CN119689532B - Global post-processing positioning method and system based on various types of Beidou enhanced services - Google Patents
Global post-processing positioning method and system based on various types of Beidou enhanced services Download PDFInfo
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Abstract
The invention discloses a global post-processing positioning method based on Beidou various types of enhancement services, which comprises the steps of acquiring three-dimensional position information of a mobile station at different positions by using various positioning modes, calculating quality factors of the mobile station at different positions in various positioning modes, acquiring high-precision three-dimensional positions of the mobile station at different positions by using reference equipment, classifying and training a random forest model by using the three-dimensional position information and the quality factors of the mobile station at different positions in various positioning modes and the high-precision three-dimensional positions acquired by the reference equipment, inputting the quality factors of the mobile station at a certain position in the various positioning modes into the trained random forest classification model to obtain position variances of the mobile station at various positioning modes, and fusing the three-dimensional position information of the mobile station at various positioning modes by using self-adaptive weighting to obtain optimal position information. According to the invention, different types of positioning results are fused, and the availability, reliability and positioning accuracy of Beidou positioning are improved.
Description
Technical Field
The invention belongs to the technical field of satellite navigation positioning, and particularly relates to a global post-processing positioning method and system based on Beidou various types of enhancement services.
Background
The Beidou satellite navigation system (Beidou system for short) is built and developed according to a three-step strategy. The Beidou I system is put into use in 2000, and adopts an active positioning system to provide pseudo-range single-point positioning, time service, wide area difference and short message communication service for Chinese users. The Beidou No. two system is put into use in 2012, and a passive positioning system is added on the basis of being compatible with the Beidou No. one system technical system, so that positioning, speed measurement, time service and short message communication service are provided for users in the asia-Tai area. The Beidou No. three system 2020 is put into use, and on the basis of the Beidou No. two system, the performance and the expansion function are further improved, and various services are provided, including global-oriented positioning navigation time service, global short message communication and international search and rescue service, satellite-based enhancement, satellite-based precise single-point positioning, foundation enhancement and regional short message communication service are provided in China and peripheral areas, and post differential positioning and post precise single-point positioning service are supported.
The pseudo-range single-point positioning (Single Point Positioning, SPP) is a mode for realizing positioning by using pseudo-range observation values and broadcast ephemeris of the Beidou system, and is a basic service provided by the Beidou system. The coverage range of the system is global, the positioning accuracy is within 5m, the system can be obtained in real time and calculated afterwards, and the positioning convergence time is 10 seconds.
The satellite-based precise single point positioning (Precise Point Positioning, PPP) is realized by using the Beidou system GEO satellite to broadcast PPP-B2B satellite-based differential correction, integrity information and other information, and dual-frequency observation value enhancement service is provided for users in China and peripheral areas. The coverage range of the system is China and surrounding areas, the positioning accuracy is within 0.4m, the system can be obtained in real time, and the positioning convergence time is 20 minutes.
The foundation enhancement positioning is based on a network RTK (Real Time Kinematic) positioning technology, and is characterized in that a data processing center processes synchronous observation data of a plurality of Beidou system reference stations covered in a certain range, differential data are generated, the differential data are broadcast through mobile communication or the Internet, and users in the area receive satellite signals and differential signals, so that high-precision real-time dynamic positioning is realized. The coverage area is the area covered by mobile communication in China and surrounding areas, the positioning accuracy is within 0.05m, the positioning accuracy can be obtained in real time, and the positioning convergence time is 30 seconds.
The post differential positioning (Post Process Kinematic, PPK) is that a user uses multi-frequency pseudo-range and carrier phase data synchronously observed by a single Beidou system reference station and a mobile station to carry out double-difference ionosphere-free combination to weaken the influence of atmospheric errors, thereby realizing high-precision post processing positioning. The coverage range of the system is 20km range with a single Beidou reference station as the center, the positioning accuracy is 0.02m+1ppm multiplied by distance kilometers, the system can be calculated afterwards, and no positioning convergence time exists.
The post-precision single point positioning (PPP, precise Point Positioning) is a high-precision post-processing positioning mode realized by correcting a series of precision error correction models by using a non-differential non-combination observation model which is carried out by a user by utilizing the multi-frequency pseudo-range and carrier phase observation value of a Beidou system mobile station and the simultaneous IGS precision ephemeris and precision satellite clock difference. The coverage range of the method is global, the positioning accuracy is within 0.2m, the method can be solved afterwards, and the positioning convergence time is not needed.
Based on pseudo-range single-point positioning, satellite-based precise single-point positioning, foundation enhanced positioning, post differential positioning and post precise single-point positioning, the Beidou system can provide enhanced services and positioning capabilities of meter-level, decimeter-level, centimeter-level and other types. However, as coverage ranges, positioning accuracy, convergence time and external dependence conditions of different types of enhanced services are different, how to make a flexible fusion strategy, the best comprehensive position information is obtained by taking the advantages and the advantages of the best comprehensive position information, and the availability, reliability and accuracy of Beidou positioning service are improved.
Disclosure of Invention
Aiming at the problems of insufficient availability, reliability and precision of Beidou positioning service caused by the difference of the existing positioning technology, the invention provides a global post-processing positioning method based on Beidou various types of enhancement services. The method has strong practicability and high flexibility, improves the availability, reliability and positioning accuracy of Beidou positioning, and can be widely applied to the field of Beidou navigation and positioning.
In order to achieve the above purpose, the technical scheme provided by the invention is a global post-processing positioning method based on Beidou various types of enhancement services, which comprises the following steps:
Step 1, acquiring three-dimensional position information of a mobile station at different positions by using multiple positioning modes based on a Beidou system, calculating and recording quality factors of the mobile station at the different positions in various positioning modes, and acquiring high-precision three-dimensional positions of the mobile station at the different positions by using reference equipment based on the Beidou system;
Step2, classifying and training the random forest model by using the three-dimensional position information and quality factors of the mobile station obtained in the step1 under a plurality of positioning modes at different positions and the high-precision three-dimensional positions of the mobile station at different positions obtained by the reference equipment to obtain a trained random forest classification model;
And 3, inputting quality factors of the mobile station in a certain position in a plurality of positioning modes into the random forest classification model trained in the step 2 to obtain position variances in the plurality of positioning modes, and fusing three-dimensional position information in the plurality of positioning modes by using an adaptive weighting method to obtain an optimal positioning result in the certain position.
Further, the positioning modes in the step 1 include two types of real-time positioning and post-processing positioning, wherein the real-time positioning includes three modes of pseudo-range single-point positioning, satellite-based precise single-point positioning and foundation enhancement positioning, and the post-processing positioning includes two modes of post-differential positioning and post-precise single-point positioning. The quality factors of the pseudo-range single-point positioning mode, the satellite-based precise single-point positioning mode and the foundation enhanced positioning mode comprise satellite quantity, position error standard deviation, a positioning resolving mode, differential time delay and precision factors. The quality factors of the post differential positioning mode include the use of satellite particles, standard deviation of position error, positioning solution mode, precision factor, signal to noise ratio, baseline length, observed data integrity, multipath error estimate, carrier phase noise and fixed check ratio of ambiguity. The quality factors of the post-precise single-point positioning mode include the use of satellite numbers, standard deviation of position errors, positioning solution mode, precision factors, signal to noise ratio, observed data integrity, multipath error estimates, carrier phase noise and fixed check ratio of ambiguity.
Further, in the step 2, the three-dimensional positions of the mobile station at different positions in the plurality of positioning modes obtained in the step 1 and the high-precision three-dimensional positions obtained by using the reference device at the positions are subjected to difference to obtain a plurality of position deviations, the position deviations are classified according to the set precision classification grades, the corresponding position variances are obtained, and the grading rule is as follows:
(7)
In the formula, Representing the variance of the position of the rover station in the ith position mode at position p,Representing the difference between the three-dimensional position of the rover station in the ith position mode at position p and the high-accuracy three-dimensional position obtained by the reference apparatus,、、、、All are set position deviation thresholds, and n is the set precision classification grade number.
Inputting the quality factors of the mobile station in the various positioning modes at different positions obtained in the step 1 and the calculated precision classification grades corresponding to the position deviations of the mobile station in the various positioning modes at different positions into a random forest model, training the random forest classifier, and evaluating the classification accuracy of the random forest classifier by using a five-fold cross validation method.
Further, in the step3, 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 the step 2 to obtain the precision classification level of the mobile station in different types of positioning modes at the position, and further obtain the position variance corresponding to the three-dimensional position information in various positioning modes at the position, wherein the self-adaptive weight of the three-dimensional position information of the mobile station in the ith positioning mode at the position p is assumed to beThree-dimensional position information in various positioning modes are independent of each other and are unbiased estimates of optimal position information, then:
(8)
(9)
In the formula, Representing the mathematical expectation that the data will be,Three-dimensional position information of the mobile station in the ith and jth positioning modes at the position p is respectively represented, N represents the number of types of positioning modes,An optimal positioning result of the mobile station to be solved;
In order to fuse variances The minimum value is obtained by carrying out multi-element function extremum calculation through Lagrangian multiplier method, the minimum self-adaptive weight value of different kinds of positioning modes and the minimum value of fusion variance are obtained, the three-dimensional position information under various positioning modes and the minimum self-adaptive weight value corresponding to the three-dimensional position information are multiplied, and the optimal positioning result of the mobile station is obtained through accumulationThe specific calculation mode is as follows:
(10)
(11)
(12)
In the formula, The minimum adaptive weight representing the ith positioning pattern at position p,The variance of the optimal positioning result is represented,The position variance corresponding to the three-dimensional position information in the ith positioning mode at the position p.
The invention also provides a global post-processing positioning system based on the Beidou various types of enhancement services, which is used for realizing the global post-processing positioning method based on the Beidou various types of enhancement services.
And the system comprises a processor and a memory, wherein the memory is used for storing program instructions, and the processor is used for calling the stored instructions in the memory to execute the global post-processing positioning method based on the Beidou various types of enhancement services.
Or comprises a readable storage medium, wherein the readable storage medium is stored with a computer program, and the computer program realizes the global post-processing positioning method based on the Beidou various types of enhancement services when being executed.
Compared with the prior art, the invention has the following advantages:
1) Aiming at pseudo-range single-point positioning, star-based precise single-point positioning, foundation-enhanced three-dimensional position information and precise single-point positioning and differential positioning three-dimensional position information obtained by post-processing, the application range, positioning precision, convergence time and the like of various positioning modes are comprehensively analyzed, precision classification is carried out by machine learning according to the three-dimensional position information of various types and quality factors thereof, and optimal comprehensive three-dimensional position information is obtained according to self-adaptive weighted fusion.
2) The method can realize flexible fusion and comprehensive application of different types of positioning modes, improves the availability, reliability and positioning precision of Beidou positioning, and can be widely applied to the fields of Beidou navigation positioning such as land measurement, aviation mapping, ocean navigation surveying and the like.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a global post-processing positioning method based on Beidou various types of enhanced services according to an embodiment of the present invention.
FIG. 2 is a diagram of a random forest classification modeling process according to an embodiment of the invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings and examples of the present invention, and it is apparent that the described examples are some, but not all, examples of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
As shown in fig. 1, the embodiment of the invention provides a global post-processing positioning method based on Beidou various types of enhancement services, which comprises the following steps:
Step 1, based on different real-time positioning modes (pseudo-range single-point positioning, satellite-based precise single-point positioning and foundation enhancement positioning) set by a Beidou system according to a mobile station receiver, three-dimensional position information and quality factors of the mobile station at different positions in different modes are obtained in real time, and meanwhile, based on the Beidou system, high-precision three-dimensional positions of the mobile station at different positions are obtained by using reference equipment.
The quality factors include the number of satellites used, standard deviation of position errors, positioning solution mode, differential time delay, precision factors, etc. The satellite number is used as the total number of satellites participating in the positioning calculation. The standard deviation of the position error is the measurement error of latitude, longitude and altitude positioning solution, if the least square positioning solution is used, the measurement error is represented by the least square residual error, and if the Kalman filtering positioning solution is used, the measurement error is represented by the position state variance. The positioning resolving mode of the pseudo-range single-point positioning mode is a pseudo-range single-point positioning mode. The positioning resolving mode of the star-based precise single-point positioning comprises a pseudo-range single-point positioning mode, a fixed solution mode of the star-based precise single-point positioning and a floating solution mode of the star-based precise single-point positioning. The positioning resolving mode of the foundation enhanced positioning comprises a pseudo-range single-point positioning mode, a foundation enhanced positioning pseudo-range differential mode, a fixed solution mode of the foundation enhanced positioning and a floating solution mode of the foundation enhanced positioning. The differential time delay is the difference between the differential correction time used and the current observation time. The precision factor is calculated by a horizontal precision factor, an elevation precision factor and a time precision factor, and the calculation formula is as follows:
(1)
In the formula, GDOP represents a precision factor, HDOP represents a horizontal precision factor, VDOP represents an elevation precision factor, and TDOP represents a time precision factor.
And 2, when the coverage range of the erected reference station comprises the position of the mobile station, performing post PPK calculation according to the acquired original observation values of the reference station and the Beidou system of the mobile station to obtain three-dimensional position information and quality factors of the mobile station at different positions, and acquiring high-precision three-dimensional positions of the mobile station at different positions by using reference equipment.
The quality factors include the number of satellites used, standard deviation of position error, positioning solution mode, accuracy factor, signal to noise ratio, baseline length, observed data integrity, multipath error estimate, carrier phase noise, fixed ambiguity rate, etc. The satellite number is used as the total number of satellites participating in the positioning calculation. The standard deviation of the position error is the measurement error of latitude, longitude and altitude positioning solution, if the least square positioning solution is used, the measurement error is represented by the least square residual error, and if the Kalman filtering positioning solution is used, the measurement error is represented by the position state variance. The positioning resolving mode of the post differential positioning mode comprises a post pseudo-range single-point positioning mode, a post differential positioning pseudo-range differential mode, a post differential positioning fixed solution mode and a post differential positioning floating solution mode. The precision factor is calculated by a horizontal precision factor, an elevation precision factor and a time precision factor, and the calculation mode is the same as the formula (1). 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 from the known reference station coordinates and the resolved rover coordinates.
The integrity of the observed data comprises the integrity rate of the observed data of the single frequency pointAnd single system observation data integrity rateThe calculation is performed by the following formula:
(2)
(3)
In the formula, Represents the complete rate of single-frequency point observation data, n represents the number of satellites observed in an observation period,Representing the actual total number of observation epochs of the jth satellite at a certain frequency point in the observation period,Represents the theoretical total number of epochs of the jth satellite at a certain frequency point in the observation period,Representing the overall rate of observed data for a single system,The epoch number representing valid observation data for all frequency points of the jth satellite during the observation period,Representing the theoretical total number of epochs for the j-th satellite during the observation period.
Multipath error estimationThe calculation is performed by the following formula:
(4)
In the formula, Indicating that satellite is observedThe multipath error estimate over the frequency is determined,The number of epochs representing the sliding window,Expressed in calendar elementObserve satellite presenceThe frequency includes the amount of calculation of the multipath error and the integer ambiguity information.
Carrier phase noiseThe calculation is performed by the following formula:
(5)
In the formula, The number of three differences of the observed quantity of the carrier phases of the adjacent epochs of the satellite at a certain frequency point is shown,Expressed in calendar elementThe observed quantity of the phase carrier phase of the satellite at a certain frequency point is observed,And the group difference value (third difference value) representing the second difference value of the carrier phase observed quantity of the adjacent epoch of a certain frequency point.
The fixed ambiguity resolution ratio is calculated using the following formula:
(6)
Where ratio represents the fixed check ratio of ambiguity, Representing the sum of squares of the next smallest residuals in the fixed solution,Representing the sum of squares of the smallest residuals in the fixed solution.
And 3, performing post PPP calculation according to the acquired original observation value of the Beidou system of the mobile station, the precise satellite ephemeris, the clock error file and the correction to acquire three-dimensional position information and quality factors of the mobile station at different positions, and acquiring high-precision three-dimensional positions of the mobile station at different positions by using reference equipment by the Beidou system.
The quality factors include the number of satellites used, standard deviation of position error, positioning solution mode, accuracy factor, signal to noise ratio, observed data integrity, multipath error estimate, carrier phase noise, fixed check ratio of ambiguity, etc. The satellite number is used as the total number of satellites participating in the positioning calculation. The standard deviation of the position error is the measurement error of latitude, longitude and altitude positioning solution, if the least square positioning solution is used, the measurement error is represented by the least square residual error, and if the Kalman filtering positioning solution is used, the measurement error is represented by the position state variance. The positioning resolving mode of the post-precision single-point positioning mode comprises a post-pseudo-range single-point positioning mode, a post-precision single-point positioning fixed solution mode and a post-precision single-point positioning floating solution mode. The precision factor is calculated by a horizontal precision factor, an elevation precision factor and a time precision factor, and the calculation mode is the same as the 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 is the same as in equation (4). The carrier phase noise calculation method is the same as the formula (5). The fuzzy degree fixed check ratio evaluation mode is the same as the formula (6).
And 4, classifying and training the random forest model by using the three-dimensional position information and quality factors of the mobile station in the different positions in a plurality of positioning modes obtained in the step 1-step 3 and the high-precision three-dimensional positions of the mobile station in the different positions obtained by the reference equipment to obtain a trained random forest classification model.
And (3) carrying out difference between three-dimensional position information of the five positioning modes (pseudo-range single-point positioning, satellite-based precise single-point positioning, foundation enhancement positioning, post differential positioning and post precise single-point positioning) obtained in the steps (1) to (3) and the high-precision three-dimensional position obtained by the reference equipment to obtain a plurality of position deviations. The position deviation is classified into 8 precision classification classes according to the precision class classification table set in table 1, wherein the precision classification class of class 1 is highest, the precision classification class of class 8 is lowest, and each precision classification class has a corresponding position variance.
TABLE 1 precision class Classification List
The random forest is a supervised machine learning integration algorithm taking the decision tree as a base learner, and attribute random selection is added in the decision tree construction process, so that the problem of over-fitting can be effectively solved, and the anti-noise performance is improved. The random forest classification method is characterized in that when a plurality of decision trees are constructed, characteristic variables and labeled samples of a training data set are randomly sampled, a decision tree is obtained by sampling results each time, and decision rules and classification results which accord with the attribute of the random forest classification algorithm can be generated by each tree, and the random forest classification algorithm is realized by integrating the decision rules and the classification results of all the trees.
And (3) inputting the quality factors of the mobile station in the various positioning modes at different positions obtained in the steps (1) to (3) and the calculated precision classification grades corresponding to the position deviations of the mobile station in the various positioning modes at different positions into a random forest model, and training the random forest classifier. Meanwhile, the accuracy of classification of the random forest classifier is evaluated by using a five-fold cross validation method, namely, five-fold repeated wheel flows are used for model training by using four equal parts of data, and the classification accuracy of the random forest classifier is tested by using one part of data, as shown in figure 2, so that the accuracy of the overall random forest classification model is improved.
And 5, inputting quality factors of the mobile station in a plurality of positioning modes at a certain position into the random forest classification model trained in the step 4 to obtain the position variance in the various positioning modes, and fusing the three-dimensional position information in the various positioning modes by using an adaptive weighting method to obtain an optimal positioning result at the certain position.
The redundant measurement information of the multi-source data can reduce the measurement error of a single data source, and the self-adaptive weighted fusion method is based on the multi-source measurement data and the corresponding characteristic standard deviation thereof, and takes the fusion variance as the principle of minimum mean square error, the weighting factors of the multi-source measurement data are automatically estimated and obtained, so that the fusion measurement data result is the optimal result.
And (3) inputting quality factors of the mobile station in different types of positioning modes at a certain position into the random forest classification model trained in the step (4) to obtain precision classification grades of the position in the different types of positioning modes, and further obtaining position variances corresponding to three-dimensional position information in the different types of positioning modes at the position. Assume that the adaptive weight of three-dimensional position information of the mobile station in the ith positioning mode at position p isThree-dimensional position information in various positioning modes are independent of each other and are unbiased estimates of optimal position information, then:
(8)
(9)
In the formula, Representing the mathematical expectation that the data will be,Three-dimensional position information of the mobile station in the ith and jth positioning modes at the position p is respectively represented, N represents the number of types of positioning modes,And (5) obtaining an optimal positioning result of the mobile station to be solved.
In order to fuse variancesThe minimum value is obtained by carrying out multi-element function extremum calculation through Lagrangian multiplier method, the minimum self-adaptive weight value of various positioning modes and the minimum value of fusion variance are obtained, the three-dimensional position information under various positioning modes and the corresponding minimum self-adaptive weight value are multiplied, and the optimal positioning result of the mobile station is obtained by accumulationThe specific calculation mode is as follows:
(9)
(10)
(11)
In the formula, The minimum adaptive weight representing the ith positioning pattern at position p,The variance of the optimal positioning result is represented,The position variance corresponding to the three-dimensional position information in the ith positioning mode at the position p.
The method can realize flexible fusion of various Beidou positioning modes by utilizing the self-adaptive weighting method, improves the availability, reliability and positioning precision of Beidou positioning, and expands the comprehensive application of Beidou.
Example 2
Based on the same inventive concept, the invention also provides a global post-processing positioning system based on the Beidou various types of enhancement services, which comprises a processor and a memory, wherein the memory is used for storing program instructions, and the processor is used for calling the program instructions in the memory to execute the global post-processing positioning method based on the Beidou various types of enhancement services.
Example 3
Based on the same inventive concept, the invention also provides a global post-processing positioning system based on the Beidou various types of enhancement services, which comprises a readable storage medium, wherein a computer program is stored on the readable storage medium, and the global post-processing positioning method based on the Beidou various types of enhancement services is realized when the computer program is executed.
In particular, the method according to the technical solution of the present invention may be implemented by those skilled in the art using computer software technology to implement an automatic operation flow, and a system apparatus for implementing the method, such as a computer readable storage medium storing a corresponding computer program according to the technical solution of the present invention, and a computer device including the operation of the corresponding computer program, should also fall within the protection scope of the present invention.
The specific embodiments described herein are offered by way of example only to illustrate the spirit of the invention. Those skilled in the art may make various modifications or additions to the described embodiments or substitutions thereof without departing from the spirit of the invention or exceeding the scope of the invention as defined in the accompanying claims.
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