CN117214921A - Method for determining quality factor, computer storage medium and terminal - Google Patents
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Abstract
The application discloses a method for determining quality factors, a computer storage medium and a terminal.
Description
Technical Field
The present application relates to, but is not limited to, satellite navigation technology, and relates to a method, computer storage medium and terminal for determining quality factors.
Background
The global satellite navigation system (GNSS, global Navigation Satellite System) can provide three-dimensional, all-weather, high-quality Positioning, navigation and timing (PNT, navigation and Timing) services for global users, and is an important Positioning means in traffic, communication, mapping and other industries. However, the use of GNSS self-navigation services can only achieve meter-level positioning accuracy, and cannot meet the urgent demands for rapid centimeter-level positioning in the fields of autopilot, precision agriculture, unmanned aerial vehicle mapping, geodetic survey, earthquake and tsunami monitoring, and the like. For this reason, high-precision positioning techniques based on GNSS have been developed; typical high precision positioning methods include Real-Time Kinematic (RTK) and precision single point positioning (PPP, precise Point Positioning); the PPP technology uses precise satellite orbit and clock error and code deviation correction products provided by the international GNSS service organization (IGS, international GNSS Service) and the like, comprehensively considers various error sources, and can realize high-precision absolute positioning by using only the pseudo-range and carrier phase observation values of a single GNSS receiver. The method integrates the advantages of standard single-point positioning and relative positioning, has the advantages of flexible positioning mode, high-precision positioning realized by a single machine, simple and convenient operation, global coverage capability and the like, and provides brand-new technical support and solution for high-precision positioning of wide GNSS users; compared with the RTK technology, the real-time PPP technology has two remarkable advantages: the service coverage area of the system is large and the total operation cost is low; however, the real-time PPP has a problem of long convergence time, so as to solve the problem of long convergence time of the real-time PPP, and the PPP-RTK technology integrating two technical advantages of PPP and RTK has the basic idea that the local area network observation data is utilized to refine and solve (partial) state space domain correction (SSR, state Space Representation) products provided by the global network (wide area network), such as satellite clock error, phase deviation and the like, and solve parameters such as atmospheric delay and the like, and all regenerated correction information is represented by SSR and is independently broadcast to a mobile station for use. The user side corrects the observed data by using the received real-time track, clock correction, pseudo-range phase deviation, high-precision non-differential troposphere delay and ionosphere delay to recover the integer characteristic of the non-differential ambiguity and fix the integer characteristic, and PPP-RTK positioning based on PPP mode is realized by accelerating the initialization of PPP.
As the basis of PPP and PPP-RTK positioning technology, the precise orbit and clock correction of satellites are critical, the precision orbit and clock correction is calculated by PPP or PPP-RTK server corresponding to each satellite in real time, the satellite is broadcast at the frequency of second level, and after receiving the correction, the user applies the satellite to GNSS broadcast ephemeris, so that the accuracy of the orbit and clock correction of the broadcast ephemeris is improved to centimeter level. In addition, precision orbit and clock error products are also necessary inputs to calculate other PPP-RTK service products (e.g., phase bias, atmosphere). In addition to the orbit clock correction data itself, the PPP and PPP-RTK client algorithms also need to obtain quality factors of these data to construct a weight matrix; the quality factor reflects the accuracy of the orbit clock correction, and the final state estimation result error can be minimized by reasonably distributing weight to each satellite.
The precise orbit and clock correction data of the GNSS satellites are calculated based on the ground observation station with global distribution by utilizing the reverse positioning principle and combining the dynamics model of the orbit and various compensation models. The broadcast frequency of this correction is typically within 10 seconds due to the fast satellite motion and the varying satellite clock. For the calculation of the quality factor of the orbit clock correction, the related art extracts the standard deviation of the error of each satellite as the quality factor of each piece of product information based on the covariance matrix obtained in the state estimation (e.g., the kalman filtering process). For the calculation of the quality factor of the track clock correction, the related technology has the advantages that the provided result is too optimistic, namely the product quality factor is far smaller than the actual error; the method is characterized in that the Kalman filtering method and the like adopted in the track clock error estimation process belong to an optimized autoregressive data processing algorithm, and the state covariance becomes smaller along with the time; however, the error model used in filtering is based on gaussian white noise assumption and cannot reflect the error characteristics at any moment in real-time operation; in addition, the theoretical model of the filtering algorithm is approximated and simplified, and some errors actually existing in the product after convergence cannot be reflected in the theoretical covariance, which further causes inaccurate quality factor results; for a positioning terminal algorithm, the error position state covariance information can be obtained by using a product quality factor which is too small, so that the performance of an integrity calculation and fusion algorithm is not facilitated; furthermore, if the usage weight is incorrectly assigned to the orbital clock error product for each satellite, the positioning accuracy can be greatly reduced, even causing the position results to diverge.
In summary, how to reduce the positioning problem caused by inaccurate quality factor of the track clock correction, and improve the positioning reliability and safety becomes a problem to be solved.
Disclosure of Invention
The following is a summary of the subject matter of the detailed description of the application. This summary is not intended to limit the scope of the claims.
The embodiment of the disclosure provides a method for determining a quality factor, a computer storage medium and a terminal, which can reduce the positioning problem caused by inaccurate quality factor of a track clock correction, and improve the positioning reliability and safety.
The embodiment of the disclosure provides a method for determining a quality factor, which comprises the following steps:
the method comprises the steps of obtaining a product error by making a difference between a historical precision track clock error product generated by a precision single point positioning PPP server and a product true value, wherein the product true value comprises an IGS post precision track clock error product;
counting a first standard deviation of the product error of the average precise orbit clock difference product of each satellite, and taking the first standard deviation as a quality factor reference;
according to the data of the historical precise orbit clock error products and the historical pseudo-range and carrier observation data stored by all monitoring stations, calculating pseudo-range residual errors and carrier residual errors of all frequency points of each satellite under a single epoch;
according to the pseudo-range residuals and the carrier residuals of the preset number of monitoring stations at the current moment, respectively solving the second standard deviation of the pseudo-range residuals and the third standard deviation of the carrier residuals of the preset number of monitoring stations at the current moment;
determining the quality factor of the precision orbit clock error product according to a predetermined quality factor parameter, a quality factor reference, a second standard deviation and a third standard deviation;
wherein the quality factor parameter is determined based on the product error.
In another aspect, embodiments of the present disclosure also provide a computer storage medium having a computer program stored therein, which when executed by a processor, implements the above-described method of determining a quality factor.
In still another aspect, an embodiment of the present disclosure further provides a terminal, including: a memory and a processor, the memory storing a computer program; wherein,
the processor is configured to execute the computer program in the memory;
the computer program, when executed by the processor, implements a method of determining a quality factor as described above.
According to the embodiment of the disclosure, the quality factor is calculated based on the historical precise track clock error product, the calculated quality factor can represent the actual error of the precise track clock error product, the result is objective, the quality of calculation of the user side algorithm weight matrix is improved, the positioning problem caused by inaccurate quality factor of the track clock error correction is reduced, and the positioning reliability and safety are improved.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the application. Other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and drawings.
Drawings
The accompanying drawings are included to provide an understanding of the principles of the application, and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain, without limitation, the principles of the application.
FIG. 1 is a flow chart of a method of determining a quality factor according to an embodiment of the present disclosure;
fig. 2 is an application processing schematic diagram of an embodiment of the present disclosure.
Detailed Description
The present application has been described in terms of several embodiments, but the description is illustrative and not restrictive, and it will be apparent to those of ordinary skill in the art that many more embodiments and implementations are possible within the scope of the described embodiments. Although many possible combinations of features are shown in the drawings and discussed in the detailed description, many other combinations of the disclosed features are possible. Any feature or element of any embodiment may be used in combination with or in place of any other feature or element of any other embodiment unless specifically limited.
The present application includes and contemplates combinations of features and elements known to those of ordinary skill in the art. The disclosed embodiments, features and elements of the present application may also be combined with any conventional features or elements to form a unique inventive arrangement as defined by the claims. Any feature or element of any embodiment may also be combined with features or elements from other inventive arrangements to form another unique inventive arrangement as defined in the claims. It is therefore to be understood that any of the features shown and/or discussed in the present application may be implemented alone or in any suitable combination. Accordingly, the embodiments are not to be restricted except in light of the attached claims and their equivalents. Further, various modifications and changes may be made within the scope of the appended claims.
Furthermore, in describing representative embodiments, the specification may have presented the method and/or process as a particular sequence of steps. However, to the extent that the method or process does not rely on the particular order of steps set forth herein, the method or process should not be limited to the particular sequence of steps described. Other sequences of steps are possible as will be appreciated by those of ordinary skill in the art. Accordingly, the particular order of the steps set forth in the specification should not be construed as limitations on the claims. Furthermore, the claims directed to the method and/or process should not be limited to the performance of their steps in the order written, and one skilled in the art can readily appreciate that the sequences may be varied and still remain within the spirit and scope of the embodiments of the present application.
Fig. 1 is a flowchart of a method for determining a quality factor according to an embodiment of the present disclosure, as shown in fig. 2, including:
step 101, a product error is obtained by subtracting a historical precision orbit clock error product and a product true value generated by a precision single point positioning (PPP) server; wherein, the product truth value includes: post-hoc precision track clock error products of IGS;
step 102, counting a first standard deviation of a product error of a precise orbit clock difference product of each satellite, and taking the first standard deviation as a quality factor reference;
step 103, calculating pseudo-range residuals and carrier residuals of all frequency points of each satellite under a single epoch according to the data of the historical precise orbit clock difference product and the historical pseudo-range and carrier observation data stored by all monitoring stations;
104, respectively solving a second standard deviation of the pseudo range residuals of the preset number of monitoring stations at the current moment and a third standard deviation of the carrier residuals according to the pseudo range residuals and the carrier residuals of the preset number of monitoring stations at the current moment; here, the preset number of monitoring stations may include all the monitoring stations, or may include a certain number of monitoring stations set by a technician; the current time refers to the time of calculating the precise track clock error product;
step 105, determining the quality factor of the precision orbit clock error product according to a predetermined quality factor parameter, a quality factor reference, a second standard deviation and a third standard deviation;
wherein the quality factor parameter is determined based on the product error.
The historical precision orbit clock error product in the embodiments of the present disclosure includes: historical precision track products and precision clock error products. The IGS in the embodiments of the present disclosure is an international organization consisting of a plurality of academia and enterprises and institutions, and is a relatively authoritative organization recognized in the industry; IGS provides precision orbital clock-biased products with high precision, reliability and stability, and therefore are often used as true products; that is, the precise track clock product provided by the IGS is a true reference; since the historical data of the station network is collected for later batch processing and checking, and is not calculated in real time, the result of one day is usually taken after 15 days, so that the station network is called a post-precision track clock error product. The precise track clock product in the embodiment of the disclosure corresponds to a track clock product with common precision, PPP can be realized by using the precise track clock product, and a common user (such as a mobile phone) uses the common track clock in a positioning way.
According to the embodiment of the disclosure, the quality factor is calculated based on the historical precise track clock error product, the calculated quality factor can represent the actual error of the precise track clock error product, the result is objective, the quality of calculation of the user side algorithm weight matrix is improved, the positioning problem caused by inaccurate quality factor of the track clock error correction is reduced, and the positioning reliability and safety are improved.
In the embodiment of the disclosure, a monitoring station comprises a receiver, and a pseudo-range residual error and a carrier residual error are provided under a frequency point of the receiver; thus, one monitoring station will provide L pseudo-range residuals and L carrier residuals. When the number of the monitoring stations is R in the step 204, R multiplied by L pseudo-range residuals and R multiplied by L carrier residuals are obtained; calculating standard deviations of the R multiplied by L pseudo-range residuals to obtain second standard deviations; and calculating the standard deviation of R multiplied by L carrier residues to obtain a third standard deviation.
The quality factor in the embodiments of the present disclosure is updated in real time as the precision track clock error product is updated; assuming that the precision track clock error product update frequency is 5 seconds, the quality factor is updated every 5 seconds.
In one illustrative example, the quality factor parameters in embodiments of the present disclosure are determined by:
dividing the product error into more than two intervals; here, the product error refers to the product error obtained by calculation in step 101;
for the product error of each divided interval, respectively determining a fourth standard deviation of a pseudo-range residual error and a fifth standard deviation of a carrier residual error corresponding to each interval;
fitting the solved fourth standard deviation and the fifth standard deviation to obtain an actual quality factor of each interval;
and solving to obtain quality factor parameters based on the fact that the product error of the interval is equal to the actual quality factor of the interval.
After dividing the product error into more than two intervals, the second standard deviation is correspondingly divided into more than two intervals, and the standard deviation of the corresponding interval is a fourth standard deviation; the third standard deviation is divided into more than two corresponding intervals, and the standard deviation of the corresponding interval is the fifth standard deviation.
The embodiment of the disclosure obtains key fitting parameters by analyzing historical product data, and obtains real-time quality factors by fitting based on residual standard deviation of a monitoring station in actual operation.
In one illustrative example, the present disclosure embodiment step 103 divides the product error into two or more intervals, including:
the product error is divided into more than two intervals according to the magnitude of the product error.
In one illustrative example, the disclosed embodiments may perform interval partitioning by a technician based on empirical values; the embodiment of the disclosure can divide the product error into more than two product error intervals with reference to the following division modes: after the product error is obtained, the product error is divided into a group from 0 to 0.03, the product error is divided into a group from 0.03 to 0.1, the product error is divided into a group from 0.1 to 1, the product error is divided into a group from 1 to 5, and the product error is removed from the product error by more than 5.
In an illustrative example, step 103 of the disclosed embodiment calculates pseudo-range residuals and carrier residuals for all frequency points of each satellite for a single epoch, including:
and (3) adopting a non-differential non-combination (PPP) mode to perform state estimation on the observed values of all the frequency points of each satellite in a single epoch, and then determining pseudo-range residual errors and carrier residual errors of all the frequency points in the single epoch.
According to the method and the device for calculating the pseudo-range residual error and the carrier residual error, the PPP mode is adopted to calculate the pseudo-range residual error and the carrier residual error, and effectiveness and robustness of an algorithm for calculating the pseudo-range residual error and the carrier residual error are improved.
In one illustrative example, embodiments of the present disclosure record pseudorange residuals asRecorded wave residual is->The pseudo-range residual errors and carrier residual errors of all frequency points under a single epoch are determined according to the following formula:
wherein i corresponds to satellite, i= … S; j corresponds to a monitoring station, j= … R; f corresponds to the signal frequency point, f= … L, ρ is the pseudo-range observed value after correction code delay, ψ is the carrier observed value,for the pseudo-range observation value of satellite i corresponding to monitoring station j after the correction code delay of signal frequency point f, +.>For the carrier observation value X of the satellite i corresponding to the monitoring station j at the signal frequency point f i For the position of satellite i calculated based on precision orbit products, X j Is the precise coordinate of the known monitoring station j, cdt i Satellite clock difference of satellite i provided for precision clock difference product, +.>Receiver clock error for watch station j estimated using PPP floating solution,/>Tropospheric delay for satellite i corresponding to rover j estimated using PPP floating solution, < >>Ionospheric delay for satellite i corresponding to rover j estimated using PPP floating solution, +.>The floating ambiguity of satellite i corresponding to the watch station j estimated by using the PPP floating solution.
According to the method for determining the pseudo-range residuals and the carrier residuals of all frequency points under a single epoch, the pseudo-range residuals and the carrier residuals of the preset number of monitoring stations at the current moment are determined.
In one illustrative example, the second standard deviation is noted asThe third standard deviation is->The disclosed embodiments fit according to the following formulas with reference to the correlation principles to obtain the actual quality factor for each interval:
wherein QI truth The actual quality factor of each interval is equal to the standard deviation of the product error in the interval; by fitting the data of different intervals, three parameters alpha, beta, gamma and can be determined
The method for obtaining the actual quality factor of each interval by fitting according to the embodiment of the disclosure can be a mathematical method existing in the related art, such as least square; based on the formula of fitting to obtain the actual quality factor of each interval and four groups of product errors of different intervals, each group can calculate and obtain QI truth Andand->The parameters alpha, beta and gamma can be obtained by solving based on four equation feet.
In one exemplary embodiment, the second standard deviation of the pseudo-range residuals of all monitoring stations worldwide at the current time is recorded asThe third standard deviation of the carrier residuals of all monitoring stations worldwide at the current moment is +.>The real-time quality factor of the precision orbit clock error product is marked as +.>Based on the previously determined α, β, and γ, embodiments of the present disclosure calculate the quality factor as:
n is a preset weighting coefficient.
Embodiments of the present disclosure calculate the obtained due to the accuracy limitations of the calculation modelPossibly too small a value of (c) in order to avoid this value too small by setting +.>For avoiding, n is a preset weighting coefficient, and may be determined by a technician according to a characteristic analysis of historical data, where n in the embodiment of the disclosure may be a value between 0.5 and 0.8, for example, may be 0.8, and the value may be a fixed value after the value is determined. In one illustrative example, the present disclosure is trueThe embodiment updates the quality factor parameter according to a preset update period.
In the embodiment of the disclosure, the quality factor parameter is updated according to the update period, and the update period may be a quarter, and one quarter is taken as an alternative example of the update period; the update period in the embodiments of the present disclosure may be adjusted according to the following two points: 1. ensuring a certain number of data points to calculate the distribution of product errors; 2. the data within the preset time period is selected to avoid that the data of the track clock error product which is too long before and the data of the current track clock error product may have overlarge characteristics and have no reference value.
The embodiment of the disclosure also provides a computer storage medium, in which a computer program is stored, which when executed by a processor, implements the method for determining a quality factor.
The embodiment of the disclosure also provides a terminal, which comprises: a memory and a processor, the memory storing a computer program;
wherein,
the processor is configured to execute the computer program in the memory;
the computer program, when executed by a processor, implements a method of determining a quality factor as described above.
The following briefly describes embodiments of the present disclosure by way of application examples, which are merely set forth embodiments of the present disclosure and are not intended to limit the scope of the embodiments of the present disclosure.
Fig. 2 is an application processing schematic diagram of an embodiment of the disclosure, as shown in fig. 2, a PPP or PPP-RTK server performs calculation of a precision orbit clock difference product based on real-time observation data of a global reference station network, global distributed independent monitoring stations provide pseudo-range data and carrier data at the same time, a residual calculation module in the embodiment of the disclosure performs residual calculation, and a pseudo-range residual and a carrier residual obtained by the calculation of the residual calculation module are broadcast to a quality factor calculation module for performing related processing of quality factor calculation including steps 101 to 105; the track clock error product quality information obtained by the embodiment of the disclosure comprises quality factors of each piece of precise track clock error product information, so that a terminal user can carry out reasonable weight and terminal integrity calculation, positioning problems caused by abnormality of the track clock error products are reduced, and the purposes of positioning reliability and safety are improved;
those of ordinary skill in the art will appreciate that all or some of the steps, systems, functional modules/units in the apparatus, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between the functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed cooperatively by several physical components. Some or all of the components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as known to those skilled in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, as is well known to those of ordinary skill in the art, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.
Claims (10)
1. A method of determining a quality factor, comprising:
the method comprises the steps of obtaining a product error by making a difference between a historical precision track clock error product generated by a precision single point positioning PPP server and a product true value, wherein the product true value comprises an IGS post precision track clock error product;
counting a first standard deviation of the product error of the average precise orbit clock difference product of each satellite, and taking the first standard deviation as a quality factor reference;
according to the data of the historical precise orbit clock error products and the historical pseudo-range and carrier observation data stored by all monitoring stations, calculating pseudo-range residual errors and carrier residual errors of all frequency points of each satellite under a single epoch;
according to the pseudo-range residuals and the carrier residuals of the preset number of monitoring stations at the current moment, respectively solving the second standard deviation of the pseudo-range residuals and the third standard deviation of the carrier residuals of the preset number of monitoring stations at the current moment;
determining the quality factor of the precision orbit clock error product according to a predetermined quality factor parameter, a quality factor reference, a second standard deviation and a third standard deviation;
wherein the quality factor parameter is determined based on the product error; the current time is the time for calculating the precise track clock difference product.
2. The method according to claim 1, wherein calculating pseudo-range residuals and carrier residuals for all frequency points of each satellite for a single epoch, respectively, comprises:
and after the state estimation is carried out on the observed values of all the frequency points of each satellite in a single epoch by adopting a non-differential non-combination PPP mode, the pseudo-range residual errors and the carrier residual errors of all the frequency points in the single epoch are determined.
3. The method of claim 2, wherein the pseudorange residuals for all frequency points of each satellite for a single epoch are recorded asEach satellite under a single epochThe carrier residuals of all frequency points are +.>Determining the pseudo-range residuals and the carrier residuals of all frequency points under a single epoch according to the following formula:
wherein i corresponds to satellite, i= … S; j corresponds to a monitoring station, j= … R; f corresponds to the signal frequency point, f= … L, ρ is the pseudo-range observed value after correction code delay, ψ is the carrier observed value,for the pseudo-range observation value of satellite i corresponding to monitoring station j after the correction code delay of signal frequency point f, +.>For the carrier observation value X of the satellite i corresponding to the monitoring station j at the signal frequency point f i For the position of satellite i calculated based on precision orbit products, X j Is the precise coordinate of the known monitoring station j, cdt i Satellite clock difference of satellite i provided for precision clock difference product, +.>Receiver clock error for watch station j estimated using PPP floating solution,/>Tropospheric delay for satellite i corresponding to rover j estimated using PPP floating solution, < >>Ionospheric delay for satellite i corresponding to rover j estimated using PPP floating solution, +.>The floating ambiguity of satellite i corresponding to the watch station j estimated by using the PPP floating solution.
4. A method according to any one of claims 1 to 3, wherein the quality factor parameter is updated according to a predetermined update period.
5. A method according to any one of claims 1 to 3, characterized in that the quality factor parameter is determined based on the product error by:
dividing the obtained product error into more than two intervals;
for the product error of each divided interval, respectively determining a fourth standard deviation of a pseudo-range residual error and a fifth standard deviation of a carrier residual error corresponding to each interval;
fitting the fourth standard deviation and the fifth standard deviation to obtain an actual quality factor of each interval;
and solving to obtain the quality factor parameter based on the product error of the interval being equal to the actual quality factor of the interval.
6. The method of claim 5, wherein the dividing the product error into more than two bins comprises:
the product error is divided into more than two intervals according to the magnitude of the product error.
7. The method of claim 5, wherein the second standard deviation isThe third standard deviation is->Quality factor reference is->Fitting according to the following formula to obtain the actual quality factor of each interval:
wherein QI truth For the actual quality factor for each interval, α, β and γ are the quality factor parameters.
8. The method of claim 7, wherein the quality factor of the precision orbit clock error product isThe expression of the quality factor is:
in the method, in the process of the application,n is a preset weighting coefficient.
9. A computer storage medium having stored therein a computer program which, when executed by a processor, implements the method of determining a quality factor according to any of claims 1 to 8.
10. A terminal, comprising: a memory and a processor, the memory storing a computer program; wherein,
the processor is configured to execute the computer program in the memory;
the computer program, when executed by the processor, implements a method of determining a quality factor as claimed in any of claims 1 to 8.
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