CN112305574A - Beidou GNSS satellite real-time positioning and orientation data preprocessing system and method - Google Patents
Beidou GNSS satellite real-time positioning and orientation data preprocessing system and method Download PDFInfo
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- 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
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- G01S19/25—Acquisition or tracking or demodulation of signals transmitted by the system involving aiding data received from a cooperating element, e.g. assisted GPS
- G01S19/258—Acquisition or tracking or demodulation of signals transmitted by the system involving aiding data received from a cooperating element, e.g. assisted GPS relating to the satellite constellation, e.g. almanac, ephemeris data, lists of satellites in view
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Abstract
The invention relates to a Beidou GNSS satellite real-time positioning and orientation data preprocessing system and method, which comprises the steps of inputting carrier phase observation values, pseudo-range observation values and broadcast ephemeris of a plurality of Beidou/GNSS satellites of an observation station 1 and an observation station 2; respectively calculating the coordinates of each satellite and the clock correction by using a satellite position calculation standard algorithm; and (3) comprehensively utilizing a pseudo-range positioning residual analysis method, an inter-station single-difference GF and MW combined observation value method and a high-order difference method to detect pseudo-range gross error and carrier phase cycle slip to calculate to obtain each data, and carrying out cycle slip judgment and pseudo-range positioning pre-and post-test residual judgment to finally obtain observation data with high effectiveness and reliability. The invention comprehensively utilizes a pseudo-range positioning residual error analysis method, an inter-station single-difference GF and MW combined observation value method and a high-order difference method to detect pseudo-range gross error and carrier phase cycle slip, thereby improving the effectiveness and reliability of detection.
Description
Technical Field
The invention relates to a Beidou GNSS satellite real-time positioning and orientation data preprocessing system and method, and belongs to the technical field of satellite positioning algorithms.
Background
With the development of technologies such as unmanned aerial vehicles and automatic driving, the application of Beidou/GNSS high-precision real-time dynamic positioning and orientation is very wide, and higher requirements are provided for guaranteeing the safety of unmanned aerial vehicles and automatic driving and the precision and reliability of real-time dynamic positioning and orientation, wherein the effect of real-time data preprocessing is to obtain the basis and the premise of high-precision and high-reliability real-time positioning and orientation. At present, in real-time high-precision dynamic positioning and orientation application, a pseudo-range coarse difference detection method mainly adopts a pseudo-range robust least square estimation method to detect a coarse difference observed value in a pseudo-range observed value, and cycle slip detection generally detects cycle slip existing in a phase observed value by using the assumed characteristic that a Geometry-free (GF) and a Melbourne-Wubbena (MW) combined observed value slowly and smoothly changes along with time. In the past, Beidou/GNSS high-precision positioning and orientation application generally requires less clearance shielding of an observation environment, and under the condition, the method can obtain a good data preprocessing effect. However, with the appearance of the application of unmanned aerial vehicles and automatic driving, the real-time dynamic positioning and orientation cannot meet the requirements of the observation environment easily, and under the complex environment with serious shielding, the method has obvious phenomena of misdetection and missed detection, which can seriously affect the precision and reliability of the real-time dynamic positioning and orientation of the Beidou/GNSS and reduce the application performance of the unmanned aerial vehicles and the automatic driving technology.
Disclosure of Invention
The invention mainly overcomes the defects in the prior art, provides a Beidou GNSS satellite real-time positioning and orientation data preprocessing system and method, and the system and method comprehensively utilize a pseudo-range positioning residual error analysis method, an inter-station single-difference GF and MW combined observation value method and a high-order difference method to detect pseudo-range gross error and carrier phase cycle slip, thereby improving the detection effectiveness and reliability.
The technical scheme provided by the invention for solving the technical problems is as follows: the Beidou GNSS satellite real-time positioning and orientation data preprocessing method comprises the following steps:
step S1, inputting carrier phase observation values, pseudo-range observation values and broadcast ephemeris of a plurality of Beidou/GNSS satellites of the observation station 1 and the observation station 2;
step S2, calculating the coordinates and the correction of clock error of all the satellites input in the step S1 through a satellite position calculation standard algorithm according to the broadcast ephemeris, deleting the satellite data without the broadcast ephemeris product, and deleting the data of unhealthy satellites according to the satellite health identification provided by the broadcast ephemeris;
step S3, judging pseudo-range observation values of all satellites input in step S1 by using a pseudo-range positioning pre-test residual error judgment method and a pseudo-range positioning pre-test residual error judgment method to delete the pseudo-range observation values of the satellites with gross errors;
step S4, marking whether cycle slip occurs on the carrier phase observation values of all the satellites input in the step S1 by using a single difference GF and MW combined observation value method and a high-order difference value method;
and step S5, finally obtaining a pseudo-range observation value without gross error, a carrier phase observation value marked as cycle slip occurrence, and a carrier phase observation value marked as cycle slip non-occurrence.
The further technical scheme is that the specific process of the step S3 is as follows:
step S31, calculating double-difference pseudo-range observed values of all satellites by pseudo-range positioning residual error analysis method by using coordinates and clock error correction numbers of all satellites, and setting initial parameter value X0The pseudo-range double-difference observation equation is linearized to obtain the pre-test residual v of each double-difference pseudo-range observation value of all satellites0(ii) a If | v0|>30, if the gross error exists, rejecting a pseudo range observation value of the satellite; | v0If the absolute value is less than or equal to 30, considering that no gross error exists, and carrying out the next step;
step S32, obtaining parameter estimation value by least square estimation
The baseline distance constraints are as follows:
const＝sqrt(N2+E2+U2)
wherein N, E, U respectively represent parameter vectors
North, middle, east, and high, const representing the baseline length;
step S33, respectively calculating the post-test residual v and the RMS value delta of the post-test residual of each satellite; if the absolute value v is larger than 4 multiplied by delta, considering that gross errors exist, rejecting the observation value of the satellite, and if the absolute value v is less than or equal to 4 multiplied by delta, considering that no gross errors exist, and keeping the pseudo-range observation value of the satellite;
in a further technical solution, the specific process of step S4 is:
step S41, calculating single difference GF and MW combined observation value delta phi through an inter-station single difference GF and MW combined observation value method according to carrier phase observation values of all satellitesGF、ΔLMW；
Step S42, respectively carrying out filtering estimation on the single-difference GF and MW combined observed values obtained in step 41 by adopting static successive filtering, weakening the influence of noise, and obtaining the estimated value epsilon (phi) of the single-difference GF and MW combined observed valuesGF)、ε(LMW) And estimating the variance δ (Φ)GF)、δ(LMW)；
Combining single difference GF and MW of current epoch into observed value delta phiGF、ΔLMWEstimate e (phi) of observation combined with single differences GF and MWGF)、ε(LMW) Comparing, if: l Δ ΦGF-ε(ΦGF)|>4δ(ΦGF) Or | Δ LMW-ε(LMW)|>4δ(LMW) If so, determining that cycle slip occurs, and marking the carrier phase observation value of the satellite; otherwise, considering that no cycle slip occurs, and not marking;
step S43, calculating a double-difference phase observation value and a high-order difference Δ Φ (t) of the double-difference phase observation value through a high-order difference method according to the carrier phase observation values of all satellites1,t2,t3)；
Step S44, filtering and estimating the high-order difference of the double-difference phase observation value obtained in the step S43 by adopting Kalman filtering, weakening the influence of noise, and obtaining a filtering estimation value epsilon ([ delta ] phi) and a variance delta ([ delta ] phi);
comparing the high-order difference of the double-difference phase observations of the current epoch to the filtered estimate ε (Δ Φ) and the variance δ (Δ Φ), if: |. Δ Φ (t)1,t2,t3)-ε(▽ΔΦ)|>4 δ ([ Δ ] Φ), then a cycle slip is considered to have occurred, and the carrier phase observation for that satellite is marked; otherwise, the cycle slip is not considered to occur, and the marking is not carried out.
Further technical solution is that, in step S31, a calculation formula of the double-difference pseudorange observed value is as follows:
in the formula: Δ represents a double difference operator;
representing double-difference pseudorange observations;
representing double-difference satellite geometric distance;
representing pseudo-range double-difference observed value noise;
residual error v before test0The calculation formula of (a) is as follows:
in the formula: v. of0Representing the pre-trial residual; b denotes a coefficient matrix.
The further technical proposal is that the posterior residual error in the step S33
The calculation formula is as follows:
in the formula:
representing a reference estimate;
the RMS value δ of the post-test residuals is calculated as follows:
in the formula: delta denotes the post-test residualN represents the satellite number of the current epoch, table viShows the posterior residual, w, of the ith satelliteiAnd the pseudo range observation value weight of the ith satellite.
Further technical solution is that, in step S41, a calculation formula of the single-difference GF combination observation value is as follows:
in the formula: delta N1,m,k,ΔN2,m,kRespectively represent L1、L2The carrier phase observations the single-difference ambiguity between stations,
noise of an observation value is combined by single difference GF between stations; lambda [ alpha ]1、λ2Respectively represent L1、L2Wavelength of carrier phase observation.
The further technical solution is that the calculation formula of the single difference MW combined observed value in step S41 is as follows:
in the formula: Δ LMW，m,kRepresents the combined observed value of single difference MW between stations, Delta Nwid,m,kExpressing single-difference wide lane ambiguity between stations, Delta sigmam,kWhich represents the delay of the hardware, is,
and representing the noise of the single difference MW combined observed value between stations.
Further technical solution is that, in step S43, a calculation formula of the double-difference phase observed value is as follows:
in the formula: i. j represents the satellite number, k, m represent the survey station number, and λ represents the carrier phaseThe wavelength of the bits is such that,
representing the geometric distance of the double-differenced satellites,
representing a double-difference integer ambiguity,
representing double difference carrier phase observation noise.
Further technical solution is that, in step S43, a calculation formula of a high-order difference of the double-difference phase observed values is as follows:
in the formula: t is t1、t2、t3Representing the three epoch time instants that are adjacent,
a second order difference representing a double difference carrier phase observation,
represents the second difference of the geometric distance of the double-difference satellites,
the observation is noisy.
Big dipper GNSS satellite real time kinematic fixes a position directional data preprocessing system, includes:
the Beidou receiver I and the Beidou receiver II are used for receiving data of a satellite;
the data forwarder is electrically connected with the Beidou receiver I and the Beidou receiver II respectively and used for forwarding the received satellite data to the data preprocessing server;
the data preprocessing server is electrically connected with the data transponder and specifically comprises a positioning residual error processing module which is used for judging a pseudo-range observed value of a satellite so as to delete the pseudo-range observed value of the satellite with gross error;
the single difference GF processing module is used for marking whether cycle slip occurs to the carrier phase observed value of the satellite;
the single difference MW processing module is used for marking whether cycle slip occurs to the carrier phase observation value of the satellite;
the high-order difference processing module is used for marking whether cycle slip occurs on the carrier phase observation value of the satellite;
and the result storage server is electrically connected with the data preprocessing service and is used for storing the data after the satellite data processing.
The invention has the following beneficial effects: according to the method, the spatial correlation of the ultra-short baseline Beidou/GNSS errors is fully utilized, on one hand, a GF and MW combined observation value which is irrelevant to the geometric distance is constructed by utilizing the traditional combined observation value, the influence of ionospheric delay and multipath effect on cycle slip detection is well eliminated through single difference between stations, on the other hand, a high-order difference observation value which slowly and smoothly changes along with time is constructed, and the high-order difference observation value is complementary with a GF and MW combined observation value method, so that the reliability and the effectiveness of cycle slip detection in a complex environment can be improved. Meanwhile, aiming at the characteristics of short and fixed baseline of an automatic driving application scene, the invention provides a method for eliminating obviously larger gross errors by using the pre-test residual error, and improves the stability of least square parameter estimation and the reliability of post-test residual error distribution, thereby improving the effectiveness and reliability of gross error detection in a complex environment.
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FIG. 1 is a block flow diagram of the present invention;
fig. 2 is a block diagram of the architecture of the present invention.
Detailed Description
The present invention will be further described with reference to the following examples and the accompanying drawings.
As shown in fig. 2, the Beidou GNSS satellite real-time dynamic positioning and orientation data preprocessing system includes:
the Beidou receiver I and the Beidou receiver II are used for receiving data of a satellite;
the data forwarder is electrically connected with the Beidou receiver I and the Beidou receiver II respectively and used for forwarding the received satellite data to the data preprocessing server;
the data preprocessing server is electrically connected with the data transponder and specifically comprises a positioning residual error processing module which is used for judging a pseudo-range observed value of a satellite so as to delete the pseudo-range observed value of the satellite with gross error;
the single difference GF processing module is used for marking whether cycle slip occurs to the carrier phase observed value of the satellite;
the single difference MW processing module is used for marking whether cycle slip occurs to the carrier phase observation value of the satellite;
the high-order difference processing module is used for marking whether cycle slip occurs on the carrier phase observation value of the satellite;
and the result storage server is electrically connected with the data preprocessing service and is used for storing the data after the satellite data processing.
As shown in fig. 1, the method for preprocessing the Beidou GNSS satellite real-time positioning orientation data of the present invention comprises the following steps:
step 1, inputting time K, original non-differential observation data of all satellites of Beidou/GNSS of the observation station 1 and the observation station 2 and broadcast ephemeris.
And 2, respectively calculating all satellite coordinates and clock error correction numbers by using a satellite position calculation standard algorithm, specifically referring to section 2.3 of GPS measurement and data processing of Wuhan university Press, deleting satellite data without a broadcast ephemeris product, and deleting data of unhealthy satellites according to satellite health marks provided by the broadcast ephemeris.
Step 3, calculating non-difference GF and MW combined observed values of all satellites of the observation station 1 and the observation station 2 according to the formulas (1) and (2), calculating single-difference GF and MW combined observed values between the stations according to the formulas (3) and (4) respectively; meanwhile, pseudo-range and phase double-difference observed values are calculated according to equations (5) and (6), respectively.
Wherein phi1，Φ2Respectively represent L1、L2Carrier phase observation, λ1，λ2Respectively represent L1、L2Wavelength of carrier phase observation, f1，f2Respectively represent L1、L2Frequency of carrier phase observations, N1，N2Respectively represent L1、L2Ambiguity of carrier phase observation, I denotes L1Ionospheric delays on the carrier-phase observations,
noise representing GF combined observations.
Wherein λwidRepresenting a wide-lane observation wavelength, NwidRepresenting widelane ambiguity, sigma representing hardware delay,
representing non-difference MW combined observation noise.
Wherein Δ N1,m,k,ΔN2,m,kRespectively represent L1、L2The carrier phase observations the single-difference ambiguity between stations,
the single difference GF between stations combines the noise of the observed values.
Wherein, Δ LMW，m,kRepresents the combined observed value of single difference MW between stations, Delta Nwid,m,kExpressing single-difference wide lane ambiguity between stations, Delta sigmam,kWhich represents the delay of the hardware, is,
and representing the noise of the single difference MW combined observed value between stations.
Where Δ represents a double difference operator,
representing a double-differenced pseudorange observation,
representing the geometric distance of the double-differenced satellites,
representing pseudorange double-difference observation noise.
Where i, j denotes the satellite number, k, m denotes the station number, λ denotes the carrier phase wavelength,
representing the geometric distance of the double-differenced satellites,
representing a double-difference integer ambiguity,
representing double difference carrier phase observation noise.
Step 4, adopting static successive filtering to respectively carry out filtering estimation on the single-difference GF and MW combined observed values obtained in the step 3, and weakening noiseInfluence, resulting in an estimate ε (Φ) of the single-difference GF and MW combined observationsGF)、ε(LMW) And estimating the variance δ (Φ)GF)、δ(LMW)。
Comparing the single difference GF and MW combined observed value of the current epoch with the static successive filtering result, if: l Δ ΦGF-ε(ΦGF)|>4δ(ΦGF) Or | Δ LMW-ε(LMW)|>4δ(LMW) If not, the cycle slip is not considered to occur. And if the cycle slip of the i satellite in the time K is judged, restarting the static successive filtering process of the i satellite in the step at the time K + 1.
Step 5, simultaneously with the step 4, calculating the high-order difference of the double-difference phase observed value according to the formula (7), and performing filtering estimation on the high-order difference of the double-difference phase observed value by adopting Kalman filtering to weaken the influence of noise to obtain a filtering estimation value epsilon ([ delta ] phi) and a variance delta ([ delta ] phi),
wherein t is1,t2,t3Representing the three epoch time instants that are adjacent,
a second order difference representing a double difference carrier phase observation,
represents the second difference of the geometric distance of the double-difference satellites,
the observation is noisy.
Comparing the high-order difference of the double-difference phase observed value of the current epoch with the filtering result, if:
|▽ΔΦ(t1,t2,t3)-ε(▽ΔΦ)|>4 δ ([ Δ ] Φ), then cycle slip is considered to have occurred, otherwise cycle slip is considered to have not occurred. If the cycle slip of the i satellite in the time K is judged, at the time K +1,the kalman filtering process restarts in this step for satellite i.
Step 6, simultaneously with the step 4, selecting an initial parameter value X0The pseudo-range double-difference observation equation is linearized (1, 1, 1), and the pre-test residual V of the double-difference pseudo-range observation value is calculated according to equation (8)0If | V0|>And 30, rejecting the observation value of the satellite if the gross error exists.
V0＝BX0-L (8)
Wherein V0Representing the pre-trial residuals, L representing the double-differenced pseudorange observations, and B representing the coefficient matrix.
The error equation (8) without gross error is listed in matrix form as follows:
obtaining parameter estimates using least squares estimation
Respectively calculating the post-test residual v and the RMS of the post-test residual of each satellite according to the formulas (9) and (10), if | v>4 RMS, the gross error is considered to exist, and the observation of the satellite is rejected.
Where δ represents the RMS value of the post-test residual, n represents the satellite number of the current epoch, viRepresenting the post-test residual of the ith satellite, wiPseudo range observation value weight of ith satellite
And 7, inputting the observation data at the moment K +1, and re-executing the steps 1-6 until the observation data at all the moments are preprocessed.
And 8, finally obtaining a pseudo-range observation value without gross error, a carrier phase observation value marked as cycle slip occurrence, and a carrier phase observation value marked as cycle slip non-occurrence.
Although the present invention has been described with reference to the above embodiments, it should be understood that the present invention is not limited to the above embodiments, and those skilled in the art can make various changes and modifications without departing from the scope of the present invention.
Claims (10)
1. The Beidou GNSS satellite real-time positioning and orientation data preprocessing method is characterized by comprising the following steps:
step S1, inputting carrier phase observation values, pseudo-range observation values and broadcast ephemeris of a plurality of Beidou/GNSS satellites of the observation station 1 and the observation station 2;
step S2, calculating the coordinates and the correction of clock error of all the satellites input in the step S1 through a satellite position calculation standard algorithm according to the broadcast ephemeris, deleting the satellite data without the broadcast ephemeris product, and deleting the data of unhealthy satellites according to the satellite health identification provided by the broadcast ephemeris;
step S3, judging pseudo-range observation values of all satellites input in step S1 by using a pseudo-range positioning pre-test residual error judgment method and a pseudo-range positioning pre-test residual error judgment method to delete the pseudo-range observation values of the satellites with gross errors;
step S4, marking whether cycle slip occurs on the carrier phase observation values of all the satellites input in the step S1 by using a single difference GF and MW combined observation value method and a high-order difference value method;
and step S5, finally obtaining a pseudo-range observation value without gross error, a carrier phase observation value marked as cycle slip occurrence, and a carrier phase observation value marked as cycle slip non-occurrence.
2. The method for preprocessing the Beidou GNSS satellite real-time positioning and orientation data according to claim 1, wherein the specific process of the step S3 is as follows:
step S31, calculating double-difference pseudo-range observed values of all satellites by a pseudo-range positioning residual error analysis method according to coordinates and clock error correction numbers of all satellites, and setting an initial parameter value X0(1, 1, 1), linearizing pseudo-range double-difference observation equation, and calculating to obtain pre-test residual v of double-difference pseudo-range observation value0(ii) a If | v0|>30, if the gross error exists, rejecting a pseudo range observation value of the satellite; | v0If the absolute value is less than or equal to 30, considering that no gross error exists, and carrying out the next step;
step S32, obtaining parameter estimation value by least square estimation
The baseline distance constraints are as follows:
const＝sqrt(N2+E2+U2)
wherein N, E, U respectively represent parameter vectors
North, middle, east, and high, const representing the baseline length;
step S5, and estimating the parameters according to step 32
Calculating the post-test residual v and RMS (root mean square) values delta of the post-test residual of all satellites; if | v $>And if the absolute value is less than or equal to 4 multiplied by delta, the pseudorange observed value of the satellite is considered to be not present, and the pseudorange observed value of the satellite is reserved.
3. The method for preprocessing the Beidou GNSS satellite real-time positioning and orientation data according to claim 1, wherein the specific process of the step S4 is as follows:
step S41, calculating single difference GF and MW combined observation value delta phi through an inter-station single difference GF and MW combined observation value method according to carrier phase observation values of all satellitesGF、ΔLMW；
Step S42, respectively carrying out filtering estimation on the single-difference GF and MW combined observed values obtained in step 41 by adopting static successive filtering, weakening the influence of noise, and obtaining the estimated value epsilon (phi) of the single-difference GF and MW combined observed valuesGF)、ε(LMW) And estimating the variance δ (Φ)GF)、δ(LMW)；
Combining single difference GF and MW of current epoch into observed value delta phiGF、ΔLMWEstimate e (phi) of observation combined with single differences GF and MWGF)、ε(LMW) Comparing, if: l Δ ΦGF-ε(ΦGF)|>4δ(ΦGF) Or | Δ LMW-ε(LMW)|>4δ(LMW) If so, determining that cycle slip occurs, and marking the carrier phase observation value of the satellite; otherwise, considering that no cycle slip occurs, and not marking;
step S43, calculating the double-difference phase observed value and the high-order difference of the double-difference phase observed value by a high-order difference method according to the carrier phase observed values of all satellites
Step S44, filtering and estimating the high-order difference of the double-difference phase observed value obtained in the step S5 by Kalman filtering, weakening the influence of noise and obtaining a filtering estimated value
Sum variance
The high-order difference of the double-difference phase observed value of the current epoch and the filtering estimation value
Sum variance
Make a comparison if
Considering that cycle slip occurs, and marking the carrier phase observed value of the satellite; otherwise, the cycle slip is not considered to occur, and the marking is not carried out.
4. The method for preprocessing the Beidou GNSS satellite real-time positioning and orientation data of claim 2, wherein the double-difference pseudorange observation in step S31 is calculated as follows:
in the formula:
representing a double difference operator;
representing double-difference pseudorange observations;
representing double-difference satellite geometric distance;
representing pseudo-range double-difference observed value noise;
residual error v before test0The calculation formula of (a) is as follows:
in the formula: v. of0Representing the pre-trial residual; b denotes a coefficient matrix.
5. The method for preprocessing the Beidou GNSS satellite real-time positioning and orientation data of claim 2, wherein the posterior residual error in the step S33 is
The calculation formula is as follows:
in the formula:
representing a reference estimate;
the RMS value δ of the post-test residuals is calculated as follows:
in the formula: delta represents the RMS value of the post-test residual, n represents the satellite number of the current epoch, table viShows the posterior residual, w, of the ith satelliteiAnd the pseudo range observation value weight of the ith satellite.
6. The method for preprocessing the Beidou GNSS satellite real-time positioning and orientation data according to claim 3, wherein the single-difference GF combined observation value in the step S41 is calculated according to the following formula:
in the formula: delta N1,m,k,ΔN2,m,kRespectively represent L1、L2The carrier phase observations the single-difference ambiguity between stations,
GF combined observation of single difference between stationsNoise of the value; lambda [ alpha ]1、λ2Respectively represent L1、L2Wavelength of carrier phase observation.
7. The method for preprocessing the Beidou GNSS satellite real-time positioning and orientation data of claim 3, wherein the calculation formula of the single difference MW combined observation value in the step S41 is as follows:
in the formula: Δ LMW，m,kRepresents the combined observed value of single difference MW between stations, Delta Nwid,m,kExpressing single-difference wide lane ambiguity between stations, Delta sigmam,kWhich represents the delay of the hardware, is,
and representing the noise of the single difference MW combined observed value between stations.
8. The method for preprocessing the Beidou GNSS satellite real-time positioning and orientation data of claim 1, wherein the calculation formula of the double-difference phase observation in the step S43 is as follows:
in the formula: i. j denotes the satellite number, k, m denote the station number, λ denotes the carrier phase wavelength,
representing the geometric distance of the double-differenced satellites,
representing a double-difference integer ambiguity,
representing double difference carrier phase observation noise.
9. The method as claimed in claim 6, wherein the calculation formula of the high order difference of the double difference phase observations in the step S43 is as follows:
in the formula: t is t1、t2、t3Representing the three epoch time instants that are adjacent,
a second order difference representing a double difference carrier phase observation,
represents the second difference of the geometric distance of the double-difference satellites,
the observation is noisy.
10. Big dipper GNSS satellite real time kinematic fixes a position directional data preprocessing system, its characterized in that includes:
the Beidou receiver I and the Beidou receiver II are used for receiving data of a satellite;
the data forwarder is electrically connected with the Beidou receiver I and the Beidou receiver II respectively and used for forwarding the received satellite data to the data preprocessing server;
the data preprocessing server is electrically connected with the data transponder and specifically comprises a positioning residual error processing module which is used for judging a pseudo-range observed value of a satellite so as to delete the pseudo-range observed value of the satellite with gross error;
the single difference GF processing module is used for marking whether cycle slip occurs to the carrier phase observed value of the satellite;
the single difference MW processing module is used for marking whether cycle slip occurs to the carrier phase observation value of the satellite;
the high-order difference processing module is used for marking whether cycle slip occurs on the carrier phase observation value of the satellite;
and the result storage server is electrically connected with the data preprocessing service and is used for storing the data after the satellite data processing.
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