerial surveying and mapping, and ocean navigation and surveying. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 The present invention is a flowchart of a global post-processing positioning method based on various types of Beidou enhanced services in an embodiment of the present invention.

[0021] Figure 2 This is a diagram of the random forest classification modeling process of an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in combination with the drawings and embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] Example 1 like Figure 1 As shown, the embodiment of the present invention provides a global post-processing positioning method based on various types of Beidou enhanced services, including the following steps: Step 1: Based on the different real-time positioning modes (pseudo-range single-point positioning, satellite-based precise single-point positioning, and ground-based enhanced positioning) set by the Beidou system according to the mobile station receiver, the three-dimensional position information and quality factor of the mobile station at different positions in different modes are obtained in real time. At the same time, the high-precision three-dimensional position of the mobile station at different positions is obtained using the reference equipment based on the Beidou system.

[0024] The quality factor includes the number of satellites used, the standard deviation of position error, the positioning solution mode, the differential delay, the precision factor, etc. The number of satellites used is the total number of satellites involved in the positioning solution. The standard deviation of the position error is the measurement error of the positioning solution of latitude, longitude and altitude. If the least squares positioning solution is used, the least squares residual is used to represent the measurement error; if the Kalman filter positioning solution is used, the position state variance is used to represent the measurement error. The positioning solution mode of the pseudo-range single point positioning mode is the pseudo-range single point positioning mode. The positioning solution modes of satellite-based precise single point positioning include pseudo-range single point positioning mode, fixed solution mode of satellite-based precise single point positioning, and floating solution mode of satellite-based precise single point positioning. The positioning solution modes of ground-based enhanced positioning include pseudo-range single point positioning mode, ground-based enhanced positioning pseudo-range differential mode, fixed solution mode of ground-based enhanced positioning, and floating solution mode of ground-based enhanced positioning. The differential delay is the difference between the time of the differential correction used and the time of the current observation value. The precision factor is calculated from the horizontal precision factor, elevation precision factor, and time precision factor. The calculation formula is: (1) Where GDOP is the Dilution of Precision, HDOP is the Horizontal Dilution of Precision, VDOP is the Elevation Dilution of Precision, and TDOP is the Temporal Dilution of Precision.

[0025] Step 2: When the coverage of the reference station includes the position of the mobile station, a post-PPK solution is performed based on the original BeiDou system observations of the reference station and the mobile station to obtain the three-dimensional position information and quality factor of the mobile station at different positions. At the same time, the reference equipment is used to obtain the high-precision three-dimensional position of the mobile station at different positions.

[0026] The quality factor includes the number of satellites used, the standard deviation of position error, the positioning solution mode, the precision factor, the signal-to-noise ratio, the baseline length, the observation data integrity, the multipath error estimate, the carrier phase noise, the ambiguity fixed check ratio, etc. The number of satellites used is the total number of satellites involved in the positioning solution. The standard deviation of position error is the measurement error of the latitude, longitude and altitude positioning solution. If the least squares positioning solution is used, the least squares residual is used to represent the measurement error; if the Kalman filter positioning solution is used, the position state variance is used to represent the measurement error. The positioning solution mode of the post-differential positioning mode includes the post-pseudorange single point positioning mode, the post-differential positioning pseudorange difference mode, the post-differential positioning fixed solution mode and the post-differential positioning floating point solution mode. The precision factor is calculated by the horizontal precision factor, the elevation precision factor and the time precision factor, and the calculation method is the same as formula (1). The signal-to-noise ratio is the ratio of the carrier signal power to the noise power spectrum density. The baseline length is the relative distance calculated based on the known base station coordinates and the solved mobile station coordinates.

[0027] The completeness of observation data includes the completeness rate of single-frequency observation data and single system observation data completeness rate , calculated by the following formula: (2) (3) In the formula, represents the completeness rate of single-frequency observation data, n represents the number of satellites observed during the observation period, represents the total number of actual observation epochs of the jth satellite at a certain frequency point during the observation period, represents the total number of theoretical epochs of the jth satellite at a certain frequency point during the observation period, represents the completeness rate of single system observation data, It indicates the number of epochs during the observation period when all the frequencies of the jth satellite have valid observation data. represents the total number of theoretical epochs of the jth satellite during the observation period.

[0028] Multipath Error Estimate Calculated using the following formula: (4) In the formula, Indicates that the satellite is observed Multipath error estimate in frequency, represents the number of epochs of the sliding window, Indicates the epoch Satellites were observed The amount of calculation that includes multipath error and integer ambiguity information on frequency.

[0029] Carrier phase noise Calculated using the following formula: (5) In the formula, It indicates the number of cubic differences of the satellite carrier phase observations at adjacent epochs at a certain frequency point. Indicates the epoch The satellite phase observation at a certain frequency is observed. It represents the group difference (third-order difference) of the secondary difference of the carrier phase observations of adjacent epochs at a certain frequency point.

[0030] The fuzzy fixed check ratio is calculated using the following formula: (6) In the formula, ratio represents the fuzzy fixed check ratio, represents the sub-minimum residual sum of squares in the fixed solution, represents the minimum residual sum of squares among the stationary solutions.

[0031] Step 3: Perform post-PPP solution based on the original Beidou system observations and precise satellite ephemeris, clock error files, and correction numbers of the mobile station to obtain the three-dimensional position information and quality factor of the mobile station at different locations. At the same time, the Beidou system uses the reference equipment to obtain the high-precision three-dimensional position of the mobile station at different locations.

[0032] The quality factor includes the number of satellites used, the standard deviation of position error, the positioning solution mode, the precision factor, the signal-to-noise ratio, the observation data integrity, the multipath error estimate, the carrier phase noise, the ambiguity fixed check ratio, etc. The number of satellites used is the total number of satellites involved in the positioning solution. The standard deviation of position error is the measurement error of the latitude, longitude and altitude positioning solution. If the least squares positioning solution is used, the least squares residual is used to represent the measurement error; if the Kalman filter positioning solution is used, the position state variance is used to represent the measurement error. The positioning solution mode of the post-precision single point positioning mode includes the post-pseudorange single point positioning mode, the post-precision single point positioning fixed solution mode, and the post-precision single point positioning floating solution mode. The precision factor is calculated by the horizontal precision factor, the elevation precision factor and the time precision factor, and the calculation method is the same as formula (1). The signal-to-noise ratio is the ratio of the carrier signal power to the noise power spectral density. The observation data integrity evaluation method is the same as formulas (2) and (3). The multipath error evaluation method is the same as formula (4). The calculation method of carrier phase noise is the same as formula (5). The evaluation method of ambiguity fixed check ratio is the same as formula (6).

[0033] Step 4, using the three-dimensional position information and quality factor of the mobile station in multiple positioning modes at different positions obtained in steps 1 to 3, and the high-precision three-dimensional position of the mobile station at different positions obtained by the reference equipment to perform classification training on the random forest model to obtain a trained random forest classification model.

[0034] The three-dimensional position information of the five positioning modes (pseudorange single point positioning, satellite-based precise single point positioning, ground-based enhanced positioning, post-differential positioning, and post-precision single point positioning) obtained in steps 1 to 3 is subtracted from the high-precision three-dimensional position obtained by the reference equipment to obtain multiple position deviations. The position deviation is divided into 8 accuracy classification levels according to the accuracy classification table set in Table 1, among which the accuracy classification level of category 1 is the highest and the accuracy classification level of category 8 is the lowest. Each accuracy classification level has a corresponding position variance.

[0035] Table 1 Accuracy level classification list

[0036] Random forest is a supervised machine learning ensemble algorithm based on decision trees. It adds random attribute selection in the process of decision tree construction, which can effectively solve the overfitting problem and improve noise resistance. The random forest classification method randomly samples the characteristic variables and labeled samples of the training data set when constructing multiple decision trees. Each sampling result obtains a decision tree, and each tree can generate decision rules and classification results that conform to its own attributes. The random forest classification algorithm implementation combines the decision rules and classification results of all trees.

[0037] The quality factors of the mobile station in various positioning modes at different locations obtained from steps 1 to 3 and the accuracy classification levels corresponding to the position deviations of the mobile station in various positioning modes at different locations obtained from step 1 to step 3 are input into the random forest model to train the random forest classifier. At the same time, the classification accuracy of the random forest classifier is evaluated using the five-fold cross-validation method, that is, the five-fold method is repeated to use four equal parts of the data for model training and one equal part of the data to test the classification accuracy of the random forest classifier. Figure 2 , in order to improve the accuracy of the overall random forest classification model.

[0038] Step 5, input the quality factors of the mobile station in multiple positioning modes at a certain location into the random forest classification model trained in step 4, obtain the position variance under the positioning mode, and use the adaptive weighting method to fuse the three-dimensional position information under various positioning modes to obtain the optimal positioning result at a certain location.

[0039] Redundant measurement information from multi-source data can reduce the measurement error of a single data source. The adaptive weighted fusion method is based on multi-source measurement data and their corresponding characteristic standard deviations. The fusion variance is the minimum mean square error as the principle. The weighting factors of multi-source measurement data are automatically estimated, thereby making the fused measurement data result the optimal result.

[0040] Input the quality factor of the mobile station in different types of positioning modes at a certain location into the random forest classification model trained in step 4 to obtain the accuracy classification level of the different types of positioning modes at the location, and then obtain the position variance corresponding to the three-dimensional position information in different types of positioning modes at the location. p Place i The adaptive weight of the three-dimensional position information of the mobile station in this positioning mode is , the three-dimensional position information under various positioning modes is independent of each other and is an unbiased estimate of the optimal position information, then: (8) (9) In the formula, represents the mathematical expectation, Respectively indicate the location p The mobile station is i , j The three-dimensional position information under the positioning modes, N represents the number of positioning modes. is the optimal positioning result of the mobile station to be solved.

[0041] In order to make the fusion variance The value is minimized, and the Lagrange multiplier method is used to solve the extreme value of the multivariate function to obtain the minimum adaptive weights and the minimum value of the fusion variance of various positioning modes. The three-dimensional position information under various positioning modes is multiplied by the corresponding minimum adaptive weights, and the optimal positioning result of the mobile station is obtained by accumulation. , the specific calculation method is as follows: (9) (10) (11) In the formula, Indicates location p Place i The minimum adaptive weight of the positioning mode, represents the variance of the optimal positioning result, For location p Place i The position variance corresponding to the three-dimensional position information in the positioning mode.

[0042] The adaptive weighted method can realize the flexible integration of various types of Beidou positioning methods, improve the availability, reliability and positioning accuracy of Beidou positioning, and expand the comprehensive application of Beidou.

[0043] Example 2 Based on the same inventive concept, the present invention also provides a global post-processing positioning system based on various types of Beidou enhanced services, including a processor and a memory, the memory is used to store program instructions, and the processor is used to call the program instructions in the memory to execute a global post-processing positioning method based on various types of Beidou enhanced services as described above.

[0044] Example 3 Based on the same inventive concept, the present invention also provides a global post-processing positioning system based on various types of Beidou enhanced services, including a readable storage medium, on which a computer program is stored. When the computer program is executed, a global post-processing positioning method based on various types of Beidou enhanced services as described above is implemented.

[0045] In specific implementation, the method proposed in the technical solution of the present invention can be implemented by technical personnel in this field using computer software technology to realize automatic operation process. System devices for implementing the method, such as computer-readable storage media storing the corresponding computer program of the technical solution of the present invention and computer equipment running the corresponding computer program, should also be within the scope of protection of the present invention.

[0046] The specific embodiments described herein are merely examples of the spirit of the present invention. Those skilled in the art may make various modifications or additions to the specific implementation cases described, or replace them with similar methods, without departing from the spirit of the present invention or exceeding the scope defined by the appended claims.

Claims

1. A global post-processing positioning method based on various types of Beidou enhanced services, characterized in that: The following steps are involved: Step 1, using multiple positioning modes based on the BeiDou system to obtain the three-dimensional position information of the mobile station at different positions, calculating and recording the quality factors under various positioning modes at different positions, and using reference equipment based on the BeiDou system to obtain the high-precision three-dimensional position of the mobile station at different positions; Step 2, using the three-dimensional position information and quality factor of the mobile station at different positions in multiple positioning modes obtained in step 1, and the high-precision three-dimensional position of the mobile station at different positions obtained by the reference equipment to perform classification training on the random forest model to obtain a trained random forest classification model; Step 3: Input the quality factors of the mobile station in multiple positioning modes at a certain location into the random forest classification model trained in step 2 to obtain the position variance in multiple positioning modes. Use the adaptive weighting method to fuse the three-dimensional position information in various positioning modes to obtain the optimal positioning result at a certain location.

2. A global post-processing positioning method based on various types of Beidou enhanced services as claimed in claim 1, characterized in that: The positioning modes in step 1 include real-time positioning and post-processing positioning. Real-time positioning includes three modes: pseudo-range single-point positioning, satellite-based precise single-point positioning and ground-based enhanced positioning. Post-processing positioning includes two modes: post-differential positioning and post-precision single-point positioning. The quality factors of the three modes of pseudo-range single-point positioning, satellite-based precise single-point positioning and ground-based enhanced positioning include the number of satellites used, standard deviation of position error, positioning solution mode, differential delay and precision factor. The quality factor of the post-differential positioning mode includes the number of satellites used, standard deviation of position error, positioning solution mode, precision factor, signal-to-noise ratio, baseline length, observation data integrity, multipath error estimate, carrier phase noise and ambiguity fixed check ratio. The quality factor of the post-precision single-point positioning mode includes the number of satellites used, standard deviation of position error, positioning solution mode, precision factor, signal-to-noise ratio, observation data integrity, multipath error estimate, carrier phase noise and ambiguity fixed check ratio.

3. A global post-processing positioning method based on various types of Beidou enhanced services as claimed in claim 2, characterized in that: The number of satellites used in step 1 is the total number of satellites involved in the positioning solution; the standard deviation of the position error is the measurement error of the latitude, longitude, and altitude positioning solution. If the least squares positioning solution is used, the least square residual is used to represent the measurement error. If the Kalman filter positioning solution is used, the position state variance is used to represent the measurement error. The positioning solution mode of the pseudo-range single-point positioning mode is the pseudo-range single-point positioning mode; the positioning solution modes of satellite-based precise single-point positioning include the pseudo-range single-point positioning mode, the fixed solution mode of satellite-based precise single-point positioning, and the floating-point solution mode of satellite-based precise single-point positioning; the positioning solution mode of ground-based enhanced positioning is the pseudo-range single-point positioning mode. The modes include pseudorange single point positioning mode, ground-based enhanced positioning pseudorange difference mode, ground-based enhanced positioning fixed solution mode and ground-based enhanced positioning floating point solution mode; the positioning solution modes of the post-differential positioning mode include post-pseudorange single point positioning mode, post-differential positioning pseudorange difference mode, post-differential positioning fixed solution mode and post-differential positioning floating point solution mode; the positioning solution modes of the post-precision single point positioning mode include post-pseudorange single point positioning mode, post-precision single point positioning fixed solution mode and post-precision single point positioning floating point solution mode; the differential delay is the difference between the time of the differential correction number used and the time of the current observation value.

4. A global post-processing positioning method based on various types of Beidou enhanced services as claimed in claim 2, characterized in that: The precision factor in step 1 is calculated from the horizontal precision factor, elevation precision factor, and time precision factor. The calculation formula is: （1） Where GDOP represents the Dilution of Precision, HDOP represents the Horizontal Dilution of Precision, VDOP represents the Vertical Dilution of Precision, and TDOP represents the Temporal Dilution of Precision. The signal-to-noise ratio is the ratio of the carrier signal power to the noise power spectral density; the baseline length is the relative distance calculated based on the known coordinates of the base station and the resolved mobile station coordinates.

5. A global post-processing positioning method based on various types of Beidou enhanced services as claimed in claim 2, characterized in that: The observation data integrity in step 1 includes the single frequency observation data integrity rate and single system observation data completeness rate , calculated by the following formula: （2） （3） In the formula, represents the completeness rate of single-frequency observation data, n represents the number of satellites observed during the observation period, represents the total number of actual observation epochs of the jth satellite at a certain frequency point during the observation period, represents the total number of theoretical epochs of the jth satellite at a certain frequency point during the observation period, represents the completeness rate of single system observation data, It indicates the number of epochs during the observation period when all the frequencies of the jth satellite have valid observation data. represents the total number of theoretical epochs of the jth satellite during the observation period; Multipath Error Estimate Calculated using the following formula: （4） In the formula, Indicates that the satellite is observed Multipath error estimate in frequency, represents the number of epochs of the sliding window, Indicates the epoch Satellites were observed The amount of calculation that includes multipath error and integer ambiguity information on frequency.

6. A global post-processing positioning method based on various types of Beidou enhanced services as claimed in claim 2, characterized in that: Carrier phase noise in step 1 Calculated using the following formula: （5） In the formula, It indicates the number of cubic differences of the satellite carrier phase observations at adjacent epochs at a certain frequency point. Indicates the epoch The satellite phase observation at a certain frequency is observed. It represents the group difference of the secondary difference of the carrier phase observations of adjacent epochs at a certain frequency point; The fuzzy fixed check ratio is calculated using the following formula: （6） In the formula, ratio represents the fuzzy fixed check ratio, represents the sub-minimum residual sum of squares in the fixed solution, represents the minimum residual sum of squares among the stationary solutions.

7. A global post-processing positioning method based on various types of Beidou enhanced services as claimed in claim 1, characterized in that: In step 2, the three-dimensional position of the mobile station at different positions in the various positioning modes obtained in step 1 is subtracted from the high-precision three-dimensional position obtained at the position using the reference equipment to obtain multiple position deviations. The position deviations are divided according to the set accuracy classification level to obtain the corresponding position variance. The classification rules are as follows: （7） In the formula, Indicates location p Place i The position variance of the mobile station in the positioning mode is Indicates location p Place i The difference between the three-dimensional position of the mobile station and the high-precision three-dimensional position obtained by the reference equipment in this positioning mode, , , , , are the set position deviation thresholds, n is the number of precision classification levels set; The quality factors of the mobile station in various positioning modes at different locations obtained in step 1 and the accuracy classification levels corresponding to the position deviations of the mobile station in various positioning modes at different locations obtained in step 1 are input into the random forest model to train the random forest classifier. At the same time, the classification accuracy of the random forest classifier is evaluated using the five-fold cross-validation method.

8. A global post-processing positioning method based on various types of Beidou enhanced services as claimed in claim 1, characterized in that: In step 3, the quality factor of the mobile station in different types of positioning modes at a certain position is input into the random forest classification model trained in step 2 to obtain the accuracy classification level of the different types of positioning modes at the position, and then obtain the position variance corresponding to the three-dimensional position information in different types of positioning modes at the position; assuming that at the position p Place i The adaptive weight of the three-dimensional position information of the mobile station in this positioning mode is , the three-dimensional position information under various positioning modes is independent of each other and is an unbiased estimate of the optimal position information, then: （8） （9） In the formula, represents the mathematical expectation, Respectively indicate the location p The mobile station is i , j The three-dimensional position information under the positioning mode, N represents the number of positioning modes. is the optimal positioning result of the mobile station to be solved; In order to make the fusion variance The value is minimized, and the Lagrange multiplier method is used to solve the extreme value of the multivariate function to obtain the minimum adaptive weights and the minimum value of the fusion variance of various positioning modes. The three-dimensional position information under various positioning modes is multiplied by the corresponding minimum adaptive weights, and the optimal positioning result of the mobile station is obtained by accumulation. , the specific calculation method is as follows: （10） （11） （12） In the formula, Indicates location p Place i The minimum adaptive weight of the positioning mode, represents the variance of the optimal positioning result, For location p Place i The position variance corresponding to the three-dimensional position information in the positioning mode.

9. A global post-processing positioning system based on various types of Beidou enhanced services, characterized in that: It includes a processor and a memory, the memory is used to store program instructions, and the processor is used to call the program instructions in the memory to execute a global post-processing positioning method based on various types of Beidou enhanced services as described in any one of claims 1-8.

10. A global post-processing positioning system based on various types of Beidou enhanced services, characterized in that: It includes a readable storage medium, on which a computer program is stored. When the computer program is executed, a global post-processing positioning method based on various types of Beidou enhanced services as described in any one of claims 1 to 8 is implemented.

Images