CN116879935B - Whole-cycle ambiguity determining method, system and computer for Beidou positioning - Google Patents
Whole-cycle ambiguity determining method, system and computer for Beidou positioning Download PDFInfo
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/43—Determining position using carrier phase measurements, e.g. kinematic positioning; using long or short baseline interferometry
- G01S19/44—Carrier phase ambiguity resolution; Floating ambiguity; LAMBDA [Least-squares AMBiguity Decorrelation Adjustment] method
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/13—Receivers
- G01S19/35—Constructional details or hardware or software details of the signal processing chain
- G01S19/37—Hardware or software details of the signal processing chain
Abstract
The application provides a whole-cycle ambiguity determining method, a system and a computer for Beidou positioning, wherein the method comprises the following steps: obtaining an observed value, and obtaining a whole-cycle ambiguity floating solution and a baseline vector floating solution based on the observed value; applying conditional constraint to the integer ambiguity floating solution by the baseline vector floating solution to obtain an integer ambiguity to-be-selected solution from the integer ambiguity floating solution; z transformation is carried out on the integer ambiguity to be selected, and a function to be selected is constructed through the integer ambiguity to be selected after Z transformation; and constructing and correcting the initially selected space to obtain an optimal space to be selected, and determining an optimal solution of the integer ambiguity by using the function to be selected and the optimal space to be selected. By means of constraint of the base line vector floating solution, part of the base line vector floating solution can be eliminated, the subsequent searching quantity is reduced, and by means of optimizing the initially selected space to be selected, the gap between the Z-transformed integer ambiguity to be selected solution and the expected value can be reduced, and the accuracy of acquiring the integer ambiguity is effectively improved.
Description
Technical Field
The application relates to the technical field of navigation positioning, in particular to a whole-cycle ambiguity determining method, a whole-cycle ambiguity determining system and a whole-cycle ambiguity determining computer for Beidou positioning.
Background
The carrier phase differential positioning method applied to the Beidou satellite navigation system is a differential method for processing carrier phase observation values of two measuring stations in real time. The carrier phase acquired by the reference station is sent to the user receiver, and the carrier phase observed values of the local station and the reference station are subjected to difference so as to calculate the coordinates.
In the carrier phase differential positioning method, the accuracy of the whole-cycle ambiguity acquisition is used for determining the accuracy of a positioning result, and how to accurately acquire the whole-cycle ambiguity is one of the key problems to be studied currently.
Disclosure of Invention
The embodiment of the application provides a whole-cycle ambiguity determining method, a whole-cycle ambiguity determining system and a whole-cycle ambiguity determining computer for Beidou positioning, which are used for solving the technical problem of how to improve the accuracy of obtaining whole-cycle ambiguities in the prior art.
In a first aspect, an embodiment of the present application provides a method for determining integer ambiguity for beidou positioning, including the following steps:
obtaining an observation value, and obtaining a whole-cycle ambiguity floating solution and a baseline vector floating solution based on the observation value;
applying a conditional constraint to the integer ambiguity float solution by the baseline vector float solution to obtain an integer ambiguity candidate solution from the integer ambiguity float solution;
z transformation is carried out on the integer ambiguity to-be-selected solution, and a to-be-selected function is constructed through the integer ambiguity to-be-selected solution after Z transformation;
and constructing a primary selection space, determining a correction value through the integer ambiguity candidate solution after Z transformation, correcting the primary selection space based on the correction value to obtain an optimal selection space, and determining an integer ambiguity optimal solution through the candidate function and the optimal selection space.
Further, the step of obtaining a whole-cycle ambiguity floating solution and a baseline vector floating solution based on the observed value includes:
constructing a double-difference observation equation among the integer ambiguity hypothesis value, the baseline vector hypothesis value and the observation value;
and carrying out least square prediction on the double difference observation equation to obtain a whole-cycle ambiguity floating solution and a baseline vector floating solution.
Further, the double difference observation equation is:
，
wherein,indicating lossFunction (F)>Representing the integer ambiguity hypothesis, +.>Representing baseline vector hypothesis values,/->Representing observation noise->、/>All represent coefficient matrices;
the integer ambiguity floating solution is:
，
wherein,representing integer ambiguity floating solution, +.>Representing covariance matrix>The transpose symbol is represented by a representation,
，/>a unit array representing the number of epochs observed and the number of satellites observed;
the baseline vector floating point solution is:
，
wherein,representing a baseline vector floating solution.
Further, the step of applying a conditional constraint to the integer ambiguity floating solution by the baseline vector floating solution to obtain an integer ambiguity candidate solution from the integer ambiguity floating solution includes:
constructing an objective function based on the integer ambiguity floating solution and the baseline vector floating solution;
and carrying out least square prediction on the objective function to obtain a whole-cycle ambiguity to-be-selected solution.
Further, the objective function is:
，
wherein,representing an objective function +.>Representing the integer ambiguity hypothesis, +.>Representing baseline vector hypothesis values,/->Representing integer ambiguity floating solution, +.>Representing integer ambiguity floating solution, +.>Conditional expectation, indicative of a baseline vector floating solution corresponding to integer ambiguity hypothesis values, ++>Representing covariance matrix>Representing variance->Represents an n-dimensional real set, ">The number of observation frequencies is represented;
the integer ambiguity is to be solved as follows:
，
wherein,representing the integer ambiguity alternative solution, +.>The conditional expectation of the baseline limiting candidate solution corresponding to the integer ambiguity candidate solution is represented.
Further, the function to be selected is:
，
wherein,representing the function to be selected->、/>All represent calculation parameters, +.>Representing the integer ambiguity after the ith Z-transform to be solved,/for selection>Representing the integer ambiguity optimal solution after Z-transformation,>and the standard deviation of the integer ambiguity optimal solution after Z transformation is shown.
Further, the correction value is:
，
wherein,indicating correction value->、/>All represent calculation parameters, +.>Representing the integer ambiguity candidate solution after Z-transformation,>representing rounding;
the optimal space to be selected is:
，
wherein,representing the optimal selection space, < >>Representing the primary selection of the space to be selected.
In a second aspect, an embodiment of the present application provides a system for determining integer ambiguity in beidou positioning, where the method for determining integer ambiguity in beidou positioning according to the first aspect is applied, and the system includes:
the calculation module is used for acquiring an observed value, and acquiring a whole-cycle ambiguity floating solution and a baseline vector floating solution based on the observed value;
the constraint module is used for applying constraint conditions to the integer ambiguity floating solution so as to obtain an integer ambiguity solution to be selected from the integer ambiguity floating solution;
the construction module is used for carrying out Z transformation on the integer ambiguity to-be-selected solution, and constructing a to-be-selected function through the integer ambiguity to-be-selected solution after Z transformation;
the screening module is used for constructing a primary selected space, determining a correction value through the integer ambiguity to-be-selected solution after Z transformation, correcting the primary selected space based on the correction value to obtain an optimal to-be-selected space, and determining the integer ambiguity optimal solution through the to-be-selected function and the optimal to-be-selected space.
In a third aspect, an embodiment of the present application provides a computer, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the processor implements the whole-cycle ambiguity determining method for beidou positioning according to the first aspect when executing the computer program.
Compared with the prior art, the application has the beneficial effects that: after the integer ambiguity floating solution is obtained, constraint is carried out on the integer ambiguity floating solution through the baseline vector floating solution, and before searching in the optimal space to be selected, part of the baseline vector floating solution is removed, so that the subsequent searching quantity is reduced, and the accuracy of the integer ambiguity obtaining is improved; by optimizing the primary selection space, the gap between the integer ambiguity to be selected after Z transformation and the expected value can be reduced, the range of the search space is reduced, the accuracy of integer ambiguity acquisition is further improved, and the search efficiency is improved.
The details of one or more embodiments of the application are set forth in the accompanying drawings and the description below to provide a more thorough understanding of the other features, objects, and advantages of the application.
Drawings
FIG. 1 is a flowchart of a method for determining integer ambiguity in Beidou positioning according to a first embodiment of the present application;
FIG. 2 is a block diagram of a system for determining integer ambiguity in Beidou positioning in a second embodiment of the present application;
the application will be further described in the following detailed description in conjunction with the above-described figures.
Detailed Description
The present application will be described and illustrated with reference to the accompanying drawings and examples in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application. All other embodiments, which can be made by a person of ordinary skill in the art based on the embodiments provided by the present application without making any inventive effort, are intended to fall within the scope of the present application.
It is apparent that the drawings in the following description are only some examples or embodiments of the present application, and it is possible for those of ordinary skill in the art to apply the present application to other similar situations according to these drawings without inventive effort. Moreover, it should be appreciated that while such a development effort might be complex and lengthy, it would nevertheless be a routine undertaking of design, fabrication, or manufacture for those of ordinary skill having the benefit of this disclosure, and thus should not be construed as having the benefit of this disclosure.
Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is to be expressly and implicitly understood by those of ordinary skill in the art that the described embodiments of the application can be combined with other embodiments without conflict.
Referring to fig. 1, the method for determining integer ambiguity in beidou positioning according to the first embodiment of the present application includes steps S10 to S40:
step S10: obtaining an observation value, and obtaining a whole-cycle ambiguity floating solution and a baseline vector floating solution based on the observation value;
it will be appreciated that by obtaining the observations within the monitoring station, in this embodiment, the observations of at least two epochs need to be observed consecutively.
Specifically, the step S10 includes:
s110: constructing a double-difference observation equation among the integer ambiguity hypothesis value, the baseline vector hypothesis value and the observation value;
the double difference observation equation is:
，
wherein,representing a loss function->Representing the integer ambiguity hypothesis, +.>Representing baseline vector hypothesis values,/->Representing observation noise->、/>Each representing a coefficient matrix.
S120: performing least square prediction on the double difference observation equation to obtain a whole-cycle ambiguity floating solution and a baseline vector floating solution;
under the condition that the observation noise is known, the floating solution can be obtained by carrying out least square estimation on the double difference observation equation.
The integer ambiguity floating solution is:
，
wherein,representing integer ambiguity floating solution, +.>Representing covariance matrix>The transpose symbol is represented by a representation,
，/>a unit array representing the number of epochs observed and the number of satellites observed;
the baseline vector floating point solution is:
，
wherein,representing a baseline vector floating solution.
In general, after the integer ambiguity floating solution is obtained, a least square function can be constructed on the integer ambiguity floating solution, and then the integer ambiguity optimal solution is determined through a search space. However, each component in the integer ambiguity floating solution has extremely strong cross correlation, so that the searching efficiency and precision are reduced.
Step S20: applying a conditional constraint to the integer ambiguity float solution by the baseline vector float solution to obtain an integer ambiguity candidate solution from the integer ambiguity float solution;
the aim of conditional constraint on the integer ambiguity floating solution is to exclude part of the baseline vector floating solution before searching in the optimal space to be selected in a baseline constraint mode, so that the number of subsequent searching is reduced, and the accuracy and speed of integer ambiguity acquisition are improved.
Specifically, the step S20 includes:
s210: constructing an objective function based on the integer ambiguity floating solution and the baseline vector floating solution;
the objective function is:
，
wherein,representing an objective function +.>Representing the integer ambiguity hypothesis, +.>Representing baseline vector hypothesis values,/->Representing integer ambiguity floating solution, +.>Representing integer ambiguity floating solution, +.>Conditional expectation, indicative of a baseline vector floating solution corresponding to integer ambiguity hypothesis values, ++>Representing covariance matrix>Representing variance->Represents an n-dimensional real set, ">The number of observation frequencies is represented;
s220: performing least square prediction on the objective function to obtain a whole-cycle ambiguity to-be-selected solution;
the integer ambiguity is to be solved as follows:
，
wherein,representing the integer ambiguity alternative solution, +.>The conditional expectation of the baseline limiting candidate solution corresponding to the integer ambiguity candidate solution is represented.
The expected expression of the condition of the baseline limit solution to be selected corresponding to the integer ambiguity solution to be selected is:
，
wherein,the conditional expectation of the baseline limiting floating solution corresponding to the integer ambiguity candidate solution is represented.
Step S30: z transformation is carried out on the integer ambiguity to-be-selected solution, and a to-be-selected function is constructed through the integer ambiguity to-be-selected solution after Z transformation;
and performing Z change on the integer ambiguity to be selected, namely processing the integer ambiguity through a change matrix Z, wherein the acquisition process of the change matrix Z is to repeatedly perform lower triangular decomposition transformation, inverse matrix change and upper triangular decomposition transformation on a covariance matrix of the integer ambiguity to be selected, and the repeated description is omitted here.
Since the covariance matrix of the integer ambiguity candidate solution is not an ideal diagonal matrix, it makes the determination of the integer ambiguity optimal solution more difficult if the candidate function is built directly through the integer ambiguity candidate solution. And the Z change is carried out through the change matrix Z, so that the correlation between the ambiguity components can be reduced to a certain extent, the covariance matrix of the integer ambiguity to be selected is optimized, and the accuracy of the integer ambiguity optimal solution is improved.
The function to be selected is:
，
wherein,representing the function to be selected->、/>All represent calculation parameters, +.>Representing the integer ambiguity after the ith Z-transform to be solved,/for selection>Representing the integer ambiguity optimal solution after Z-transformation,>and the standard deviation of the integer ambiguity optimal solution after Z transformation is shown.
It will be appreciated that the number of components,。
step S40: and constructing a primary selection space, determining a correction value through the integer ambiguity candidate solution after Z transformation, correcting the primary selection space based on the correction value to obtain an optimal selection space, and determining an integer ambiguity optimal solution through the candidate function and the optimal selection space.
In this embodiment, the volume of the primary selected space is determined by the covariance matrix of the integer ambiguity solution to be selected, the integer number of the volumes of the primary selected space is determined, and the determination of the primary selected space is completed by the correlation between the volumes of the primary selected space and the integer number.
Specifically, the correction value is:
，
wherein,indicating correction value->、/>All represent calculation parameters, +.>Representing the integer ambiguity candidate solution after Z-transformation,>representing rounding;
the optimal space to be selected is:
，
wherein,representing the optimal selection space, < >>Representing the primary selection of the space to be selected.
It can be appreciated that the relation between the function to be selected and the space to be most selected is:
，
through the above relation, it can be determined in the function to be selectedFurther by->And performing inverse transformation to obtain the integer ambiguity optimal solution. By optimizing the primary selection space, the gap between the integer ambiguity to be selected after Z transformation and the expected value can be reduced, the range of the search space is reduced, the accuracy of integer ambiguity acquisition is further improved, and the search efficiency is improved.
Referring to fig. 2, a second embodiment of the present application provides a whole-cycle ambiguity determining system for beidou positioning, which applies the whole-cycle ambiguity determining method for beidou positioning in the above embodiment, and is not described in detail. As used below, the terms "module," "unit," "sub-unit," and the like may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
The system comprises:
the computing module 10 is used for acquiring an observed value, and acquiring a whole-cycle ambiguity floating solution and a baseline vector floating solution based on the observed value;
the calculation module 10 includes:
the first unit is used for acquiring an observed value and constructing a double-difference observation equation among the whole-cycle ambiguity, the baseline vector and the observed value;
the second unit is used for carrying out least square estimation on the double difference observation equation so as to obtain a whole-cycle ambiguity floating solution and a baseline vector floating solution;
a constraint module 20, configured to apply constraint conditions to the integer ambiguity floating solution, so as to obtain an integer ambiguity solution to be selected from the integer ambiguity floating solution;
the constraint module 20 includes:
a third unit for constructing an objective function based on the integer ambiguity floating solution and the baseline vector floating solution;
a fourth unit, configured to perform least square prediction on the objective function, so as to obtain a to-be-selected solution of the integer ambiguity;
the construction module 30 is configured to perform Z-transform on the integer ambiguity candidate solution, and construct a candidate function according to the integer ambiguity candidate solution after Z-transform;
the screening module 40 is configured to construct a primary selected space, determine a correction value through the integer ambiguity candidate solution after Z transformation, correct the primary selected space based on the correction value to obtain an optimal candidate space, and determine an integer ambiguity optimal solution through the candidate function and the optimal candidate space.
The application also provides a computer, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor realizes the whole-cycle ambiguity determining method for Beidou positioning according to the technical scheme when executing the computer program.
The application also provides a storage medium, on which a computer program is stored, which when being executed by a processor implements the whole-cycle ambiguity determination method for Beidou positioning as described in the above technical scheme.
The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (7)
1. The whole-cycle ambiguity determining method for Beidou positioning is characterized by comprising the following steps of:
obtaining an observation value, and obtaining a whole-cycle ambiguity floating solution and a baseline vector floating solution based on the observation value;
applying a conditional constraint to the integer ambiguity float solution by the baseline vector float solution to obtain an integer ambiguity candidate solution from the integer ambiguity float solution;
the step of applying a conditional constraint to the integer ambiguity floating solution by the baseline vector floating solution to obtain an integer ambiguity candidate solution from the integer ambiguity floating solution includes:
constructing an objective function based on the integer ambiguity floating solution and the baseline vector floating solution;
the objective function is:
，
wherein,representing an objective function +.>Representing the integer ambiguity hypothesis, +.>Representing baseline vector hypothesis values,/->Representing the whole circumference mouldPaste floating point solution, < >>Representing baseline vector floating solution,/->Conditional expectation, indicative of a baseline vector floating solution corresponding to integer ambiguity hypothesis values, ++>Representing covariance matrix>Representing variance->Represents an n-dimensional real set, ">The number of observation frequencies is represented;
performing least square prediction on the objective function to obtain a whole-cycle ambiguity to-be-selected solution;
the integer ambiguity is to be solved as follows:
，
wherein,representing the integer ambiguity alternative solution, +.>Representing a conditional expectation of a baseline vector solution to be selected corresponding to the integer ambiguity solution to be selected;
z transformation is carried out on the integer ambiguity to-be-selected solution, and a to-be-selected function is constructed through the integer ambiguity to-be-selected solution after Z transformation;
constructing a primary selection space, determining a correction value through the integer ambiguity candidate solution after Z transformation, correcting the primary selection space based on the correction value to obtain an optimal selection space, and determining an integer ambiguity optimal solution through the candidate function and the optimal selection space;
the relation of the function to be selected and the space to be most selected is as follows:
，
wherein,representing the function to be selected->Representing the optimal candidate space.
2. The integer ambiguity determination method for Beidou positioning of claim 1, wherein the step of obtaining integer ambiguity floating solution and baseline vector floating solution based on the observations includes:
constructing a double-difference observation equation among the integer ambiguity hypothesis value, the baseline vector hypothesis value and the observation value;
and carrying out least square prediction on the double difference observation equation to obtain a whole-cycle ambiguity floating solution and a baseline vector floating solution.
3. The integer ambiguity determination method for Beidou positioning of claim 2, wherein the double difference observation equation is:
，
wherein,representing a loss function->Representing the integer ambiguity hypothesis, +.>Representing baseline vector hypothesis values,/->Representing observation noise->、/>All represent coefficient matrices;
the integer ambiguity floating solution is:
，
wherein,representing integer ambiguity floating solution, +.>Representing covariance matrix>The transpose symbol is represented by a representation,
，/>a unit array representing the number of epochs observed and the number of satellites observed;
the baseline vector floating point solution is:
，
wherein,representing a baseline vector floating solution.
4. The integer ambiguity determination method for Beidou positioning according to claim 1, wherein the function to be selected is:
，
wherein,representing the function to be selected->、/>All represent calculation parameters, +.>Representing the integer ambiguity after the ith Z-transform to be solved,/for selection>Representing the integer ambiguity optimal solution after Z-transformation,>and the standard deviation of the integer ambiguity optimal solution after Z transformation is shown.
5. The integer ambiguity determining method for Beidou positioning of claim 1, wherein the correction value is:
，
wherein,indicating correction value->、/>All represent calculation parameters, +.>Representing the integer ambiguity candidate solution after Z-transformation,>representing rounding;
the optimal space to be selected is:
，
wherein,representing the optimal selection space, < >>Representing the primary selection of the space to be selected.
6. A whole-cycle ambiguity determining system for beidou positioning, applying the whole-cycle ambiguity determining method for beidou positioning according to any one of claims 1 to 5, characterized in that the system comprises:
the calculation module is used for acquiring an observed value, and acquiring a whole-cycle ambiguity floating solution and a baseline vector floating solution based on the observed value;
the constraint module is used for applying constraint conditions to the integer ambiguity floating solution so as to obtain an integer ambiguity solution to be selected from the integer ambiguity floating solution;
the constraint module includes:
a third unit for constructing an objective function based on the integer ambiguity floating solution and the baseline vector floating solution;
the objective function is:
，
wherein,representing an objective function +.>Representing the integer ambiguity hypothesis, +.>Representing baseline vector hypothesis values,/->Representing integer ambiguity floating solution, +.>Representing baseline vector floating solution,/->Conditional expectation, indicative of a baseline vector floating solution corresponding to integer ambiguity hypothesis values, ++>Representing covariance matrix>Representing variance->Representing an n-dimensional real set，/>The number of observation frequencies is represented;
a fourth unit, configured to perform least square prediction on the objective function, so as to obtain a to-be-selected solution of the integer ambiguity;
the integer ambiguity is to be solved as follows:
，
wherein,representing the integer ambiguity alternative solution, +.>Representing a conditional expectation of a baseline vector solution to be selected corresponding to the integer ambiguity solution to be selected;
the construction module is used for carrying out Z transformation on the integer ambiguity to-be-selected solution, and constructing a to-be-selected function through the integer ambiguity to-be-selected solution after Z transformation;
the screening module is used for constructing a primary selected space, determining a correction value through the integer ambiguity to be selected after Z transformation, correcting the primary selected space based on the correction value to obtain an optimal space to be selected, and determining an integer ambiguity optimal solution through the function to be selected and the optimal space to be selected;
the relation of the function to be selected and the space to be most selected is as follows:
，
wherein,representing the function to be selected->Representing the optimal candidate space.
7. A computer comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the whole-cycle ambiguity determination method for Beidou positioning according to any one of claims 1 to 5 when executing the computer program.
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