阅读说明：本技术 Gnss形变监测方法、系统 (GNSS deformation monitoring method and system ) 是由 陈玉林 余伟 于 2020-06-03 设计创作，主要内容包括：本申请公开了GNSS形变监测方法、系统。该方法包括：根据双差观测方程计算卫星的双差残差；将所述双差残差转换为单差残差；计算每颗卫星的重复周期；根据每颗卫星相邻前几个周期的单差残差合并计算一个周期的单差残差；对所述合并计算的单差残差进行经验模态分析,获取每颗卫星的多路径误差；在基线解算过程中消除所述每颗卫星的多路径误差。(The application discloses a GNSS deformation monitoring method and a GNSS deformation monitoring system. The method comprises the following steps: calculating double-difference residual errors of the satellites according to a double-difference observation equation; converting the double-difference residual error into a single-difference residual error; calculating the repetition period of each satellite; the single-difference residual error of one period is calculated according to the single-difference residual errors of the adjacent previous periods of each satellite; performing empirical mode analysis on the single-difference residual errors obtained by the combination calculation to obtain a multi-path error of each satellite; the multipath error for each satellite is eliminated during the baseline solution.)

1. A GNSS deformation monitoring method is characterized by comprising the following steps:

calculating double-difference residual errors of the satellites according to a double-difference observation equation;

converting the double-difference residual error into a single-difference residual error;

calculating the repetition period of each satellite;

the single-difference residual error of one period is calculated according to the single-difference residual errors of the adjacent previous periods of each satellite;

performing empirical mode analysis on the single-difference residual errors obtained by the combination calculation to obtain a multi-path error of each satellite;

the multipath error for each satellite is eliminated during the baseline solution.

2. The GNSS deformation monitoring method according to claim 1, wherein the step of calculating the double-difference residuals of the satellites according to the double-difference observation equation further includes:

constructing a double-difference observation equation, wherein the double-difference observation equation comprises a pseudo-range double-difference observation equation and a carrier phase double-difference observation equation, and the pseudo-range double-difference observation equation and the carrier phase double-difference observation equation are respectively expressed as follows:

wherein said pairThe parameters to be estimated in the difference observation equation comprise three coordinate parameters x of the rover station_u,y_u,z_uAnd double-difference ambiguity parameter

Carrying out linearization processing on the double-difference observation equation to obtain the following formula:

V＝A·x+B·y-L

wherein, V is a double-difference observation value residual error, A, B is a coordinate parameter and a double-difference ambiguity parameter coefficient array respectively, and L is a difference between an observation value and a calculated value;

calculating and obtaining the estimated value of the parameter to be estimated according to the least square principleFor the floating-point solution of the coordinate parameters,for double-difference ambiguity parameter floating solution, the lambda method is used for the double-difference ambiguity parameter floating solutionFixing to obtain double-difference ambiguity parameter fixing solutionFixing the double-difference ambiguity parameter to a solutionSubstituting the two-difference observation equation to obtain a coordinate parameter fixed solution according to the least square principleFixing the coordinate parameters to a solutionThe double difference blurDegree parameter fixation solutionSubstituting the double-difference observation equation to calculate to obtain the double-difference residual error

3. The GNSS deformation monitoring method according to claim 2, wherein the step of converting the double-difference residuals of the satellites into single-difference residuals further comprises:

the double difference residual error is processedExpressed as a matrix and single difference residual error according to the following formulaThe product of (a):

wherein, w_iRepresenting the weight factor of satellite i in the baseline solution,

converting the double difference residual to a single difference residual comprising only multipath error and random noise using matrix inversion.

4. The GNSS deformation monitoring method according to claim 1, wherein the step of calculating the repetition period of each satellite further comprises:

calculating a repetition period for each satellite according to the following formula:

T_a1＝86400-2(2π/n)

T_a2＝86400-(2π/n)

T_a3＝86400·7-13·(2π/n)

wherein the content of the first and second substances,is the earth's gravitational constant, a is the semi-major axis of the satellite's orbit, n is the angular velocity of the satellite's rotation, Δ n is the perturbation parameter of the average angular velocity, T_a1For GPS satellite repetition period time offset, T_a2For BDS GEO/IGSO satellite repetition period time offset, T_a3The periodic time offset is repeated for the BDS MEO satellites.

5. The GNSS deformation monitoring method according to claim 1, wherein the step of calculating the single-difference residuals of one period based on the combination of the single-difference residuals of the previous adjacent periods of each satellite further comprises: and averaging the single difference residuals of the adjacent previous periods.

6. The GNSS deformation monitoring method according to claim 1, further comprising: selecting a baseline vector as an observed value during net adjustment; forming a function model of unconstrained net adjustment; solving the function model to obtain a mean square value, a correction number and a corresponding precision statistic value of the baseline vector; judging whether the observed value has gross error; if yes, removing or reducing the weight of the observed value, and if not, outputting a final result.

7. A GNSS deformation monitoring system, comprising:

a residual error acquisition module configured to calculate a double-difference residual error of the satellite according to a double-difference observation equation;

a residual transformation module configured to transform the double-difference residual into a single-difference residual;

a period calculation module configured to calculate a repetition period of each satellite;

the merging calculation module is configured to calculate single-difference residual errors of one period according to the single-difference residual errors of the adjacent previous periods of each satellite;

an error extraction module configured to perform empirical mode analysis on the single-difference residuals obtained through the merging calculation to obtain a multipath error of each satellite;

a resolving module configured to eliminate the multipath error for each satellite during a baseline resolution process.

8. The GNSS deformation monitoring system of claim 7, wherein the residual acquisition module is further configured to:

constructing a double-difference observation equation, wherein the double-difference observation equation comprises a pseudo-range double-difference observation equation and a carrier phase double-difference observation equation, and the pseudo-range double-difference observation equation and the carrier phase double-difference observation equation are respectively expressed as follows:

wherein the parameters to be estimated in the double-difference observation equation comprise three coordinate parameters x of the rover station_u,y_u,z_uAnd double-difference ambiguity parameter

Carrying out linearization processing on the double-difference observation equation to obtain the following formula:

V＝A·x+B·y-L

wherein, V is a double-difference observation value residual error, A, B is a coordinate parameter and a double-difference ambiguity parameter coefficient array respectively, and L is a difference between an observation value and a calculated value;

calculating and obtaining the estimation of the parameter to be estimated according to the least square principleEvaluating valueFor the floating-point solution of the coordinate parameters,for double-difference ambiguity parameter float solution, the lambda method is used to solve the double-difference ambiguity float solutionFixing to obtain double-difference ambiguity parameter fixing solutionFixing the double-difference ambiguity parameter to a solutionSubstituting the two-difference observation equation to obtain a coordinate parameter fixed solution according to the least square principleFixing the coordinate parameters to a solutionThe double-difference ambiguity parameter fixed solutionSubstituting the double-difference observation equation to calculate to obtain the double-difference residual error

9. The GNSS deformation monitoring system of claim 8, wherein the residual transformation module is further configured to:

the double difference residual error is processedExpressed as a matrix and single difference residual error according to the following formulaThe product of (a):

wherein, w_iRepresenting the weight factors of the i satellites in the baseline solution,

converting the double difference residual to a single difference residual comprising only multipath error and random noise using matrix inversion.

10. The GNSS deformation monitoring system according to claim 7, wherein the period calculation module calculates the repetition period of each satellite according to the following formula:

T_a1＝86400-2(2π/n)

T_a2＝86400-(2π/n)

T_a3＝86400·7-13·(2π/n)

whereinIs the earth's gravitational constant, a is the semi-major axis of the satellite's orbit, n is the angular velocity of the satellite's rotation, Δ n is the perturbation parameter of the average angular velocity, T_a1For GPS satellite repetition period time offset, T_a2For BDS GEO/IGSO satellite repetition period time offset, T_a3The periodic time offset is repeated for the BDS MEO satellites.

11. The GNSS deformation monitoring system of claim 7 wherein the combining computation module averages the single difference residuals of the previous adjacent cycles.

12. The GNSS deformation monitoring system of claim 7, further comprising a baseline net adjustment calculation module configured to: selecting a baseline vector as an observed value during net adjustment; forming a function model of unconstrained net adjustment; solving the function model to obtain a mean square value, a correction number and a corresponding precision statistic value of the baseline vector; judging whether the observed value has gross error; if yes, removing or reducing the weight of the observed value, and if not, outputting a final result.

13. A GNSS deformation monitoring system, comprising:

a memory for storing computer executable instructions;

a processor, coupled with the memory, for implementing the steps in the method of any of claims 1-6 when executing the computer-executable instructions.

14. A computer-readable storage medium having stored thereon computer-executable instructions which, when executed by a processor, implement the steps of the method of any one of claims 1 to 6.

Technical Field

The present disclosure relates generally to the field of satellite navigation technologies, and in particular, to a GNSS deformation monitoring method and system.

Background

In the current monitoring scheme based on the GNSS, a baseline is formed by monitoring station data and reference station data (or virtual VRS data), and the baseline is calculated to obtain coordinate information of a monitoring point, so that whether a building deforms or not is determined. First, satellite data received at the surface includes useful information such as receiver position, random observation errors, and various system errors. Wherein systematic errors, such as ionosphere errors, troposphere errors, orbit errors, satellite clock errors, receiver clock errors, and the like, can be eliminated or greatly attenuated through double-frequency observation, double-difference observation and accurate model correction. However, multipath effects associated with the site environment have no spatial correlation, cannot be eliminated using differential mode, and cannot be separated by linear model estimation.

Disclosure of Invention

The specification provides a GNSS deformation monitoring method for eliminating multipath errors in a satellite navigation positioning signal propagation process.

An embodiment of the present application discloses a GNSS deformation monitoring method, including:

calculating double-difference residual errors of the satellites according to a double-difference observation equation;

converting the double-difference residual error into a single-difference residual error;

calculating the repetition period of each satellite;

the single-difference residual error of one period is calculated according to the single-difference residual errors of the adjacent previous periods of each satellite;

performing empirical mode analysis on the single-difference residual errors obtained by the combination calculation to obtain a multi-path error of each satellite;

the multipath error for each satellite is eliminated during the baseline solution.

In a preferred embodiment, the step of calculating the double-difference residual of the satellite according to the double-difference observation equation further includes:

constructing a double-difference observation equation, wherein the double-difference observation equation comprises a pseudo-range double-difference observation equation and a carrier phase double-difference observation equation, and the pseudo-range double-difference observation equation and the carrier phase double-difference observation equation are respectively expressed as follows:

wherein to be estimated in the double difference observation equationThe parameters include three coordinate parameters x of the rover_u,y_u,z_uAnd double-difference ambiguity parameter

Carrying out linearization processing on the double-difference observation equation to obtain the following formula:

V＝A·x+B·y-L

wherein, V is a double-difference observation value residual error, A, B is a coordinate parameter and a double-difference ambiguity parameter coefficient array respectively, and L is a difference between an observation value and a calculated value;

calculating and obtaining the estimated value of the parameter to be estimated according to the least square principleFor the floating-point solution of the coordinate parameters,for double-difference ambiguity parameter float solution, the lambda method is used to solve the double-difference ambiguity float solutionFixing to obtain double-difference ambiguity parameter fixing solutionFixing the double-difference ambiguity parameter to a solutionSubstituting the two-difference observation equation to obtain a coordinate parameter fixed solution according to the least square principleFixing the coordinate parameters to a solutionThe double-difference ambiguity parameter fixed solutionSubstituting the double-difference observation equation to calculate to obtain the double-difference residual error

In a preferred embodiment, the step of converting the double-difference residual of the satellite into the single-difference residual further includes:

the double difference residual error is processedExpressed as a matrix and single difference residual error according to the following formulaThe product of (a):

wherein, w_iRepresenting the weight factor of satellite i in the baseline solution,

converting the double difference residual to a single difference residual comprising only multipath error and random noise using matrix inversion.

In a preferred embodiment, the step of calculating the repetition period of each satellite further includes:

calculating a repetition period for each satellite according to the following formula:

T_a1＝86400-2(2π/n)

T_a2＝86400-(2π/n)

T_a3＝86400·7-13·(2π/n)

whereinIs the earth's gravitational constant, a is the semi-major axis of the satellite's orbit, n is the angular velocity of the satellite's rotation, Δ n is the perturbation parameter of the average angular velocity, T_a1For GPS satellite repetition period time offset, T_a2For BDS GEO/IGSO satellite repetition period time offset, T_a3The periodic time offset is repeated for the BDS MEO satellites.

In a preferred embodiment, the step of calculating the single-difference residual of one period according to the single-difference residuals of several adjacent previous periods of each satellite further includes: and averaging the single difference residuals of the adjacent previous periods.

In a preferred embodiment, the method further comprises the following steps: selecting a baseline vector as an observed value during net adjustment; forming a function model of net adjustment; solving the function model to obtain a mean square value, a correction number and a corresponding precision statistic value of the baseline vector; judging whether the observed value has gross error; if yes, removing or reducing the weight of the observed value, and if not, outputting a final result.

In another embodiment of the present application, a GNSS deformation monitoring system is disclosed, which includes:

a residual error acquisition module configured to calculate a double-difference residual error of the satellite according to a double-difference observation equation;

a residual transformation module configured to transform the double-difference residual into a single-difference residual;

a period calculation module configured to calculate a repetition period of each satellite;

the merging calculation module is configured to calculate single-difference residual errors of one period according to the single-difference residual errors of the adjacent previous periods of each satellite;

an error extraction module configured to perform empirical mode analysis on the single-difference residuals obtained through the merging calculation to obtain a multipath error of each satellite;

a resolving module configured to eliminate the multipath error for each satellite during a baseline resolution process.

In a preferred embodiment, the residual obtaining module is further configured to:

constructing a double-difference observation equation, wherein the double-difference observation equation comprises a pseudo-range double-difference observation equation and a carrier phase double-difference observation equation, and the pseudo-range double-difference observation equation and the carrier phase double-difference observation equation are respectively expressed as follows:

wherein the parameters to be estimated in the double-difference observation equation comprise three coordinate parameters x of the rover station_u,y_u,z_uAnd double-difference ambiguity parameter

Carrying out linearization processing on the double-difference observation equation to obtain the following formula:

V＝A·x+B·y-L

wherein, V is a double-difference observation value residual error, A, B is a coordinate parameter and a double-difference ambiguity parameter coefficient array respectively, and L is a difference between an observation value and a calculated value;

calculating and obtaining the estimated value of the parameter to be estimated according to the least square principleFor the floating-point solution of the coordinate parameters,for double-difference ambiguity parameter float solution, the lambda method is used to solve the double-difference ambiguity float solutionFixing to obtain double-difference ambiguity parameter fixing solutionFixing the double-difference ambiguity parameter to a solutionSubstituting the two-difference observation equation to obtain a coordinate parameter fixed solution according to the least square principleFixing the coordinate parameters to a solutionThe double-difference ambiguity parameter fixed solutionSubstituting the double-difference observation equation to calculate to obtain the double-difference residual error

In a preferred embodiment, the residual transform module is further configured to:

the residual error conversion module converts the double-difference residual errorExpressed as a matrix and single difference residual error according to the following formulaThe product of (a):

wherein, w_iRepresenting the weight factors of the i satellites in the baseline solution,

converting the double difference residual to a single difference residual comprising only multipath error and random noise using matrix inversion.

In a preferred embodiment, the period calculating module calculates the repetition period of each satellite according to the following formula:

T_a1＝86400-2(2π/n)

T_a2＝86400-(2π/n)

T_a3＝86400·7-13·(2π/n)

whereinIs the earth's gravitational constant, a is the semi-major axis of the satellite's orbit, n is the angular velocity of the satellite's rotation, Δ n is the perturbation parameter of the average angular velocity, T_a1For GPS satellite repetition period time offset, T_a2For BDS GEO/IGSO satellite repetition period time offset, T_a3The periodic time offset is repeated for the BDS MEO satellites.

In a preferred embodiment, the combination calculation module performs an averaging process on the single-difference residuals of the previous adjacent cycles.

In a preferred embodiment, the system further comprises a baseline net adjustment calculation module configured to: selecting a baseline vector as an observed value during net adjustment; forming a function model of net adjustment; solving the function model to obtain a mean square value, a correction number and a corresponding precision statistic value of the baseline vector; judging whether the observed value has gross error; if yes, removing or reducing the weight of the observed value, and if not, outputting a final result.

Another embodiment of the present application further discloses a GNSS deformation monitoring system including:

a memory for storing computer executable instructions; and

a processor, coupled with the memory, for implementing the steps in the method as described above when executing the computer-executable instructions.

Another embodiment of the present application also discloses a computer-readable storage medium having stored therein computer-executable instructions that, when executed by a processor, implement the steps in the method as described above.

Compared with the prior art, the method has the following beneficial effects:

the influence that this application can effectually weaken multi-path effect and solve the baseline promotes the precision of solving of a strip base line, adopts GNSS basic line net adjustment scheme simultaneously, eliminates the influence of error basic line to monitoring network, improves monitoring network quality, promotes whole monitoring precision, is applicable to the millimeter level deformation monitoring of complex scenes such as dam bridge, crisis, iron tower.

A large number of technical features are described in the specification, and are distributed in various technical solutions, so that the specification is too long if all possible combinations of the technical features (namely, the technical solutions) in the application are listed. In order to avoid this problem, the respective technical features disclosed in the above summary of the invention of the present specification, the respective technical features disclosed in the following embodiments and examples, and the respective technical features disclosed in the drawings may be freely combined with each other to constitute various new technical solutions (which should be regarded as having been described in the present specification) unless such a combination of the technical features is technically impossible. For example, in one example, the feature a + B + C is disclosed, in another example, the feature a + B + D + E is disclosed, and the features C and D are equivalent technical means for the same purpose, and technically only one feature is used, but not simultaneously employed, and the feature E can be technically combined with the feature C, then the solution of a + B + C + D should not be considered as being described because the technology is not feasible, and the solution of a + B + C + E should be considered as being described.

Drawings

Non-limiting and non-exhaustive embodiments of the present application are described with reference to the following figures, wherein like reference numerals refer to like parts throughout the various views unless otherwise specified.

FIG. 1 is a flowchart illustrating a GNSS deformation monitoring method according to an embodiment of the present disclosure.

FIG. 2 is a diagram of a GNSS deformation monitoring system according to an embodiment of the present disclosure.

Detailed Description

The existing GNSS deformation monitoring schemes have the following two types. Firstly, newly-built GNSS deformation monitoring reference station: the method comprises the steps of installing a monitoring base station on a measured point of a building, setting a reference station in a relative settlement-free area near the building, and transmitting data of the monitoring base station and the reference station to a service system through a wireless or wired transmission system to analyze and solve to obtain deformation information. Secondly, receiving an enhanced signal at a monitoring point: the receiver receives satellite telegraph text signals and low orbit satellite navigation positioning auxiliary enhancement system signals or navigation positioning and deformation monitoring positioning auxiliary enhancement system signals, such as VRS signals in NRTK, at monitoring points, and the deformation information is obtained through analysis and calculation.

In both monitoring schemes, the data of the monitoring station and the data of the reference station (or virtual VRS data) form a baseline, and the baseline is calculated to obtain the coordinate information of the monitoring point, so that whether the building deforms or not is determined. The satellite data received on the ground not only contains useful information such as the position of a receiver, but also contains random observation errors and various system errors, such as ionosphere errors, troposphere errors, orbit errors, satellite clock errors, receiver clock errors and the like.

In the first scheme, the distance between the monitoring station and the reference station is often short, the ionosphere error, the troposphere error, the orbit error, the satellite clock error and the receiver clock error can be effectively eliminated or greatly weakened through double-difference observation under the condition of a short baseline, only the coordinate parameter item and the ambiguity parameter item are considered in the estimated parameters at the moment, and the coordinates of the monitoring point can be obtained through ambiguity search and fixation so as to obtain the deformation quantity.

In the second scheme, an enhancement system such as a CORS system is utilized, an accurate error model is established by integrating the observation information of each reference station to correct the distance-related error, a virtual reference station VRS which does not exist in real time is generated near a user station (monitoring station), then, the difference is carried out by utilizing the virtual reference station VRS and the observation value of the monitoring station, and the coordinate of the monitoring station is accurately determined so as to obtain the deformation information.

The specific scheme of the first scheme is as follows:

the satellite navigation positioning signals are affected by various types of errors from the broadcast, the propagation and the acquisition stage of the receiver antenna. The errors at the satellite end include hardware delay, satellite clock error, satellite orbit error and the like, ionospheric delay and tropospheric delay in the propagation process, and multipath effect caused by reflectors and the like, and the errors at the receiver end include hardware delay, receiver clock error and the like. The carrier phase and pseudorange non-difference observation range equations may therefore be expressed in the form (in meters):

the meaning of the parameters in the above formula is as follows: p and L are non-differential observations of pseudorange and carrier phase respectively,geometric distance of satellite to survey station, OⁱFor orbital error, c is the speed of light in vacuum, δ t_uAnd δ tⁱRespectively the receiver and the satellite clock offset,in order to delay the tropospheric delay,for ionospheric delay, DpⁱAnd Dp_uPseudorange hardware delays Dl at satellite and receiver ends, respectivelyⁱAnd Dl_uHardware delay of carrier phase, lambda, at satellite and receiver ends, respectively_uIs the carrier phase wavelength of the current frequency point,the degree of ambiguity of the whole circumference is,anddistributed as pseudorange and carrier phase multipath errors,andrespectively pseudorange and carrier phase residual error.

Assuming that the satellite i is observed by u and r at the same time in the current epoch, the single-difference observation equation can be obtained by making a difference between the non-difference observation equation stations, and the formula is as follows:

in the above formula, under the condition of medium and short baselines, the orbit error and the clock error of the single-difference satellite end between stations are basically eliminated, and meanwhile, most of ionospheric delay and flow delay error with strong correlation can be weakened, and the multipath error has no correlation between stations, so the multipath error still exists after the single difference between stations, and in addition, the clock error and the hardware delay of the single-difference receiver end between stations are not eliminated.

Assuming that a certain epoch, u, r observation station observes the satellite i, j simultaneously, a double-difference observation equation can be formed according to the above formula, and the specific expression is as follows:

the multipath error term in the above equation cannot be ignored, and the estimation parameter includes a coordinate parameter term, a multipath error term, and an ambiguity parameter term. In addition, the current GNSS deformation monitoring scheme mostly adopts a single baseline mode, that is, one monitoring station corresponds to one reference station, and the deformation amount of the monitoring point is obtained according to one baseline resolving result, so that the reliability and stability of the result cannot be ensured by the single baseline result affected by the observation environment. The application provides a GNSS deformation monitoring scheme considering multi-path errors.

In the following description, numerous technical details are set forth in order to provide a better understanding of the present application. However, it will be understood by those skilled in the art that the technical solutions claimed in the present application may be implemented without these technical details and with various changes and modifications based on the following embodiments. To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.

An embodiment of the present application discloses a GNSS deformation monitoring method, and fig. 1 is a flowchart of the GNSS deformation monitoring method in the embodiment, where the method includes:

and 101, calculating double-difference residual errors of the satellites according to a double-difference observation equation.

In a preferred embodiment, the step 101 of calculating the double-difference residual of the satellite according to the double-difference observation equation further includes:

constructing a double-difference observation equation, wherein the double-difference observation equation comprises a pseudo-range double-difference observation equation and a carrier phase double-difference observation equation,

the observation of satellite i by station u, the carrier phase and pseudorange non-differential observation range equations can be expressed as follows (in meters):

wherein P and L are pseudoranges anda non-differential observation of the phase of the carrier,geometric distance of satellite to survey station, OⁱFor orbital error, c is the speed of light in vacuum, δ t_uAnd δ tⁱRespectively the receiver and the satellite clock offset,in order to delay the tropospheric delay,for ionospheric delay, DpⁱAnd Dp_uPseudorange hardware delays Dl at satellite and receiver ends, respectivelyⁱAnd Dl_uHardware delay of carrier phase, lambda, at satellite and receiver ends, respectively_uIs the carrier phase wavelength of the current frequency point,the degree of ambiguity of the whole circumference is,anddistributed as pseudorange and carrier phase multipath errors,andrespectively pseudorange and carrier phase residual error.

The observation stations u and r simultaneously observe the satellite i, and the single-difference observation value of the satellite i is expressed by the following formula:

the observation values of the observation stations u and r observing the satellites i and j simultaneously and the double-difference observation values of the satellites i and j are expressed by the following formulas:

in the formula (I), the compound is shown in the specification,the inter-station single difference values of the geometric distances from the satellites i and j to the receiver, respectively, can be expressed by the following formula:

wherein x isⁱ,yⁱ,zⁱAnd x^j,y^j,z^jThe positions of the satellites i and j are obtained by calculating ephemeris orbit parameters,respectively the distance, x, of the satellite i, j to a known reference value r_u,y_u,z_uThe rover position parameter is to be found.

According to the formula, the following formula can be obtained:

wherein the parameters to be estimated in the double-difference observation equation comprise three coordinate parameters x of the rover station_u,y_u,z_uAnd double-difference ambiguity parameter

Carrying out linearization processing on the double-difference observation equation to obtain the following formula:

V＝A·x+B·y-L

wherein, V is a double-difference observation value residual error, A, B is a coordinate parameter and a double-difference ambiguity parameter coefficient array respectively, and L is a difference between an observation value and a calculated value;

calculating and obtaining the estimated value of the parameter to be estimated according to the least square principleFor the floating-point solution of the coordinate parameters,for the double-difference ambiguity parameter floating solution, the lambda method is used to solve the double-difference ambiguity parameter floating solutionFixing to obtain double-difference ambiguity parameter fixing solutionFix the double-difference ambiguity parameterSubstituting the two-difference observation equation to obtain a coordinate parameter fixed solution according to the least square principleFix the coordinate parametersDouble-difference ambiguity parameter fixed solutionAnd substituting the double-difference observation equation to calculate to obtain the double-difference residual value.

Step 102, converting the double-difference residual error of the satellite into a single-difference residual error.

In a preferred embodiment, the step 102 of converting the double-difference residual of the satellite into the single-difference residual converts the double-difference residual into the single-difference residualExpressed as a matrix and single difference residual error according to the following formulaThe product of (a):

in the formula w_iThe weight factor of the i satellite in the baseline solution is represented, if enough observation satellites are assumed, the multipath error in the observed value can be regarded as random noise, and the weighted average value of the single difference residual errors is theoretically zero, namely the weighted average value in the formulaThe double difference residual can be converted to a single difference residual with only multipath error and random noise left by matrix inversion.

In step 103, the repetition period of each satellite is calculated.

In a preferred embodiment, the repetition period of each satellite is calculated according to the following formula:

T_a1＝86400-2(2π/n)

T_a2＝86400-(2π/n)

T_a3＝86400·7-13·(2π/n)

whereinIs the earth's gravitational constant, a is the semi-major axis of the satellite's orbit, n is the angular velocity of the satellite's rotation, Δ n is the perturbation parameter of the average angular velocity, T_a1For GPS satellite repetition period time offset, T_a2For BDS GEO/IGSO satellite repetition period time offset, T_a3The periodic time offset is repeated for the BDS MEO satellites.

For example, since the BDS satellite and the GEO satellite are geosynchronous orbit satellites, which are stationary with respect to the earth, and have a cycle of operation of one sidereal day, and the IGSO satellite has a cycle of operation of one sidereal day, the repetition cycle of the GEO satellite and the IGSO satellite can be regarded as one sidereal day. For the MEO satellite, the operation cycle does not have the characteristic of half a sidereal day or one sidereal day, and according to the minimum common multiple of the operation cycle and the sidereal day, the MEO satellite can be analyzed to run for 13 circles around the earth after running for 7 sidereal day cycles, so that the repetition cycle of the MEO satellite is 7 sidereal days.

And step 104, combining and calculating single-difference residual errors of one period according to the single-difference residual errors of the adjacent previous periods of each satellite.

In a preferred embodiment, the step of calculating the single-difference residual of one period according to the single-difference residuals of several adjacent previous periods of each satellite further includes: and averaging the single difference residuals of the adjacent previous periods.

In the embodiment, the GNSS deformation monitoring observation condition is poor, data is lost due to reasons such as shielding, and data with poor data quality is often removed in the data resolving process, so that the finally obtained satellite single-difference residual error has data loss, and in order to ensure the integrity of the satellite residual error data in one period, adjacent 3 periods of the satellite data are obtained to be merged and averaged, so that complete single-period residual error data are obtained.

And 105, performing empirical mode analysis on the single-difference residual errors obtained through the combination calculation to obtain the multipath error of each satellite.

The multipath error for each satellite is eliminated during baseline resolution, i.e., the computed multipath error is subtracted from the observation equation, step 106.

In the GNSS deformation monitoring method in the embodiment, the multipath error is extracted by using the data of the previous adjacent periods for current data correction, and the real-time correction of the multipath error can be realized. Meanwhile, in order to ensure the integrity of the established multipath model, the satellite single-difference residual errors of the adjacent first 3 periods are adopted to extract multipath errors, and the baseline resolving precision is improved;

in a preferred embodiment, the GNSS deformation monitoring system further includes: selecting a baseline vector as an observed value during net adjustment; forming a function model of unconstrained net adjustment; solving the function model to obtain a mean square value, a correction number and a corresponding precision statistic value of the baseline vector; judging whether the observed value has gross error; if yes, removing or reducing the weight of the observed value, and if not, outputting a final result. The GNSS basic line network adjustment scheme is adopted in the embodiment, the influence of an error basic line on the monitoring network is eliminated, the quality of the monitoring network is improved, the overall monitoring precision is improved, and the method is suitable for millimeter-scale deformation monitoring of complex scenes such as dam bridges, critical houses and iron towers.

In another embodiment of the present application, a GNSS deformation monitoring system is disclosed, and fig. 2 shows a block diagram of the GNSS deformation monitoring system in this embodiment, where the system includes:

a residual obtaining module 201 configured to calculate a double-difference residual of the satellite according to a double-difference observation equation;

a residual transformation module 202 configured to transform the double-difference residual into a single-difference residual;

a period calculation module 203 configured to calculate a repetition period of each satellite;

a combination calculation module 204 configured to calculate single-difference residuals of one period according to the single-difference residuals of adjacent previous periods of each satellite;

an error extraction module 205, configured to perform empirical mode analysis on the single-difference residuals obtained through the merging calculation, and obtain a multipath error of each satellite;

a solution module 206 configured to eliminate the multipath error for each satellite during the baseline solution.

In a preferred embodiment, the residual obtaining module 101 is further configured to:

constructing a double-difference observation equation, wherein the double-difference observation equation comprises a pseudo-range double-difference observation equation and a carrier phase double-difference observation equation,

the observation of satellite i by station u, the carrier phase and pseudorange non-differential observation range equations can be expressed as follows (in meters):

wherein P and L are non-differential observed values of the pseudorange and the carrier phase respectively,geometric distance of satellite to survey station, OⁱFor orbital error, c is the speed of light in vacuum, δ t_uAnd δ tⁱRespectively the receiver and the satellite clock offset,in order to delay the tropospheric delay,for ionospheric delay, DpⁱAnd Dp_uPseudorange hardware delays Dl at satellite and receiver ends, respectivelyⁱAnd Dl_uHardware delay of carrier phase, lambda, at satellite and receiver ends, respectively_uIs the carrier phase wavelength of the current frequency point,fuzzy of whole weekThe degree of the magnetic field is measured,anddistributed as pseudorange and carrier phase multipath errors,andrespectively pseudorange and carrier phase residual error.

The observation stations u and r simultaneously observe the satellite i, and the single-difference observation value of the satellite i is expressed by the following formula:

u, r observation stations simultaneously observe the satellites i, j, and the double-difference observation values of the satellites i, j are expressed by the following formula:

in the formula (I), the compound is shown in the specification,the inter-station single difference values for the satellite i, j to receiver geometric distances, respectively, can be expressed by the following equation:

wherein x isⁱ,yⁱ,zⁱAnd x^j,y^j,z^jThe positions of the satellites i and j are obtained by calculating ephemeris orbit parameters,respectively the distance, x, of the satellite i, j to a known reference value r_u,y_u,z_uThe rover position parameter is to be found.

According to the formula, the following formula can be obtained:

wherein the parameters to be estimated in the double-difference observation equation comprise three coordinate parameters x of the rover station_u,y_u,z_uAnd double-difference ambiguity parameter

Carrying out linearization processing on the double-difference observation equation to obtain the following formula:

V＝A·x+B·y-L

wherein, V is a double-difference observation value residual error, A, B is a coordinate parameter and a double-difference ambiguity parameter coefficient array respectively, and L is a difference between an observation value and a calculated value;

calculating and obtaining the estimated value of the parameter to be estimated according to the least square principleFor the floating-point solution of the coordinate parameters,for the double-difference ambiguity parameter floating solution, the lambda method is used to solve the double-difference ambiguity parameter floating solutionFixing to obtain double-difference ambiguity parameter fixing solutionFix the double-difference ambiguity parameterSubstituting the two-difference observation equation to obtain a coordinate parameter fixed solution according to the least square principleFix the coordinate parametersDouble-difference ambiguity parameter fixed solutionSubstituting the double-difference observation equation to calculate to obtain a double-difference residual value;

in a preferred embodiment, the residual transformation module transforms the residual according to double-difference residualsCan be expressed as a matrix and single difference residual error according to the following formulaThe product of (a):

in the formula w_iRepresenting the weight factors of the i satellites in the baseline solution, assuming enough observation satellitesThe multipath error in the observed value can be regarded as random noise, and the weighted average of the single difference residuals should be theoretically zero, i.e. in the above formulaThe double difference residual can be converted to a single difference residual with only multipath error and random noise left by matrix inversion.

In a preferred embodiment, the period calculating module calculates the repetition period of each satellite according to the following formula:

T_a1＝86400-2(2π/n)

T_a2＝86400-(2π/n)

T_a3＝86400·7-13·(2π/n)

wherein the content of the first and second substances,and a is an earth gravity constant, a is a major semi-axis of a satellite orbit, n is an angular velocity of satellite rotation, and deltan is a perturbation parameter of an average angular velocity.

In a preferred embodiment, the combination calculation module performs an averaging process on the single-difference residuals of the previous adjacent cycles.

In a preferred embodiment, the system further comprises a baseline net adjustment calculation module configured to: selecting a baseline vector as an observed value during net adjustment; forming a function model of unconstrained net adjustment; solving the function model to obtain a mean square value, a correction number and a corresponding precision statistic value of the baseline vector; judging whether the observed value has gross error; if yes, removing or reducing the weight of the observed value, and if not, outputting a final result.

The first embodiment is a system embodiment corresponding to the present embodiment, and the technical details in the first embodiment may be applied to the present embodiment, and the technical details in the present embodiment may also be applied to the first embodiment.

It should be noted that, as will be understood by those skilled in the art, the implementation functions of the modules shown in the above embodiments of the GNSS deformation monitoring system can be understood by referring to the related description of the GNSS deformation monitoring method. The functions of the modules shown in the above embodiments of the GNSS deformation monitoring system may be implemented by a program (executable instructions) running on a processor, and may also be implemented by specific logic circuits. The GNSS deformation monitoring system according to the embodiment of the present disclosure may also be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a stand-alone product. Based on such understanding, the technical solutions of the embodiments of the present specification may be essentially or partially implemented in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present specification. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read Only Memory (ROM), a magnetic disk, or an optical disk. Thus, embodiments of the present description are not limited to any specific combination of hardware and software.

Accordingly, the present specification embodiments also provide a computer-readable storage medium having stored therein computer-executable instructions that, when executed by a processor, implement the method embodiments of the present specification. Computer-readable storage media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable storage medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

In addition, embodiments of the present specification further provide a GNSS deformation monitoring system, which includes a memory for storing computer-executable instructions, and a processor; the processor is configured to implement the steps of the method embodiments described above when executing the computer-executable instructions in the memory.

In one embodiment, the computer-executable instructions may be for:

calculating double-difference residual errors of the satellites according to a double-difference observation equation;

converting the double-difference residual error of the satellite into a single-difference residual error;

calculating the repetition period of each satellite;

the single-difference residual error of one period is calculated according to the single-difference residual errors of the adjacent previous periods of each satellite;

performing empirical mode analysis on the single-difference residual errors obtained by the combination calculation to obtain a multi-path error of each satellite;

the multipath error for each satellite is eliminated during the baseline solution.

In one embodiment, the Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), or the like. The aforementioned memory may be a read-only memory (ROM), a Random Access Memory (RAM), a Flash memory (Flash), a hard disk, or a solid state disk. The steps of the method disclosed in the embodiments of the present invention may be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in the processor. In one embodiment, the system of surface monitoring systems further comprises a bus and a communication interface. The processor, memory and communication interface are all interconnected by a bus. The communication interface may be a wireless communication interface or a wired communication interface for enabling the processor to communicate with other systems.

It is noted that, in the present patent application, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, the use of the verb "comprise a" to define an element does not exclude the presence of another, same element in a process, method, article, or apparatus that comprises the element. In the present patent application, if it is mentioned that a certain action is executed according to a certain element, it means that the action is executed according to at least the element, and two cases are included: performing the action based only on the element, and performing the action based on the element and other elements. The expression of a plurality of, a plurality of and the like includes 2, 2 and more than 2, more than 2 and more than 2.

All documents mentioned in this specification are to be considered as being incorporated in their entirety into the disclosure of this specification so as to be subject to modification as necessary. It should be understood that the above description is only a preferred embodiment of the present disclosure, and is not intended to limit the scope of the present disclosure. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of the present disclosure should be included in the scope of protection of one or more embodiments of the present disclosure.

In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.