CN111381264A - Long baseline ambiguity fixing method and platform in network RTK - Google Patents
Long baseline ambiguity fixing method and platform in network RTK Download PDFInfo
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- CN111381264A CN111381264A CN201811613933.2A CN201811613933A CN111381264A CN 111381264 A CN111381264 A CN 111381264A CN 201811613933 A CN201811613933 A CN 201811613933A CN 111381264 A CN111381264 A CN 111381264A
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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
Abstract
The invention provides a method and a platform for fixing long baseline ambiguity in network RTK (real-time kinematic), wherein the method comprises the following steps: acquiring a dual-frequency pseudo-range observation value and dual-frequency carrier phase observation data transmitted by a reference station; acquiring a floating solution of double-difference wide lane combined ambiguity according to the double-frequency pseudo-range observed value and the double-frequency carrier phase observed data; obtaining a fixed solution corresponding to a floating solution of the double-difference wide lane combined ambiguity according to a data optimization algorithm; and obtaining a fixed solution corresponding to the floating solution of the single-frequency ambiguity according to the fixed solution corresponding to the floating solution of the double-difference wide-lane combined ambiguity. Thereby improving the fixation rate and reliability of the medium and long baseline ambiguity.
Description
Technical Field
The invention relates to the technical field of satellite navigation, in particular to a method and a platform for fixing long baseline ambiguity in network RTK.
Background
The Real Time Kinematic (RTK) technique is to uniformly establish a plurality of Global Positioning System (GPS) reference stations in a certain area to realize mesh coverage of the area. During positioning, one or more of the reference stations are used as reference, correction item information of the positioning data is calculated in real time, and finally the correction item information obtained through calculation is continuously issued to a user in real time through a communication link, so that the user side can obtain a high-precision real-time positioning result. In network RTK, however, it is a very critical step to solve the ambiguity value on the base line between the reference stations, which directly determines the reliability of the correction item information.
At present, in the medium-long baseline mode, a double-differenced pseudorange and carrier phase (MW) combination is generally adopted, and ambiguity values on baselines between reference stations are obtained through a multi-epoch smoothing method.
However, the above method requires smoothing of multiple epochs to obtain a stable floating point value, and if the quality of the original data acquired by the receiver is poor, it is difficult to obtain a stable floating point value even by smoothing of multiple epochs, so that the ambiguity value on the baseline between the reference stations has poor fixation rate and low reliability.
Disclosure of Invention
The invention provides a method and a platform for fixing a long and medium baseline ambiguity in network RTK (real-time kinematic), which are used for improving the fixing rate and the reliability of the long and medium baseline ambiguity.
In a first aspect, an embodiment of the present invention provides a method for fixing a long baseline ambiguity in network RTK, including:
acquiring a dual-frequency pseudo-range observation value and dual-frequency carrier phase observation data transmitted by a reference station;
acquiring a floating solution of double-difference wide lane combined ambiguity according to the double-frequency pseudo-range observed value and the double-frequency carrier phase observed data;
obtaining a fixed solution corresponding to a floating solution of the double-difference wide lane combined ambiguity according to a data optimization algorithm; and obtaining a fixed solution corresponding to the floating solution of the single-frequency ambiguity according to the fixed solution corresponding to the floating solution of the double-difference wide-lane combined ambiguity.
In a second aspect, an embodiment of the present invention provides a long baseline ambiguity fixing platform in network RTK, including:
the receiving and transmitting module is used for acquiring a dual-frequency pseudo-range observation value and dual-frequency carrier phase observation data sent by a reference station;
the processing module is used for acquiring a floating solution of the double-difference wide lane combined ambiguity according to the double-frequency pseudo-range observation value and the double-frequency carrier phase observation data;
obtaining a fixed solution corresponding to a floating solution of the double-difference wide lane combined ambiguity according to a data optimization algorithm; and acquiring a fixed solution corresponding to the floating solution of the single-frequency ambiguity according to the fixed solution corresponding to the floating solution of the double-difference wide-lane combined ambiguity.
In a third aspect, an embodiment of the present invention provides a cloud platform, including:
a memory for storing a program;
a processor for executing the program stored by the memory, the processor being configured to perform the method of any of the first aspects when the program is executed.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, including: computer program, which, when run on a computer, causes the computer to perform the method of any of the first aspects.
According to the method and the platform for fixing the long baseline ambiguity in the network RTK, the double-frequency pseudo range observation value and the double-frequency carrier phase observation data sent by the reference station are obtained; acquiring a floating solution of double-difference wide lane combined ambiguity according to the double-frequency pseudo-range observed value and the double-frequency carrier phase observed data; obtaining a fixed solution corresponding to a floating solution of the double-difference wide lane combined ambiguity according to a data optimization algorithm; and obtaining a fixed solution corresponding to the floating solution of the single-frequency ambiguity according to the fixed solution corresponding to the floating solution of the double-difference wide-lane combined ambiguity. Therefore, the fixed rate and the reliability of the medium-long baseline ambiguity are effectively improved, the stable estimation of the medium-long baseline (30-150 km) ambiguity is realized, the construction number of the reference stations is reduced, the station construction cost is saved, and the economic benefit is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic structural diagram of an application scenario according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for fixing a long baseline ambiguity in network RTK according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of a long baseline ambiguity fixed platform in network RTK according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of a long baseline ambiguity fixed platform in network RTK according to a fourth embodiment of the present invention;
fig. 5 is a schematic structural diagram of a cloud platform according to a fourth embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, 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 some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The technical solution of the present invention will be described in detail below with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.
In the following, some terms in the present application are explained to facilitate understanding by those skilled in the art:
1) the carrier-time kinematic (RTK) is a system for performing Real-time navigation and positioning in a global area by using satellites. The difference method for processing the observed quantity of the carrier phases of the two reference stations in real time sends the carrier phases acquired by the reference stations to a user receiver, and calculates the coordinates by calculating the difference. The method is a new common Global Positioning System (GPS) measurement method, the former static, fast static and dynamic measurements all need to be solved afterwards to obtain centimeter-level accuracy, the RTK is a measurement method capable of obtaining centimeter-level positioning accuracy in real time in the field, a carrier phase dynamic real-time difference method is adopted, the method is a great milestone applied by the GPS, the appearance of the method is project lofting and terrain mapping, new eosin is brought for various control measurements, and the operation efficiency is greatly improved.
2) Network RTK is a new technology established on the basis of conventional RTK and differential GPS in recent years, and is still in the experimental and development stages at present. Positioning systems that establish multiple (typically three or more) GPS reference stations within an area, form a mesh coverage of the area, and calculate and transmit GPS correction information based on one or more of the reference stations to correct GPS users in the area in real time are commonly referred to as GPS network RTKs, also known as multi-reference RTKs. The basic principle of the method is that a plurality of reference stations are sparsely and uniformly distributed in a larger area to form a reference station network, and then the basic principle and method in the wide area differential GPS and the local area differential GPS with a plurality of reference stations are used for seeking to eliminate or weaken the influence of various system errors, so that a high-precision positioning result is obtained.
3) Virtual Reference States (VRS) are the technologies mainly used in the development of the current network carrier phase differential technology (RTK), and the basic principle of VRS operation is as follows: in the coverage range of three or more reference stations, a user sends a self-positioning result (single-point positioning, deviation more than meter level) to a data processing center through a wireless data link, meanwhile, the data processing center carries out data processing according to observation data of each reference station, base line ambiguity parameters and the like are solved, an error source influencing positioning is modeled and calculated, then various error correction numbers at corresponding positions are calculated by combining rough positions sent by the user, finally, one reference station is obtained in a virtual mode at the rough positions, observation data of the reference station are calculated in a simulated mode, and then the simulated data are sent to the user. And the user uses the data of the virtual reference station to carry out short baseline differential calculation to obtain position information with centimeter-level precision.
Fig. 1 is a schematic structural diagram of an application scenario provided in an embodiment of the present invention, as shown in fig. 1, including: the cloud platform 10, the rover station 20, the reference station group 30 includes: three and more reference stations 31. The cloud platform 10 acquires the current position data of the user from the rover station 20, and selects observation data of at least 3 reference stations from the reference station group 30 according to the current position data of the user. The cloud platform 10 calculates the integer ambiguity between the reference stations based on the selected observation data of each reference station. The cloud platform 10 corrects the current position data of the flow station 20 through the calculated integer ambiguity between the reference stations, and establishes a virtual reference station at the current position of the flow station 20. Finally, the cloud platform 10 simulates observation data of the virtual reference station and sends the observation data to the rover station 20, so that position information with centimeter-level accuracy can be obtained. Optionally, the cloud platform 10 performs classification modeling on the error sources according to the integer ambiguity between the selected reference stations, and interpolates to obtain the differential correction value of the virtual reference station. The calculated differential corrections are then sent to the rover station 20 in the standard RTCM protocol so that the rover station 20 performs differential positioning based on the differential corrections. In this embodiment, the rover station 20 may be a terminal with a positioning function, such as a smart phone, a smart watch, a tablet computer, and the like.
The following describes the technical solutions of the present invention and how to solve the above technical problems with specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present invention will be described below with reference to the accompanying drawings.
Fig. 2 is a flowchart of a method for fixing a long baseline ambiguity in network RTK according to a second embodiment of the present invention, as shown in fig. 2, the method in this embodiment may include:
s101, obtaining a dual-frequency pseudo-range observation value and dual-frequency carrier phase observation data sent by a reference station.
In the embodiment, firstly, a double-difference observation equation of a medium-long baseline is constructed; the double-difference observation equation for the medium-long baseline is as follows:
wherein the content of the first and second substances,
is a double-difference carrier observed quantity, lambda, between stations and starskIs the carrier wavelength of the k frequency point,
the unit is the inter-station inter-satellite double-difference carrier observed quantity: the number of weeks;
is the double-difference geometric distance between the satellites of the stations,
is the inter-station inter-satellite double-difference ionosphere residual error,
is the interstation intersatellite double-difference troposphere residual error, lambdakIs the carrier wavelength of the k frequency point,
is the double-difference ambiguity between the interstation stars, unit: the number of weeks; epsilonφNoise residuals are measured for inter-station inter-satellite carrier phases,
the double-difference pseudo range observed quantity between the stations is obtained; epsilonpThe method is characterized in that inter-station inter-satellite pseudo-range measurement noise residual errors are represented, i is a reference satellite label, and the value range of i is as follows: 1 to 32; j is a non-reference satellite label, and the value range of j is as follows: 1 to 32; k is a satellite frequency point, and the value range of k is as follows: 1-3; subscript r denotes the secondary reference station on the baseline, and subscript b denotes the primary reference station on the baseline.
In this embodiment, through the double-difference observation equation of the medium and long base lines, the residual error of the interstation double-difference troposphere on the base line can be accurately solved by combining the accurately obtained meteorological data according to the existing troposphere residual error, the base line ambiguity floating point solution precision is further improved by eliminating the solved double-difference troposphere residual error, and the ambiguity fixing rate and the ambiguity fixing reliability can be effectively improved.
Then, simulating a residual relative ionosphere by adopting a Gaussian Markov process, and estimating a double-difference ionosphere residual error; simulating a satellite troposphere on a reference station through a Saastamoinen model, and estimating double-difference troposphere residual errors between the reference stations; the double difference tropospheric residual calculation formula is as follows:
wherein:
is the interstation inter-satellite double-difference troposphere residual error,
for reference to the current layer values of the satellite master station,
for non-reference satellite masters to flow layer values,
for reference to the satellite secondary station convective layer values,
and the flow layer value is a non-reference station secondary station. The Saastamoinen model requires accurate meteorological data from a reference station, such as: the constructed reference station can acquire accurate meteorological parameter data through meteorological network data or a meteorological measurement method; wherein, the satellite troposphere on the used reference station can be obtained through a model.
Further, the double-frequency pseudo range observation value sent by the selected reference station, the carrier parameter corresponding to the double-frequency carrier phase observation data, the double-difference ionosphere residual error and the double-difference troposphere residual error are substituted into a double-difference observation equation of a medium-long baseline to obtain the inter-satellite double-difference ambiguity between stations
And finally, constructing a resolving equation of the double-difference wide lane combined ambiguity between the reference stations, wherein the resolving equation of the double-difference wide lane combined ambiguity between the reference stations is as follows:
wherein: n is a radical ofKFor combining double-difference ambiguities, N, between frequency points1Is a 1-frequency point double-difference ambiguity, N2Is a 2-frequency point double-difference ambiguity, f1Is a frequency point of 1, f2Is a 2-frequency point carrier frequency rho1Is a 1-frequency point double-difference pseudo-range observed quantity, lambda1At 1 frequency point carrier wavelength, p2Is a 2-frequency point double-difference pseudo-range observed quantity, lambda2Is a 2-frequency point carrier wavelength, L1Is 1 frequencyPoint double difference carrier observations, L2Is a 2-frequency point double-difference carrier observed quantity.
In this example, N isK＝N1-N2,N1Correspond to
I.e. double-difference ambiguity of frequency point 1, N2Correspond to
I.e. the double-difference ambiguity at frequency point 2.
Optionally, before executing step S101, the dual-frequency carrier phase observed quantity data may be preprocessed to obtain a characteristic parameter of the dual-frequency carrier phase observed quantity data, where the characteristic parameter includes: signal elevation, carrier-to-noise ratio, observation noise; and removing the dual-frequency carrier phase observed quantity data with the characteristic parameters not within the preset threshold range.
In this embodiment, an ionosphere estimation technique may be used for existing ionosphere residuals, and each epoch estimates a single-difference residual value between ionosphere stations while performing ambiguity floating solution filtering, so that ambiguity floating solution accuracy may be effectively improved, and accurate fixing of ambiguity may be realized more quickly. In addition, by setting the reference ionosphere constraint value, the satellite ambiguity of the ionosphere solution anomaly can be prevented from participating in the subsequent fixation, so that the ambiguity fixation rate and the ambiguity fixation reliability are further improved.
S102, obtaining a floating solution of the double-difference wide-lane combined ambiguity according to the double-frequency pseudo-range observed value and the double-frequency carrier phase observed data.
In an optional implementation manner, a solution equation of double-difference wide-lane combination ambiguity can be constructed according to the double-frequency pseudo-range observation value and the double-frequency carrier phase observation data; and then, solving a resolving equation of the double-difference wide lane combined ambiguity by adopting a filtering algorithm to obtain a floating solution of the double-difference wide lane combined ambiguity.
In this embodiment, a kalman filtering algorithm may be adopted to solve the solution equation of the double-difference wide-lane combined ambiguity to obtain a floating solution of the double-difference wide-lane combined ambiguity.
Specifically, the kalman filter equation is as follows:
wherein: w is akObeying a normal distribution N (0, Q)k)，ekObeying a normal distribution N (0, R)k)，QkIs the state transition noise variance, RkTo measure the variance of the noise, k is the number of equations. XkFor state prediction at the present moment, Xk-1Is the last moment state quantity, phik,k-1Being a state transition matrix, wkIs a systematic error vector, Γk,k-1Is a unit array, YkFor the observed quantity at the present moment, AkCharacterizing the relationship between the state quantity and the observed quantity as a coefficient matrix, ekIs an observation error vector.
In double-difference wide-lane combined ambiguity filtering, XkFor double-frequency combined double-difference ambiguity floating solution and single-difference residual value between ionosphere stations, k represents a certain available satellite (non-reference satellite), YkCombining dual differential observations residuals (pseudoranges, carriers), Q, for frequency pointsk、RkMay be derived from a real-time filtering process.
In this embodiment, a single-frequency non-combined ambiguity floating solution is resolved by using kalman filtering, and for an existing ionospheric residual, an ionospheric estimation technique is used, and each epoch estimates a single-difference residual value between ionospheric stations while filtering the ambiguity floating solution. Therefore, the ambiguity floating solution precision can be effectively improved, and the ambiguity can be accurately fixed more quickly. In addition, by setting a reference ionosphere constraint value, the ionosphere solves abnormal satellite ambiguity without participating in subsequent fixation, so that the ambiguity fixation rate and the ambiguity fixation reliability can be effectively improved. Specifically, when parameter estimation is performed using a filter equation, it is necessary to empirically give an initial ionospheric delay given by Ii(t0)10-6Rice, wherein t0Representing the initial time, standard deviation of 0.03 × lb×10-4Rice (10km, 3 cm).
S103, obtaining a fixed solution corresponding to the floating solution of the double-difference wide-lane combined ambiguity according to a data optimization algorithm.
In this embodiment, an integer least square method may be adopted to obtain a fixed solution corresponding to the floating solution of the double-difference wide-lane combined ambiguity. The integer least squares method provides a method for transition of ambiguity from a floating solution (real solution) to an integer solution, and no numerical solution exists, and the currently mainstream method is a search method, namely, a search for discrete integer points. In this embodiment, a practical search technique based on integer least squares estimation is not limited (for example, FARA, FASF, and LAMBDA may be used), and the LAMBDA method is used in the present method. The resolution of the integer ambiguity mainly has three steps. The first step is to generate all possible integer ambiguity combinations from an algorithm point of view; secondly, searching out a correct ambiguity combination; the third step is the examination of the ambiguity integer solution.
And S104, obtaining a fixed solution corresponding to the floating solution of the single-frequency ambiguity according to the fixed solution corresponding to the floating solution of the double-difference wide-lane combined ambiguity.
In an optional implementation manner, the floating solution of the single-frequency ambiguity may be obtained according to a solving equation of a fixed solution and a single-frequency ambiguity corresponding to the floating solution of the double-difference wide-lane combined ambiguity; acquiring single-difference residual values between ionospheric stations corresponding to the floating solutions of the single-frequency ambiguities; judging whether the single-difference residual value between the ionospheric stations is within a preset constraint range, and if not, rejecting a floating solution of a corresponding single-frequency ambiguity; and if so, acquiring a fixed solution corresponding to the floating solution of the single-frequency ambiguity according to an optimization algorithm.
In this embodiment, a fixed solution corresponding to a floating solution of the double-difference wide-lane combined ambiguity may be substituted into a solution equation of the single-frequency ambiguity, and the solution equation of the single-frequency ambiguity may be solved through a kalman filter algorithm to obtain the floating solution of the single-frequency ambiguity.
Specifically, the solution equation for single frequency ambiguity is as follows:
Ns＝ρs-Ls-ΔIs
wherein: n is a radical ofsIs the double-difference ambiguity of s frequency points, rhosIs s frequency point inter-station double-difference pseudo range observed quantity, LsIs s-frequency point inter-station double-difference carrier observed quantity, delta IsAnd the ionospheric estimate is taken as the s frequency point, and s is taken as the satellite frequency point.
In this embodiment, a relatively long ambiguity wide-lane solution with a relatively long wavelength can be formed by combining different frequency point observations according to the characteristic that the satellite receiver on the reference station is a multi-frequency receiver. Because the wide-lane ambiguity resolution wavelength is relatively long, the wide-lane ambiguity is easier to fix, and is fixed before the single-frequency ambiguity. The method comprises the steps of firstly fixing the ambiguity of the wide lane, and then substituting a fixed solution of the ambiguity of the wide lane into a resolving equation with fixed single-frequency ambiguity. By adopting the method in the embodiment, the fixation of the single-frequency point ambiguity can be effectively accelerated, and the fixed initialization time of the ambiguity is prolonged.
In this embodiment, an integer least square method may be adopted to obtain a fixed solution corresponding to a floating solution of a single-frequency ambiguity. The integer least squares method provides a method for transition of ambiguity from a floating solution (real solution) to an integer solution, and no numerical solution exists, and the currently mainstream method is a search method, namely, a search for discrete integer points. In this embodiment, a practical search technique based on integer least squares estimation is not limited (for example, FARA, FASF, and LAMBDA may be used), and the LAMBDA method is used in the present method. The resolution of the integer ambiguity mainly has three steps. The first step is to generate all possible integer ambiguity combinations from an algorithm point of view; secondly, searching out a correct ambiguity combination; the third step is the examination of the ambiguity integer solution.
In an alternative embodiment, the solution equations for the single-frequency ambiguities may be characterized in a matrix form; then solving a resolving equation representing the single-frequency ambiguity in a matrix form according to a filtering algorithm; and for a symmetric matrix in a resolving equation of the single-frequency ambiguity, storing matrix elements of an upper triangle in the symmetric matrix so as to rapidly access the resolving mode of the single-frequency ambiguity.
Specifically, a solving equation of the single-frequency ambiguity can be represented in a matrix form; for a symmetric matrix in a resolving equation of single-frequency ambiguity, only storing the matrix elements of an upper triangle in the symmetric matrix when the matrix elements of the symmetric matrix are stored; and then solving a resolving equation for representing the single-frequency ambiguity in a matrix form by a Kalman filtering algorithm.
Specifically, a matrix calculation efficiency optimization technology is used, namely a storage scheme for storing only upper triangular elements (including diagonal elements) is adopted to store the symmetric matrix, and only the upper triangular elements are stored in the array in sequence. And restoring the subscript of the symmetric matrix through the storage position of the matrix element in the array, thereby restoring the original symmetric matrix. Through an optimization technology, the number of matrix elements can be changed from N2And the compression is carried out to N x (N +1)/2, so that the storage space is greatly saved, unnecessary repeated calculation is avoided, and the efficiency of engineering realization is improved.
In this embodiment, due to the addition of the ionosphere single difference parameter, the unknown quantity parameter of the filtering equation is increased, the order of the filtering matrix is increased, and the resolving efficiency is affected. Therefore, a software optimization technology can be adopted, a calculation method is optimized according to the characteristics of the symmetric matrix, the calculation efficiency is effectively improved, and the calculation burden is reduced.
In this embodiment, a dual-frequency pseudo-range observation value and dual-frequency carrier phase observation data sent by a reference station are obtained; acquiring a floating solution of double-difference wide lane combined ambiguity according to the double-frequency pseudo-range observed value and the double-frequency carrier phase observed data; obtaining a fixed solution corresponding to a floating solution of the double-difference wide lane combined ambiguity according to a data optimization algorithm; and obtaining a fixed solution corresponding to the floating solution of the single-frequency ambiguity according to the fixed solution corresponding to the floating solution of the double-difference wide-lane combined ambiguity. Therefore, the fixed rate and the reliability of the medium-long baseline ambiguity are effectively improved, the stable estimation of the medium-long baseline (30-150 km) ambiguity is realized, the construction number of the reference stations is reduced, the station construction cost is saved, and the economic benefit is improved.
Fig. 3 is a schematic structural diagram of a long baseline ambiguity fixed platform in network RTK according to a third embodiment of the present invention, and as shown in fig. 3, the platform in this embodiment may include:
the transceiver module 41 is configured to obtain a dual-frequency pseudo-range observation value and dual-frequency carrier phase observation data sent by a reference station; the transceiver module 41 may be a transceiver or an interface;
the processing module 42 is configured to obtain a floating solution of the double-difference wide-lane combined ambiguity according to the double-frequency pseudo-range observed value and the double-frequency carrier phase observed data; the processing module 42 may be a processor or a controller;
obtaining a fixed solution corresponding to a floating solution of the double-difference wide lane combined ambiguity according to a data optimization algorithm; and acquiring a fixed solution corresponding to the floating solution of the single-frequency ambiguity according to the fixed solution corresponding to the floating solution of the double-difference wide-lane combined ambiguity.
Optionally, the processing module 42 is specifically configured to:
constructing a resolving equation of double-difference wide-lane combination ambiguity according to the double-frequency pseudo-range observed value and the double-frequency carrier phase observed data;
and solving a resolving equation of the double-difference wide lane combined ambiguity by adopting a filtering algorithm to obtain a floating solution of the double-difference wide lane combined ambiguity.
Optionally, the processing module 42 is specifically configured to:
obtaining a floating solution of the single-frequency ambiguity according to a solving equation of a fixed solution and the single-frequency ambiguity corresponding to the floating solution of the double-difference wide lane combined ambiguity;
acquiring single-difference residual values between ionospheric stations corresponding to the floating solutions of the single-frequency ambiguities;
judging whether the single-difference residual value between the ionospheric stations is within a preset constraint range, and if not, rejecting a floating solution of a corresponding single-frequency ambiguity; and if so, acquiring a fixed solution corresponding to the floating solution of the single-frequency ambiguity according to an optimization algorithm.
Optionally, obtaining a floating solution of the single-frequency ambiguity according to a solution equation of the single-frequency ambiguity and a fixed solution corresponding to the floating solution of the double-difference wide-lane combined ambiguity includes:
characterizing a solving equation of the single-frequency ambiguity in a matrix form;
solving a resolving equation for representing the single-frequency ambiguity in a matrix form according to a filtering algorithm;
and for a symmetric matrix in a resolving equation of the single-frequency ambiguity, storing matrix elements of an upper triangle in the symmetric matrix so as to rapidly access the resolving mode of the single-frequency ambiguity.
It should be noted that the platform in this embodiment may be formed by one server, or may be a server cluster formed by a plurality of servers, or may be a software system platform.
The embodiment may execute the technical solution in the method shown in fig. 2, and the implementation process and the technical effect are similar to those of the method, which are not described herein again.
Fig. 4 is a schematic structural diagram of a long baseline ambiguity fixed platform in network RTK according to a fourth embodiment of the present invention, and as shown in fig. 4, the apparatus in this embodiment may further include, on the basis of the platform shown in fig. 3:
a preprocessing module 43, configured to obtain a characteristic parameter of the dual-frequency carrier phase observed quantity data according to the dual-frequency carrier phase observed quantity data, where the characteristic parameter includes: signal elevation, carrier-to-noise ratio, observation noise; and eliminating the dual-frequency carrier phase observed quantity data corresponding to the characteristic parameters which are not in the preset threshold range.
The embodiment may execute the technical solution in the method shown in fig. 2, and the implementation process and the technical effect are similar to those of the method, which are not described herein again.
Fig. 5 is a schematic structural diagram of a cloud platform according to a fourth embodiment of the present invention, and as shown in fig. 5, a cloud platform 50 in this embodiment includes: a processor 51 and a memory 52;
a memory 52 for storing computer programs (e.g., applications, functional modules, etc. that implement the above-described methods), computer instructions, etc., which may be stored in one or more of the memories 52 in a partitioned manner. And the above-mentioned computer program, computer instructions, data, etc. can be called by the processor 51.
A processor 51 for executing the computer program stored in the memory 52 to implement the steps of the method according to the above embodiments. Reference may be made in particular to the description relating to the preceding method embodiment. The memory 52 and the processor 51 may be coupled via a bus 53.
Optionally, the processor 51 is further configured to perform any one or more of the following:
sending real-time differential data to a terminal so that the terminal can perform high-precision positioning according to the differential data;
monitoring a satellite positioning system in real time, identifying the satellite positioning system with a fault when the satellite positioning system has the fault, and sending reminding information to a client side served by the satellite positioning system;
and fitting the troposphere situation above the coverage area of the reference station by combining the troposphere data observed by a plurality of reference station satellites, and performing inversion on the real-time meteorological data above the coverage area of the reference station.
The embodiment may execute the technical solution in the method shown in fig. 2, and the implementation process and the technical effect are similar to those of the method, which are not described herein again.
In addition, embodiments of the present application further provide a computer-readable storage medium, in which computer-executable instructions are stored, and when at least one processor of the user equipment executes the computer-executable instructions, the user equipment performs the above-mentioned various possible methods.
Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an ASIC. Additionally, the ASIC may reside in user equipment. Of course, the processor and the storage medium may reside as discrete components in a communication device.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (12)
1. A method for fixing long baseline ambiguity in network RTK is characterized by comprising the following steps:
acquiring a dual-frequency pseudo-range observation value and dual-frequency carrier phase observation data transmitted by a reference station;
acquiring a floating solution of double-difference wide lane combined ambiguity according to the double-frequency pseudo-range observed value and the double-frequency carrier phase observed data;
obtaining a fixed solution corresponding to a floating solution of the double-difference wide lane combined ambiguity according to a data optimization algorithm;
and obtaining a fixed solution corresponding to the floating solution of the single-frequency ambiguity according to the fixed solution corresponding to the floating solution of the double-difference wide-lane combined ambiguity.
2. The method of claim 1, further comprising, prior to obtaining dual-frequency pseudorange observations and dual-frequency carrier-phase observations transmitted by a reference station:
obtaining characteristic parameters of the dual-frequency carrier phase observed quantity data according to the dual-frequency carrier phase observed quantity data, wherein the characteristic parameters comprise: signal elevation, carrier-to-noise ratio, observation noise;
and eliminating the dual-frequency carrier phase observed quantity data corresponding to the characteristic parameters which are not in the preset threshold range.
3. The method of claim 1, wherein obtaining a floating solution for double-differenced wide-lane combined ambiguity from the dual-frequency pseudorange observations and dual-frequency carrier-phase observations comprises:
constructing a resolving equation of double-difference wide-lane combination ambiguity according to the double-frequency pseudo-range observed value and the double-frequency carrier phase observed data;
and solving a resolving equation of the double-difference wide lane combined ambiguity by adopting a filtering algorithm to obtain a floating solution of the double-difference wide lane combined ambiguity.
4. The method according to any one of claims 1-3, wherein obtaining a fixed solution corresponding to a floating solution of single-frequency ambiguities from a fixed solution corresponding to a floating solution of the double-difference wide-lane combined ambiguities comprises:
obtaining a floating solution of the single-frequency ambiguity according to a solving equation of a fixed solution and the single-frequency ambiguity corresponding to the floating solution of the double-difference wide lane combined ambiguity;
acquiring single-difference residual values between ionospheric stations corresponding to the floating solutions of the single-frequency ambiguities;
judging whether the single-difference residual value between the ionospheric stations is within a preset constraint range, and if not, rejecting a floating solution of a corresponding single-frequency ambiguity; and if so, acquiring a fixed solution corresponding to the floating solution of the single-frequency ambiguity according to an optimization algorithm.
5. The method of claim 4, wherein obtaining the single-frequency ambiguity float solution according to a solution equation of a single-frequency ambiguity and a fixed solution corresponding to the float solution of the double-difference wide-lane combined ambiguity comprises:
characterizing a solving equation of the single-frequency ambiguity in a matrix form;
solving a resolving equation for representing the single-frequency ambiguity in a matrix form according to a filtering algorithm;
and for a symmetric matrix in a resolving equation of the single-frequency ambiguity, storing matrix elements of an upper triangle in the symmetric matrix so as to rapidly access the resolving mode of the single-frequency ambiguity.
6. A long baseline ambiguity fixed platform in network RTK, comprising:
the receiving and transmitting module is used for acquiring a dual-frequency pseudo-range observation value and dual-frequency carrier phase observation data sent by a reference station;
the processing module is used for acquiring a floating solution of the double-difference wide lane combined ambiguity according to the double-frequency pseudo-range observation value and the double-frequency carrier phase observation data; obtaining a fixed solution corresponding to a floating solution of the double-difference wide lane combined ambiguity according to a data optimization algorithm; and acquiring a fixed solution corresponding to the floating solution of the single-frequency ambiguity according to the fixed solution corresponding to the floating solution of the double-difference wide-lane combined ambiguity.
7. The platform of claim 6, further comprising:
the preprocessing module is configured to obtain a characteristic parameter of the dual-frequency carrier phase observed quantity data according to the dual-frequency carrier phase observed quantity data, where the characteristic parameter includes: signal elevation, carrier-to-noise ratio, observation noise;
and eliminating the dual-frequency carrier phase observed quantity data corresponding to the characteristic parameters which are not in the preset threshold range.
8. The platform of claim 6, wherein the processing module is specifically configured to:
constructing a resolving equation of double-difference wide-lane combination ambiguity according to the double-frequency pseudo-range observed value and the double-frequency carrier phase observed data;
and solving a resolving equation of the double-difference wide lane combined ambiguity by adopting a filtering algorithm to obtain a floating solution of the double-difference wide lane combined ambiguity.
9. The platform according to any one of claims 6 to 8, wherein the processing module is specifically configured to:
obtaining a floating solution of the single-frequency ambiguity according to a solving equation of a fixed solution and the single-frequency ambiguity corresponding to the floating solution of the double-difference wide lane combined ambiguity;
acquiring single-difference residual values between ionospheric stations corresponding to the floating solutions of the single-frequency ambiguities;
judging whether the single-difference residual value between the ionospheric stations is within a preset constraint range, and if not, rejecting a floating solution of a corresponding single-frequency ambiguity; and if so, acquiring a fixed solution corresponding to the floating solution of the single-frequency ambiguity according to an optimization algorithm.
10. The platform of claim 9, wherein obtaining the single-frequency ambiguity float solution according to a fixed solution and a single-frequency ambiguity solution equation corresponding to the double-difference wide-lane combined ambiguity float solution comprises:
characterizing a solving equation of the single-frequency ambiguity in a matrix form;
solving a resolving equation for representing the single-frequency ambiguity in a matrix form according to a filtering algorithm;
and for a symmetric matrix in a resolving equation of the single-frequency ambiguity, storing matrix elements of an upper triangle in the symmetric matrix so as to rapidly access the resolving mode of the single-frequency ambiguity.
11. A cloud platform, comprising:
a memory for storing a program;
a processor for executing the program stored by the memory, the processor being configured to perform the method of any of claims 1-5 when the program is executed.
12. The cloud platform of claim 11, wherein the processor is further configured to perform any one or more of:
sending real-time differential data to a terminal so that the terminal can perform high-precision positioning according to the differential data;
monitoring a satellite positioning system in real time, identifying the satellite positioning system with a fault when the satellite positioning system has the fault, and sending reminding information to a client side served by the satellite positioning system;
and fitting the troposphere situation above the coverage area of the reference station by combining the troposphere data observed by a plurality of reference station satellites, and performing inversion on the real-time meteorological data above the coverage area of the reference station.
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