CN108415049B - Method for improving network RTK double-difference wide lane ambiguity fixing accuracy - Google Patents
Method for improving network RTK double-difference wide lane ambiguity fixing accuracy Download PDFInfo
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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 for improving network RTK double-difference wide lane ambiguity fixing accuracy, which comprises the following steps: step 1, data preparation: receiving real-time observation data of a GNSS reference station, satellite ephemeris and coordinate information of the reference station; step 2, calculating a real-time ionosphere product: according to the coordinate information of the reference station and the satellite coordinates, performing non-differential precise point positioning on the reference station, and calculating a non-differential real-time ionospheric delay value of a satellite signal propagation path; step 3, calculating the ambiguity of the baseline double-difference wide lane, comprising the following steps: step 3.1, forming double-difference observation values by the observation data of the two reference stations, and correcting the double-difference ionospheric residue items by using the non-difference real-time ionospheric delay values calculated in the step 2; step 3.2, calculating a floating solution of double-difference wide lane ambiguity; and 3.3, performing rounding on the floating-point solution of the double-difference widelane ambiguity to obtain the double-difference widelane ambiguity integer. The invention improves the accuracy of calculating the ambiguity of the baseline double-difference wide lane, thereby improving the precision and the stability of the network RTK.
Description
Technical Field
The invention relates to the technical field of satellite positioning systems and positioning measurement, in particular to a method for improving network RTK double-difference wide lane ambiguity fixing accuracy.
Background
The VRS (Virtual Reference Station) mode is the most common positioning mode for network RTK (Real-Time Kinematic) positioning. A plurality of (3 or more than 3) GNSS (Global Navigation Satellite System) satellites continuously track reference stations (or called base stations and reference stations) in a certain area, and a mesh coverage is formed for the area, so that real-time high-precision error correction information is provided for positioning users in the area, and the positioning precision of the users is improved, which is called as a network RTK technology. The virtual observation value of the virtual reference station is corrected by utilizing the virtual observation value of the virtual reference station, so that a relatively accurate virtual observation value can be obtained. The user can finally perform a differential positioning with this virtual reference station in his vicinity using conventional RTK techniques. Since the virtual reference station is very close to the user, this distance (typically less than 10 meters, determined by the single point positioning accuracy) does not affect the performance of conventional RTK positioning techniques. One of the key factors in the quality of network RTK services is the accuracy of the virtual observations of the virtual reference stations, which depends on the accuracy of the error correction. The correctness of the baseline double-difference ambiguity is one of the key factors of the error correction precision, and the improvement of the correctness of the baseline double-difference ambiguity can improve the error correction precision of the virtual reference station, so that the precision and the stability of the network RTK positioning can be improved.
The existing baseline double-difference ambiguity resolution method generally resolves double-difference wide-lane ambiguity firstly, then resolves double-difference narrow-lane ambiguity to obtain baseline double-difference ambiguity, and then can resolve the baseline double-difference atmosphere. The existing basic linewidth lane ambiguity resolution method generally comprises a phase linear combination method, a MW combination method and a three-frequency ultra-wide lane combination method, and the three methods have the following problems:
1. the existing phase linear combination method only uses the linear combination of observed values of double-frequency phases, and then solves the widelane ambiguity. Because the wavelength of the widelane ambiguity is longer, about 0.86 m, and for a base line shorter, for example within 20 km, most residual error terms are less than half the wavelength of 0.43 m through double differences of observation value sets, and the widelane ambiguity can be easily obtained through smooth rounding of a plurality of epochs. However, the method is only suitable for a short baseline, and in a long baseline or an ionosphere active time period, a residual error term often exceeds half wavelength of the widelane ambiguity, so that the correct fixation of the widelane ambiguity is influenced.
2. The MW combination method is a linear combination of two types of observed values of double-frequency pseudo range and phase, and by adopting the MW combination, a troposphere, an ionosphere and a geometric term can be eliminated, and only observation noise and multipath errors are remained. After smoothing of a plurality of epochs, the total error is generally less than half a wavelength of the widelane ambiguity, and a correct value of the widelane ambiguity can be obtained. The MW combination utilizes a pseudo range observation value with low precision, and when observation noise of a pseudo range is large or a multi-path error is large, it is difficult to ensure that a total error is less than half a wavelength of the ambiguity of the wide lane, and correct fixation of the double-difference ambiguity of the wide lane is influenced.
3. The method can obtain the ultra-wide lane ambiguity with longer wavelength by a three-frequency ultra-wide lane combination method, and then the ultra-wide lane ambiguity is used for calculating the wide lane ambiguity. The three-frequency ultra-wide lane ambiguity method needs observation values of three frequencies, but except that all satellites of the Beidou satellite system contain three-frequency observation data, only part of satellites of the GPS satellite system have three-frequency observation data, and the GLONASS satellite only has two-frequency observation data. These objective conditions limit the use of the three-frequency ultra-wide lane combination method.
Disclosure of Invention
The method solves the problem of the correctness of the double-difference widelane ambiguity in a Network RTK (NRTK) baseline solution algorithm, and can improve the correctness of the double-difference widelane ambiguity of the baseline solution in the network RTK. The accuracy of virtual observation data of a virtual reference station in the network RTK is influenced by the correctness of the baseline double-difference ambiguity, and the accuracy of resolving the baseline double-difference widelane ambiguity is improved, so that the accuracy and the stability of the network RTK can be improved.
The technical scheme adopted by the invention is as follows:
a method for improving network RTK double-difference wide lane ambiguity fixing accuracy comprises the following steps:
step 1, data preparation: receiving real-time observation data of a reference station, satellite ephemeris and coordinate information of the reference station;
step 2, calculating a real-time ionosphere product: calculating a non-differential real-time ionospheric delay value of a satellite signal propagation path according to the coordinate information of the reference station and the satellite coordinates;
step 3, calculating the ambiguity of the baseline double-difference wide lane, comprising the following steps:
step 3.1, forming double-difference observation values by the observation data of the two reference stations, and correcting the double-difference ionospheric residue items by using the non-difference real-time ionospheric delay values calculated in the step 2;
step 3.2, calculating a floating solution of double-difference wide lane ambiguity;
and 3.3, performing rounding on the floating-point solution of the double-difference widelane ambiguity to obtain the double-difference widelane ambiguity integer.
Further, the satellite coordinates in step 2 are obtained by satellite ephemeris calculation.
Further, in the step 2, a non-differential real-time ionospheric delay value of the satellite signal propagation path is calculated by a real-time non-differential non-combination precise single-point positioning technology.
Further, the step 2 specifically includes the following steps:
step 2.1, listing non-differential non-combined observation equations of the double-frequency pseudo range and the carrier phase according to the coordinate information of the reference station and the satellite coordinate;
step 2.2, correcting errors;
step 2.3, estimating receiver clock error, non-differential ambiguity and ionized layer delay parameters including satellite end and receiver end hardware delay deviation DCB by using Kalman filtering;
and 2.4, separating the DCB parameters to obtain the ionospheric delay value of the real satellite signal propagation path in the inclined direction.
Further, the errors in the step 2.2 include earth rotation errors, relativistic effect errors and phase winding errors.
Further, in the step 2.4, the DCB parameters are separated by the non-differential ionospheric delay model established in the vertical direction of the region.
Further, the specific steps of composing the double-difference observation value by the observation data of the two reference stations in the step 3.1 are as follows: and selecting the satellite with the highest satellite altitude angle as a reference satellite, taking other satellites as mobile satellites, subtracting the observation data of the mobile satellite and the reference satellite in one reference station to obtain a primary difference observation value, and subtracting the primary difference observation value of the reference station from the primary difference observation value of the other reference station to obtain a double-difference observation value.
Further, in step 3.2, a float solution of the double-difference widelane ambiguity is calculated by the following formula:
wherein the content of the first and second substances,
is a double difference operator between stations and stars, phi1，φ2Respectively representing phase observed values of two frequencies in a unit of a cycle, rho is the geometric distance between a satellite and a reference station, I1，I2Are respectively provided withIonospheric delay values representing two frequencies in the propagation path of the satellite signal, T being the tropospheric delay value, ε1，ε2Representing unmodeled and noise errors, λ, at two frequencies, respectively1，λ2Representing the wavelengths of two frequencies, N, respectively1，N2Respectively representing the ambiguities of the two frequencies,
i.e. a double-difference wide-lane ambiguity value,
i.e. the double difference ionosphere residue term.
The method has the advantages that the method weakens the influence of double-difference ionosphere residual items, does not need to use a pseudo-range observation value with low precision, does not need three-frequency observation data, and is suitable for all navigation satellite systems. The method can improve the accuracy of double-difference wide lane ambiguity fixing, thereby improving the accuracy of baseline double-difference atmosphere and improving the positioning accuracy and stability of network RTK.
Drawings
FIG. 1 is a flow chart of the present invention for estimating ionospheric delay values over a signal propagation path using PPP techniques;
FIG. 2 is a flow chart of the baseline double-difference wide-lane ambiguity calculation of the present invention.
Detailed Description
The invention provides a method for improving network RTK double-difference wide lane ambiguity fixing accuracy, which is improved based on a phase linear combination method, wherein the phase linear combination formula is as follows:
wherein the content of the first and second substances,
is a double difference operator between stations and stars, phi1，φ2Respectively representing phase observations of two frequencies in cycles,ρ is the geometric distance between the satellite and the reference station, I1，I2Ionospheric delay values representing two frequencies respectively in the propagation path of the satellite signal, T being the tropospheric delay value, ε1，ε2Representing unmodeled and noise errors at two frequencies, respectively, lambda1，λ2Representing the wavelengths of two frequencies, N, respectively1，N2Respectively representing the ambiguities of the two frequencies,
i.e. a double-difference wide-lane ambiguity value,
i.e. the double difference ionospheric residue.
When the ionized layer is active, the double-difference ionized layer residual terms are large, the resolving of double-difference wide-lane ambiguity is influenced, and the precision of the baseline double-difference atmosphere is further influenced. The invention adopts the real-time Precise Point Positioning technology (PPP) to calculate the real-time ionosphere delay value in the satellite signal propagation path. The real-time precise single-point positioning technology is an absolute positioning technology for performing precise single-point positioning by utilizing real-time precise tracks, precise clock error products and observation data acquired in real time. The coordinates of the reference station and the satellite orbit are accurately known, the receiver clock error, the zenith wet troposphere delay, the non-differential ambiguity, the hardware delay deviation and the like are taken as unknowns, and a real-time non-differential ionosphere delay value in a satellite signal propagation path can be estimated in real time by adopting a precise single-point positioning technology. And forming double differences by using the non-differential ionosphere delay values to obtain double-differential ionosphere residual terms in the formula (1), so that the correctness of double-differential wide-lane ambiguity resolution is improved.
The invention is further illustrated below with reference to the figures and examples. The method comprises the following steps:
step 1, data preparation:
real-time observation data of the reference station is received, as well as real-time satellite ephemeris and precise coordinate information of the reference station.
Step 2, calculating a real-time ionosphere product:
the reference station coordinates and the satellite coordinates are accurately known, and a real-time precise single-point positioning technology is adopted to calculate the non-differential real-time ionospheric delay value of the satellite signal propagation path. And estimating the non-difference real-time ionospheric delay containing the hardware delay deviation DCB by using non-difference non-combination observation data and Kalman filtering. And finally, carrying out regional modeling and DCB separation by adopting a polynomial fitting model to obtain a real ionospheric delay value in the satellite signal propagation path inclination direction.
Step 3, calculating the ambiguity of the baseline double-difference wide lane:
and forming a double difference value by the observation data of two reference stations, correcting the residual items of the double-difference ionosphere by using the real-time ionosphere delay value calculated in the second step, calculating the floating point value of double-difference widelane ambiguity, and finally obtaining the double-difference widelane ambiguity integer by a rounding mode. After the accuracy of network RTK double-difference wide lane ambiguity fixing is improved, the data calculation of the virtual reference station can be more accurate.
Preferably, the flow of calculating the non-poor real-time ionospheric delay values in step 2 is as shown in fig. 1. The coordinates of the reference station are accurately known, the coordinates of the satellite are also accurately known, and a real-time precise single-point positioning technology is adopted to calculate the non-differential real-time ionospheric delay value of the satellite signal propagation path. Under the condition that coordinates of a reference station and a satellite are accurately known, non-differential non-combined observation equations of double-frequency pseudo ranges and carrier phases are listed, then error correction such as earth rotation, relativistic effect, phase winding and the like is carried out, Kalman filtering is utilized to estimate parameters such as receiver clock error, non-differential ambiguity, ionized layer delay containing satellite end and receiver end hardware delay deviation DCB (difference Code bias) and the like, a regional vertical direction ionized layer delay model is established by utilizing the non-differential ionized layer delay, and DCB parameters are separated, so that a real ionized layer delay value in the satellite signal propagation path inclination direction is obtained.
Preferably, the step of calculating the double-difference widelane ambiguity of the baseline composed of two reference base stations in step 3 is as shown in fig. 2. The coordinates of the reference base station are known, and the satellite with the highest satellite altitude angle is selected as the reference star, and other satellites are selected as the mobile stars. And subtracting the observation data of the moving star and the reference star in one base station to obtain a primary difference observation value, and subtracting the primary difference observation value of the station from the primary difference observation value of the other base station to obtain a double-difference observation value. Under the condition that the coordinates of a reference station are known and the coordinates of a satellite are known through satellite ephemeris calculation, a double-difference ionosphere value is calculated by utilizing a real-time non-difference ionosphere delay value, then a floating solution of double-difference widelane ambiguity can be calculated according to a formula (1), and then the integer of the floating solution ambiguity is obtained. After the accuracy of network RTK double-difference wide lane ambiguity fixing is improved, the data calculation of the virtual reference station can be more accurate.
Although the present invention has been described with reference to the preferred embodiments, it is not intended to limit the present invention, and those skilled in the art can make variations and modifications of the present invention without departing from the spirit and scope of the present invention by using the methods and technical contents disclosed above.
Claims (6)
1. A method for improving network RTK double-difference wide lane ambiguity fixing accuracy is characterized by comprising the following steps:
step 1, data preparation: receiving real-time observation data of a reference station, satellite ephemeris and coordinate information of the reference station;
step 2, calculating a real-time ionosphere product: calculating a non-differential real-time ionospheric delay value of a satellite signal propagation path according to the coordinate information of the reference station and the satellite coordinates;
step 3, calculating the ambiguity of the baseline double-difference wide lane, comprising the following steps:
step 3.1, forming double-difference observation values by the observation data of the two reference stations, and correcting the double-difference ionospheric residue items by using the non-difference real-time ionospheric delay values calculated in the step 2;
step 3.2, calculating a floating solution of double-difference wide lane ambiguity;
step 3.3, rounding the floating-point solution of the double-difference wide-lane ambiguity to obtain a double-difference wide-lane ambiguity integer;
the formula for calculating the floating solution of the double-difference widelane ambiguity is as follows:
wherein the content of the first and second substances,
is a double difference operator between stations and stars, phi1，φ2Respectively representing phase observed values of two frequencies in a unit of a cycle, rho is the geometric distance between a satellite and a reference station, I1，I2Ionospheric delay values representing two frequencies respectively in the propagation path of the satellite signal, T being the tropospheric delay value, ε1，ε2Representing unmodeled and noise errors, λ, at two frequencies, respectively1，λ2Representing the wavelengths of two frequencies, N, respectively1，N2Respectively representing the ambiguities of the two frequencies,
i.e. a double-difference wide-lane ambiguity value,
i.e., the double difference ionosphere residue term;
the step 2 specifically comprises the following steps:
step 2.1, listing non-differential non-combined observation equations of the double-frequency pseudo range and the carrier phase according to the coordinate information of the reference station and the satellite coordinate;
step 2.2, correcting errors;
step 2.3, estimating receiver clock error, non-differential ambiguity and ionized layer delay parameters including satellite end and receiver end hardware delay deviation DCB by using Kalman filtering;
and 2.4, separating the DCB parameters to obtain the ionospheric delay value of the real satellite signal propagation path in the inclined direction.
2. The method for improving network RTK double-difference widelane ambiguity fix accuracy of claim 1, wherein the satellite coordinates in step 2 are obtained by satellite ephemeris calculation.
3. The method for improving the RTK double-difference widelane ambiguity fix accuracy of the network as claimed in claim 1, wherein in step 2, the non-difference real-time ionospheric delay value of the satellite signal propagation path is calculated by real-time precise single-point positioning technique.
4. The method for improving network RTK double-difference widelane ambiguity fix accuracy of claim 1, wherein the errors in step 2.2 include earth rotation errors, relativistic effect errors, phase wrapping errors.
5. The method for improving the RTK double-difference widelane ambiguity fix accuracy of the network as claimed in claim 1, wherein said step 2.4 of establishing the regional vertical direction ionospheric delay model by the non-differential ionospheric delay separates the DCB parameters.
6. The method for improving the RTK double-difference widelane ambiguity fix accuracy of the network according to claim 5, wherein the step 3.1 of composing the double-difference observation value from the observation data of the two reference stations comprises the following specific steps: and selecting a satellite with the highest satellite altitude angle as a reference satellite, taking other satellites as mobile satellites, subtracting the observation data of the mobile satellite and the reference satellite in one reference station to obtain a primary difference observation value, and subtracting the primary difference observation value of the reference station from the primary difference observation value of the other reference station to obtain a double-difference observation value.
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| CN105842721A (en) * | 2016-03-23 | 2016-08-10 | 中国电子科技集团公司第十研究所 | Method for improving resolving success rate of medium and long baseline GPS integral cycle fuzziness |
| CN106873009A (en) * | 2017-01-12 | 2017-06-20 | 中国科学院测量与地球物理研究所 | The Long baselines Ambiguity Solution Methods aided in using non-combined PPP |
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