CN115755131A - Satellite positioning method, device and medium - Google Patents
Satellite positioning method, device and medium Download PDFInfo
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Abstract
The invention discloses a method, a device and a medium for satellite positioning, which are suitable for the technical field of positioning and navigation. Calling a predictive protection level correction model to input attribute information; acquiring an output parameter of a prediction protection level correction model as a correction coefficient; correcting the theoretical protection level according to the correction coefficient to obtain a corrected protection level; and analyzing the positioning result of the satellite positioning according to the corrected protection level to obtain an analysis result. By introducing data drive (attribute information), the attribute information is based on actual running actual data, the relation of positioning errors obtained by PPP-RTK positioning of service information and observation information is mined, the prediction of a protection level correction coefficient is realized, the protection level is corrected, the corrected protection level positions a satellite, the probability of dangerous events is reduced, and the reliability of the protection level in a complex environment is improved.
Description
Technical Field
The present invention relates to the field of positioning and navigation technologies, and in particular, to a method, an apparatus, and a medium for satellite positioning.
Background
The Global Navigation Satellite System (GNSS) has a wide application prospect in high-precision positioning. Compared with the traditional precision Point Positioning technology (PPP), the PPP-RTK technology can greatly shorten the convergence time and realize quick ambiguity fixing. Meanwhile, compared with a Real Time Kinematic (RTK) technology, the PPP-RTK technology needs fewer base stations and has higher service reliability. Therefore, PPP-RTK is expected to be widely applied in the fields of automatic driving and the like. In order to realize the application of the PPP-RTK in the fields of automatic driving and the like, integrity monitoring needs to be carried out on a PPP-RTK user side, and position error upper bound information under acceptable risks, namely the protection level, is output to a user.
The existing PPP-RTK technology is mainly researched in the directions of realizing a system, improving positioning precision, improving ambiguity fixing rate and the like, and the PPP-RTK integrity monitoring is less researched. However, for life safety related applications such as autonomous driving, integrity is a crucial performance indicator. Integrity refers to the ability to provide an alert to a user in a timely manner when the navigation system is not available, which reflects the degree of confidence in the correctness of the navigation information provided by the navigation system. In particular, the unavailability of navigation systems is often due to faults in the measurements or product information involved in the positioning. However, in actual operation, the receiver is subject to interference such as multipath and non-direct signal, and the probability that the actual positioning error exceeds the protection level derived by theory is far higher than the theoretical value, so that the user is exposed to risks.
Therefore, how to implement the correction of the protection level to improve the integrity monitoring of the positioning system is a urgent need to be solved by those skilled in the art.
Disclosure of Invention
The invention aims to provide a satellite positioning method, a satellite positioning device and a satellite positioning medium, which are used for correcting a protection level, reducing the probability of dangerous events and improving the reliability of the protection level in a complex environment.
In order to solve the above technical problem, the present invention provides a method for satellite positioning, comprising:
calling a prediction protection level correction model to input attribute information, wherein the attribute information is obtained by PPP-RTK positioning through PPP-RTK service information and observation information of a receiver;
acquiring an output parameter of the prediction protection level correction model as a correction coefficient;
correcting a theoretical protection level according to the correction coefficient to obtain a corrected protection level, wherein the theoretical protection level is obtained based on a theoretical model;
and analyzing the positioning result of the satellite positioning according to the corrected protection level to obtain an analysis result.
Preferably, the PPP-RTK service information at least includes orbit information, clock error information, bias information and atmospheric information of GNSS satellites;
the observation information at least comprises pseudo-range information and carrier observation information of the receiver;
the attribute information at least comprises the quantity information of visible satellites, carrier-to-noise ratio information, residual error information, ambiguity fixed state information and ambiguity fixed quantity information.
Preferably, the process for establishing the prediction protection level correction model specifically includes:
acquiring sample service information, sample observation information and reference track information stored in a database;
PPP-RTK positioning is carried out according to the sample service information and the sample observation information to obtain off-line positioning information and off-line attribute information;
processing according to the offline positioning information and the reference track information to obtain positioning error information;
determining an off-line correction coefficient according to the relation between the theoretical protection level and the positioning error information;
and training the offline correction coefficient and the offline attribute information through a machine learning algorithm to obtain the prediction protection level correction model.
Preferably, the determining an offline correction coefficient according to the relationship between the theoretical protection level and the positioning error information includes:
and setting the offline correction coefficient under the condition that the positioning error information is not completely enveloped by the theoretical protection level or the positioning error information is completely enveloped by the theoretical protection level, and the difference value between the theoretical protection level and the positioning error information is less than a threshold value.
Preferably, the theoretical protection level is obtained by a fault-free protection level formula or a multiple solution split protection level formula.
Preferably, the obtaining the sample service information and the sample observation information includes:
building a PPP-RTK acquisition system;
performing drive test according to different scenes to record the sample service information and the sample observation information;
correspondingly, acquiring the reference track information stored in the database includes:
building a truth value reference system;
and obtaining the reference track information according to post-processing software.
Preferably, after obtaining the corrected protection level, the method further includes:
and outputting prompt information for prompting the staff.
In order to solve the above technical problem, the present invention further provides a satellite positioning apparatus, including:
the calling module is used for calling the prediction protection level correction model to input attribute information, wherein the attribute information is obtained by PPP-RTK positioning through PPP-RTK service information and observation information of a receiver;
the acquisition module is used for acquiring the output parameters of the prediction protection level correction model as correction coefficients;
the correction module is used for correcting a theoretical protection level according to the correction coefficient to obtain a corrected protection level, wherein the theoretical protection level is obtained based on a theoretical model;
and the analysis module is used for analyzing the positioning result of the satellite positioning according to the corrected protection level to obtain an analysis result.
In order to solve the above technical problem, the present invention further provides a satellite positioning apparatus, including:
a memory for storing a computer program;
a processor for implementing the steps of the method for satellite based positioning as described above when executing the computer program.
To solve the above technical problem, the present invention further provides a computer-readable storage medium, having a computer program stored thereon, where the computer program is executed by a processor to implement the steps of the method for satellite positioning as described above.
The invention provides a satellite positioning method, which comprises the following steps: calling a prediction protection level correction model to input attribute information, wherein the attribute information is obtained by PPP-RTK positioning through PPP-RTK service information and observation information of a receiver; acquiring an output parameter of a prediction protection level correction model as a correction coefficient; correcting the theoretical protection level according to the correction coefficient to obtain a corrected protection level, wherein the theoretical protection level is obtained based on a theoretical model; and analyzing the positioning result of the satellite positioning according to the corrected protection level to obtain an analysis result. According to the method, data drive (attribute information) is introduced, the relationship of positioning errors obtained by PPP-RTK positioning of the attribute information based on actual running actual data and service information and observation information is mined, the protection level correction coefficient is predicted, the protection level is corrected, the corrected protection level positions a satellite, the probability of dangerous events is reduced, and the reliability of the protection level in a complex environment is improved.
In addition, the invention also provides a device and a medium for satellite positioning, which have the same beneficial effects as the method for satellite positioning.
Drawings
In order to more clearly illustrate the embodiments of the present invention, the drawings required for the embodiments will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained by those skilled in the art without inventive effort.
Fig. 1 is a flowchart of a method for satellite positioning according to an embodiment of the present invention;
FIG. 2 is a flow chart of another method for satellite positioning according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of machine learning training according to an embodiment of the present disclosure;
FIG. 4 is a diagram illustrating a machine learning prediction process according to an embodiment of the present invention;
fig. 5 is a block diagram of a satellite positioning apparatus according to an embodiment of the present invention;
fig. 6 is a block diagram of another satellite positioning apparatus according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present invention without any creative work belong to the protection scope of the present invention.
The core of the invention is to provide a method, a device and a medium for satellite positioning, which are used for correcting the protection level, reducing the probability of dangerous events and improving the reliability of the protection level in a complex environment.
In order that those skilled in the art will better understand the disclosure, the invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
It should be noted that the basic principle of the PPP-RTK technique is that, at the server, the globally distributed reference stations are used to estimate and generate orbits, clock offsets and offset products of GNSS satellites in real time, and the locally distributed reference stations are used to generate local atmospheric delay information in real time; the information generated by the server is broadcasted to the user side through the Internet or a satellite link; and at the user side, position estimation is carried out by utilizing the pseudo range and carrier wave observation output by the receiver and the received service information of the service side based on state estimation methods such as Kalman filtering and the like, and ambiguity fixing is carried out to enhance the positioning precision. The integrity monitoring of the user end of the existing PPP-RTK technology mainly adopts two schemes, one scheme is based on a non-fault mode to push a protection level, and the other scheme is based on the other mode to obtain a safer protection level due to the consideration of different fault modes.
In addition, the existing measurement error model for integrity monitoring is difficult to accurately describe the actual error distribution, so that the protection level obtained by the existing PPP-RTK user side integrity monitoring method cannot safely envelop the actual positioning error. In particular, when the receiver antenna is affected by trees, buildings, etc., the actual PPP-RTK positioning error may exceed the given level of protection, thereby posing a danger to the user. In order to improve the reliability of the protection level in a complex environment and reduce the probability of the occurrence of the dangerous events, engineering correction needs to be performed on the protection level.
Fig. 1 is a flowchart of a method for positioning a satellite according to an embodiment of the present invention, as shown in fig. 1, including:
s11: calling a prediction protection level correction model to input attribute information, wherein the attribute information is obtained by PPP-RTK positioning through PPP-RTK service information and observation information of a receiver;
s12: acquiring an output parameter of a prediction protection level correction model as a correction coefficient;
s13: correcting the theoretical protection level according to the correction coefficient to obtain a corrected protection level, wherein the theoretical protection level is obtained based on a theoretical model;
s14: and analyzing the positioning result of the satellite positioning according to the corrected protection level to obtain an analysis result.
Specifically, the predicted protection level correction model is called to solve the problem that the protection level cannot completely envelop the actual positioning error in the complex challenge environment, and a machine learning-based protection level correction method is used for excavating the relationship between the attribute information and the positioning error so as to predict the protection level correction coefficient. As an embodiment, the process for establishing the prediction protection level correction model specifically includes:
acquiring sample service information, sample observation information and reference track information stored in a database;
PPP-RTK positioning is carried out according to the sample service information and the sample observation information to obtain off-line positioning information and off-line attribute information;
processing according to the offline positioning information and the reference track information to obtain positioning error information;
determining an off-line correction coefficient according to the relation between the theoretical protection level and the positioning error information;
and training the offline correction coefficient and the offline attribute information through a machine learning algorithm to obtain a prediction protection level correction model.
It can be understood that the model is established offline through sample data, and a large amount of observation data needs to be collected, that is, sample service information, sample observation information and reference trajectory information are obtained. The sample service information is mainly product information for PPP-RTK technology, such as orbit information, clock error information, and bias information of GNSS satellites. The observation information mainly comprises pseudo-range information, carrier observation information and the like output by the receiver, and the reference track information is a positioning result obtained by performing PPP-RTK positioning technology on real data which is stored in a database, and the positioning result obtained by performing positioning processing again on the real data is not needed.
And performing PPP-RTK positioning according to the sample service information and the sample observation information to obtain offline positioning information and offline attribute information, and recording the offline positioning information, namely a positioning result obtained by performing positioning processing according to offline data when performing PPP-RTK positioning technology. The off-line attribute information is process information including the number of visible satellites, signal-to-noise ratio, residual error, ambiguity fixed state, ambiguity fixed number, and the like.
And obtaining positioning error information by processing according to the offline positioning information and the reference track information, namely comparing the positioning information obtained according to the current offline information with the sample positioning information of the reference track information to obtain the positioning error information.
And determining an offline correction coefficient according to the relation between the theoretical protection level and the positioning error information, wherein the protection level calculated based on the theoretical model can not safely envelop the actual positioning error in some scenes, so that the protection level is artificially corrected based on an actual error sequence, and the correction coefficient is the offline correction coefficient. The corresponding correction process can be set according to the actual situation, and the invention is not particularly limited.
And training the offline correction coefficient and the offline attribute information through a machine learning algorithm to obtain a prediction protection level correction model of the offline correction coefficient and the offline attribute information. The invention does not set which machine learning algorithm is used, and can be based on machine learning algorithms such as a support vector machine, a neural network and the like.
And inputting the attribute information into the established prediction protection level correction model, and outputting a correction coefficient. It can be understood that the attribute information is the same as the parameters of the above-mentioned offline attribute information, and the specific data under the parameters is obtained according to the data running in real time, that is, the information obtained by PPP-RTK positioning through the PPP-RTK service information and the observation information of the receiver.
As an embodiment, the PPP-RTK service information includes at least orbit information, clock error information, bias information, and atmospheric information of the GNSS satellite;
the observation information at least comprises pseudo-range information and carrier observation information of the receiver;
the attribute information at least comprises quantity information of visible satellites, carrier-to-noise ratio information, residual information, ambiguity fixed state information and ambiguity fixed quantity information.
It is understood that the PPP-RTK service information and the observation information of the receiver may be the same as the sample service information and the sample observation information in the above embodiments, or may include parameters on the basis of the sample service information and the sample observation information, that is, at least the parameters in the above embodiments, but the data of the specific parameters is different from the sample information in the above embodiments and is obtained by actual data acquisition in real time operation.
The correction coefficient is obtained based on the recorded attribute information (visible satellite number, carrier-to-noise ratio, residual error and other process information) and a pre-trained model, and the corrected protection level is obtained by correcting the theoretical protection level after the correction coefficient is obtained. It can be understood that the theoretical protection level is obtained based on a theoretical model, and may be the same as or different from the above-mentioned calculation formula used for establishing the theoretical protection level of the predicted protection level correction model, and in order to improve the accuracy, the calculation formula used is the same.
And evaluating the positioning result of the satellite positioning according to the corrected protection level to determine the accuracy of the positioning result, namely analyzing the positioning result to obtain an analysis result.
The satellite positioning method provided by the embodiment of the invention comprises the following steps: calling a prediction protection level correction model to input attribute information, wherein the attribute information is obtained by PPP-RTK positioning through PPP-RTK service information and observation information of a receiver; acquiring an output parameter of a prediction protection level correction model as a correction coefficient; correcting the theoretical protection level according to the correction coefficient to obtain a corrected protection level, wherein the theoretical protection level is obtained based on a theoretical model; and analyzing the positioning result of the satellite positioning according to the corrected protection level to obtain an analysis result. According to the method, data drive (attribute information) is introduced, the relationship between the attribute information and positioning errors obtained by PPP-RTK positioning of service information and observation information is mined on the basis of actual data of actual operation, the prediction of a protection level correction coefficient is realized, the protection level is corrected, the corrected protection level positions a satellite, the probability of dangerous events is reduced, and the reliability of the protection level in a complex environment is improved.
On the basis of the above embodiment, determining an offline correction coefficient according to a relationship between a theoretical protection level and positioning error information includes:
and setting an offline correction coefficient under the condition that the theoretical protection level does not envelop the positioning error information or the theoretical protection level envelops the positioning error information completely, and the difference value between the theoretical protection level and the positioning error information is greater than a threshold value.
Specifically, the protection level calculated based on the theoretical model may not safely envelop actual positioning errors in some scenes, so that the corresponding protection level is manually corrected based on an actual error sequence to enable the protection level to meet two conditions, wherein one condition is that the theoretical protection level does not envelop all positioning error information; and the other is that the difference value between the theoretical protection level and the positioning error information is larger than a threshold value on the basis of the whole envelope positioning error information. And setting an off-line correction coefficient on the basis of meeting two conditions. An initial offline correction coefficient can be set and continuously input to the original established model to adjust the correction coefficient until the two preset conditions are met, so that a final offline correction coefficient is obtained.
According to the embodiment of the invention, the protection level is corrected through the set off-line correction coefficient to obtain the model for predicting the correction coefficient of the protection level by using the off-line attribute information, namely, the established model is more accurate.
On the basis of the above embodiment, as an embodiment, the theoretical protection level is obtained based on a theoretical model, and may be the same as or different from the calculation formula adopted for establishing the theoretical protection level of the predicted protection level correction model, specifically: the theoretical protection level is obtained by a fault-free protection level formula or a multi-solution separation protection level formula.
A fault-free protection level calculation formula may be utilized, the specific formula being as follows:
wherein Q is a Gaussian probability function, P HMI，q To assign a health risk to the q direction, PL q Protection level of qth direction, σ q Is the corresponding standard deviation of error.
The theoretical protection level can also be calculated by using a multi-solution separation protection level calculation formula, wherein the specific formula is as follows:
wherein, P NM Is the sum of the probabilities of the unmonitored failure modes,
is the standard deviation of error under all-in-view, N s For the number of failure modes to be monitored,
is the standard deviation of error at the s-th subset,
the detection threshold corresponding to the s-th subset,
and
probability of all-in-view (full set) and s-th subset, respectively.
The theoretical protection level provided by the embodiment is obtained through a fault-free protection level formula or a multi-solution separation protection level formula, and the theoretical protection level is obtained according to a protection level formula, so that the theoretical protection level can be corrected conveniently according to a correction coefficient to obtain a corrected protection level.
On the basis of the above embodiment, in the process of establishing the prediction protection level correction model, obtaining sample service information and sample observation information includes:
building a PPP-RTK acquisition system;
performing drive test according to different scenes to record sample service information and sample observation information;
correspondingly, acquiring the reference track information stored in the database comprises the following steps:
building a truth value reference system;
and processing the software after the events to obtain the reference track information.
It can be understood that the collection of a large amount of road test data is to build a PPP-RTK test collection vehicle, select scenes such as high speed and high altitude to carry out a large amount of road tests, and record the output data of the receiver and the PPP-RTK service data. Collecting true reference data: a truth value reference system (such as a Novatel SPAN system) is built on a PPP-RTK test acquisition vehicle, and a high-precision track truth value is obtained by using post-processing software (such as Novatel interferometric Explorer).
The sample service information, the sample observation information, and the reference trajectory information stored in the database are obtained by the present embodiment, which is convenient for offline training to provide sample data to establish a prediction protection level correction model.
On the basis of the above embodiment, after obtaining the corrected protection level, the method further includes:
and outputting prompt information for prompting the staff.
And after the corrected protection level is obtained, outputting prompt information, and outputting the protection level to a user for subsequent integrity monitoring. The output mode of the output prompt information is not limited, and the output prompt information can be voice output, mail prompt or short message prompt, and can be set according to the actual situation.
After the corrected protection level is obtained, the prompt information for prompting the staff is output. And reminding workers to facilitate subsequent integrity monitoring.
Fig. 2 is a flowchart of another satellite positioning method according to an embodiment of the present invention, and as shown in fig. 2, the PPP-RTK client protection level correction based on machine learning includes two major parts, i.e., offline training and real-time operation. The offline training has the following functions: and (3) excavating the relation between the number of visible satellites, the carrier-to-noise ratio, the residual error and the like and the positioning error by using a large amount of drive test data and the corresponding track truth value, and further training a protection level correction model. And then, in real-time operation, predicting a protection level correction coefficient by using the trained model to obtain a corrected protection level, and outputting the corrected protection level to a user.
Fig. 3 is a schematic diagram of machine learning training according to an embodiment of the present invention, and fig. 4 is a schematic diagram of a prediction process of machine learning according to an embodiment of the present invention, and as shown in fig. 3, model training is performed based on machine learning methods such as a support vector machine and a neural network by using a protection level correction coefficient obtained in the step of "manually determining a protection level correction coefficient" and process information such as a visible satellite number, a carrier-to-noise ratio, a residual error, and a fixed number of ambiguities stored in the step of "user side positioning & error calculation". To obtain a model for predicting the protection level correction factor using the process information. As shown in fig. 4, the protection level correction coefficient is predicted for the trained model of fig. 3 using process information such as the actual number of visible satellites, carrier-to-noise ratio, residual error, and fixed number of ambiguities.
On the basis of the above detailed description of various embodiments corresponding to the satellite positioning method, the present invention further discloses a satellite positioning apparatus corresponding to the above method, and fig. 5 is a structural diagram of a satellite positioning apparatus provided in an embodiment of the present invention. As shown in fig. 5, the satellite positioning apparatus includes:
a calling module 11, configured to call the prediction protection level correction model to input attribute information, where the attribute information is obtained by PPP-RTK positioning through PPP-RTK service information and observation information of the receiver;
an obtaining module 12, configured to obtain an output parameter of the prediction protection level correction model as a correction coefficient;
the correction module 13 is configured to correct the theoretical protection level according to the correction coefficient to obtain a corrected protection level, where the theoretical protection level is obtained based on a theoretical model;
and the analysis module 14 is configured to analyze the positioning result of the satellite positioning according to the corrected protection level to obtain an analysis result.
Since the embodiment of the apparatus portion corresponds to the above-mentioned embodiment, the embodiment of the apparatus portion is described with reference to the embodiment of the method portion, and is not described again here.
For the introduction of the satellite positioning apparatus provided by the present invention, please refer to the above method embodiment, which is not described herein again, and has the same beneficial effects as the above satellite positioning method.
Fig. 6 is a block diagram of another satellite positioning apparatus according to an embodiment of the present invention, and as shown in fig. 6, the apparatus includes:
a memory 21 for storing a computer program;
a processor 22 for implementing the steps of the method for satellite based positioning when executing the computer program.
The satellite positioning device provided in this embodiment may include, but is not limited to, a smart phone, a tablet computer, a notebook computer, or a desktop computer.
The processor 22 may include one or more processing cores, such as a 4-core processor, an 8-core processor, and so on. The Processor 22 may be implemented in hardware using at least one of a Digital Signal Processor (DSP), a Field-Programmable Gate Array (FPGA), and a Programmable Logic Array (PLA). The processor 22 may also include a main processor and a coprocessor, the main processor is a processor for Processing data in an awake state, and is also called a Central Processing Unit (CPU); a coprocessor is a low power processor for processing data in a standby state. In some embodiments, the processor 22 may be integrated with a Graphics Processing Unit (GPU) that is responsible for rendering and rendering content that the display screen needs to display. In some embodiments, processor 22 may also include an Artificial Intelligence (AI) processor for processing computational operations related to machine learning.
Memory 21 may include one or more computer-readable storage media, which may be non-transitory. Memory 21 may also include high speed random access memory, as well as non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In this embodiment, the memory 21 is at least used for storing a computer program 211, wherein the computer program is loaded and executed by the processor 22, and then the relevant steps of the method for satellite positioning disclosed in any of the foregoing embodiments can be implemented. In addition, the resources stored in the memory 21 may also include an operating system 212, data 213, and the like, and the storage manner may be a transient storage or a permanent storage. Operating system 212 may include Windows, unix, linux, etc., among others. Data 213 may include, but is not limited to, data related to methods of satellite positioning, and the like.
In some embodiments, the satellite positioning device may further include a display 23, an input/output interface 24, a communication interface 25, a power supply 26, and a communication bus 27.
Those skilled in the art will appreciate that the configuration shown in fig. 6 does not constitute a limitation of the means for satellite positioning and may include more or fewer components than those shown.
The processor 22 realizes the method of satellite positioning provided by any of the above embodiments by calling instructions stored in the memory 21.
For the introduction of the satellite positioning apparatus provided by the present invention, please refer to the above method embodiment, which is not described herein again, and has the same beneficial effects as the above satellite positioning method.
Further, the present invention also provides a computer readable storage medium having stored thereon a computer program which, when being executed by the processor 22, carries out the steps of the method for satellite based positioning as described above.
It is to be understood that if the method in the above embodiments is implemented in the form of software functional units and sold or used as a stand-alone product, it can be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and performs all or part of the steps of the methods according to the embodiments of the present invention, or all or part of the technical solution. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
For the introduction of a computer-readable storage medium provided by the present invention, please refer to the above method embodiments, which are not repeated herein, and have the same beneficial effects as the above satellite positioning method.
The present invention provides a method, an apparatus and a medium for satellite positioning. The embodiments are described in a progressive manner in the specification, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description. It should be noted that, for those skilled in the art, it is possible to make various improvements and modifications to the present invention without departing from the principle of the present invention, and those improvements and modifications also fall within the scope of the claims of the present invention.
It is further noted that, in the present specification, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or apparatus that comprises the element.
Claims (10)
1. A method of satellite positioning, comprising:
calling a prediction protection level correction model to input attribute information, wherein the attribute information is obtained by PPP-RTK positioning through PPP-RTK service information and observation information of a receiver;
acquiring an output parameter of the prediction protection level correction model as a correction coefficient;
correcting a theoretical protection level according to the correction coefficient to obtain a corrected protection level, wherein the theoretical protection level is obtained based on a theoretical model;
and analyzing the positioning result of the satellite positioning according to the corrected protection level to obtain an analysis result.
2. The method for satellite positioning according to claim 1, wherein the PPP-RTK service information includes at least orbit information, clock error information, bias information, and atmospheric information of GNSS satellites;
the observation information at least comprises pseudo-range information and carrier observation information of the receiver;
the attribute information at least comprises the quantity information of visible satellites, carrier-to-noise ratio information, residual error information, ambiguity fixed state information and ambiguity fixed quantity information.
3. The satellite positioning method according to claim 2, wherein the process of establishing the predicted protection level correction model specifically includes:
acquiring sample service information, sample observation information and reference track information stored in a database;
PPP-RTK positioning is carried out according to the sample service information and the sample observation information to obtain off-line positioning information and off-line attribute information;
processing according to the offline positioning information and the reference track information to obtain positioning error information;
determining an off-line correction coefficient according to the relation between the theoretical protection level and the positioning error information;
and training the offline correction coefficient and the offline attribute information through a machine learning algorithm to obtain the prediction protection level correction model.
4. The method according to claim 3, wherein the determining an offline correction factor according to the relationship between the theoretical protection level and the positioning error information comprises:
and setting the offline correction coefficient under the condition that the positioning error information is not completely enveloped by the theoretical protection level or the positioning error information is completely enveloped by the theoretical protection level, and the difference value between the theoretical protection level and the positioning error information is less than a threshold value.
5. The method according to claim 4, wherein the theoretical protection level is obtained by a non-fault protection level formula or a multi-solution split protection level formula.
6. The method of satellite positioning according to claim 3, wherein obtaining the sample service information and the sample observation information comprises:
building a PPP-RTK acquisition system;
performing drive test according to different scenes to record the sample service information and the sample observation information;
correspondingly, acquiring the reference track information stored in the database includes:
building a truth value reference system;
and obtaining the reference track information according to post-processing software.
7. The method according to any of claims 1 to 6, further comprising, after obtaining the corrected protection level:
and outputting prompt information for prompting the staff.
8. An apparatus for satellite positioning, comprising:
the calling module is used for calling the prediction protection level correction model to input attribute information, wherein the attribute information is obtained by PPP-RTK positioning through PPP-RTK service information and observation information of a receiver;
the acquisition module is used for acquiring the output parameters of the prediction protection level correction model as correction coefficients;
the correction module is used for correcting a theoretical protection level according to the correction coefficient to obtain a corrected protection level, wherein the theoretical protection level is obtained based on a theoretical model;
and the analysis module is used for analyzing the positioning result of the satellite positioning according to the corrected protection level to obtain an analysis result.
9. An apparatus for satellite positioning, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the method for satellite based positioning according to any of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, characterized in that a computer program is stored thereon, which computer program, when being executed by a processor, carries out the steps of the method for satellite based positioning according to one of claims 1 to 7.
Priority Applications (1)
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| CN116859422A (en) * | 2023-07-18 | 2023-10-10 | 湖南六九零六信息科技股份有限公司 | High-precision satellite positioning enhancement system and method based on heterogeneous fusion parallel cluster architecture |
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| CN116859422A (en) * | 2023-07-18 | 2023-10-10 | 湖南六九零六信息科技股份有限公司 | High-precision satellite positioning enhancement system and method based on heterogeneous fusion parallel cluster architecture |
| CN116859422B (en) * | 2023-07-18 | 2024-01-26 | 湖南六九零六信息科技股份有限公司 | High-precision satellite positioning enhancement system and method based on heterogeneous fusion parallel cluster architecture |
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