CN115390117B - Precise single-point positioning deformation monitoring method and device - Google Patents

Precise single-point positioning deformation monitoring method and device Download PDF

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CN115390117B
CN115390117B CN202211324013.5A CN202211324013A CN115390117B CN 115390117 B CN115390117 B CN 115390117B CN 202211324013 A CN202211324013 A CN 202211324013A CN 115390117 B CN115390117 B CN 115390117B
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monitoring
coordinate
point
delay information
information
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CN115390117A (en
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杨胜军
邵文翰
李选平
徐彩红
潘林
赵凯
罗丽云
雷海华
汤威
贺湘玲
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Hunan Shanhe Survey And Design Co ltd
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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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B7/00—Measuring arrangements characterised by the use of electric or magnetic techniques
    • G01B7/16—Measuring arrangements characterised by the use of electric or magnetic techniques for measuring the deformation in a solid, e.g. by resistance strain gauge
    • 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
    • G01S19/393—Trajectory determination or predictive tracking, e.g. Kalman filtering
    • 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
    • G01S19/40—Correcting position, velocity or attitude

Abstract

The application provides a method and a device for monitoring precise single-point positioning deformation, which comprise the following steps: s1, acquiring precision correction information, wherein the precision correction information comprises: receiver coordinate information, troposphere delay information and ionosphere delay information of the monitoring points; s2, performing parameter estimation on the coordinate information of the receiver, the troposphere delay information and the ionosphere delay information by adopting Kalman filtering to obtain a precision single-point positioning PPP deformation monitoring resolving result of a monitoring point in a current epoch; wherein, the parameter estimation process comprises: and adding a monitoring point coordinate constraint to the monitoring point, and/or adding an atmosphere delay information constraint to the monitoring point. According to the technical scheme, the monitoring point coordinate constraint and the atmospheric delay information constraint are added to the monitoring point in the monitoring process, the PPP convergence speed is accelerated, the delay influence of hardware at the receiver end is reduced, and the monitoring precision is improved.

Description

Precise single-point positioning deformation monitoring method and device
Technical Field
The application relates to the technical field of satellite positioning, in particular to a method and a device for monitoring precise single-point positioning deformation.
Background
Since the 80 s in the 20 th century, GNSS (Global Navigation Satellite System) has been widely used in deformation monitoring of structures such as volcanoes, landslides, ground subsidence, dams, bridges, and high-rise buildings due to its all-weather, automation, and high precision, and has achieved a great research result. The GNSS high-precision positioning technology includes a relative positioning technology and a PPP (precision point positioning) technology. The relative positioning technology is that two GNSS receivers are utilized to synchronously observe the same GNSS satellite, and the influence of various errors is eliminated or weakened through a difference method, so that the relative position between the measuring stations is measured. The precise single-point positioning technology is a precise ephemeris product issued by organizations such as international GNSS service and the like, and the three-dimensional space coordinate of a measuring station can be solved by fully considering accurate correction of various errors and depending on a single receiver non-differential method. And (3) grasping the deformation rule and the deformation scale of the structure body according to the coordinate displacement sequence by tracking and observing the monitoring points for a long time, thereby carrying out corresponding prediction, early warning and forecast work.
The relative positioning technology has been widely applied in the field of deformation monitoring, has been applied in various aspects such as water reservoir bank landslide, mining area ground cracks, ground subsidence and the like, becomes a very mature GNSS deformation monitoring technology at present, and is applied in various monitoring engineering projects. Some students also try to apply the precise single-point positioning technology to the field of deformation monitoring, such as landslide monitoring, mine deformation monitoring, earthquake displacement monitoring and the like, but the existing precise single-point positioning technology has the problem of long convergence time, usually takes tens of minutes to half an hour, and is not favorable for timely monitoring, early warning and forecasting.
Therefore, how to improve the convergence rate and the monitoring accuracy in the precise single-point positioning deformation monitoring process becomes a problem to be solved.
The above information disclosed in the background section is only for enhancement of understanding of the background of the present application and therefore it may contain information that does not form the prior art that is known to those of ordinary skill in the art.
Disclosure of Invention
The application provides a method and a device for monitoring precise single-point positioning deformation, which are used for solving the problems in the prior art.
In a first aspect, the present application provides a method for monitoring precise single-point positioning deformation, including the following steps: s1, acquiring precision correction information, wherein the precision correction information comprises: receiver coordinate information, troposphere delay information and ionosphere delay information of the monitoring points; s2, performing parameter estimation on the receiver coordinate information, the troposphere delay information and the ionosphere delay information by adopting Kalman filtering to obtain a precision point positioning PPP (Point-to-Point protocol) deformation monitoring resolving result of the monitoring point in the current epoch; wherein, the parameter estimation process comprises: and adding a monitoring point coordinate constraint to the monitoring point, and/or adding an atmospheric delay information constraint to the monitoring point.
In some embodiments, the adding a monitoring point coordinate constraint to the monitoring point comprises: a1. determining a single-day solution coordinate of the monitoring point according to a PPP static calculation result of the monitoring point within preset days, and taking the single-day solution coordinate as an initial coordinate of the monitoring point; a2. and constraining PPP coordinate parameters through the initial coordinates of the monitoring points, and adding a coordinate constraint equation in the Kalman filtering.
In some embodiments, the coordinate constraint equation is expressed as:
Figure 158687DEST_PATH_IMAGE001
Figure 103509DEST_PATH_IMAGE002
wherein, the first and the second end of the pipe are connected with each other,
Figure 455993DEST_PATH_IMAGE003
is the initial coordinate of the monitoring point in the international earth reference coordinate system,
Figure 460858DEST_PATH_IMAGE004
is the coordinate of the monitoring point to be found,
Figure 898793DEST_PATH_IMAGE005
is a correction value for the coordinate constraint that,
Figure 883192DEST_PATH_IMAGE006
is a covariance matrix of virtual observations of the coordinate constraints,
Figure 355761DEST_PATH_IMAGE007
to be the accuracy of the initial coordinates, the coordinates of the initial coordinates,
Figure 265949DEST_PATH_IMAGE008
is the latitude and longitude to which the initial coordinates correspond,
Figure 191179DEST_PATH_IMAGE009
is a transformation matrix for transforming the international earth reference coordinate system to the station center coordinate system.
In some embodiments, further comprising: and newly adding a process noise constraint equation between epochs of the PPP coordinate parameter in the Kalman filtering.
In some embodiments, the inter-epoch process noise constraint equation is expressed as:
Figure 415487DEST_PATH_IMAGE010
wherein, the first and the second end of the pipe are connected with each other,
Figure 804880DEST_PATH_IMAGE011
representing the observation time of the current epoch,
Figure 89231DEST_PATH_IMAGE012
the observation time of the last epoch is shown,
Figure 564075DEST_PATH_IMAGE013
denotes the first
Figure 326494DEST_PATH_IMAGE011
The receiver coordinate parameters of the epoch predictions,
Figure 508077DEST_PATH_IMAGE014
is to assume the inter-epoch variance of the coordinate parameters,
Figure 527111DEST_PATH_IMAGE015
is the process noise added to the coordinate parameters.
In some embodiments, said adding an atmospheric delay information constraint to said monitoring point comprises: b1. acquiring first atmospheric delay information of the monitoring point through PPP dynamic solution, wherein the first atmospheric delay information comprises the troposphere delay information and the ionosphere delay information; b2. acquiring second atmospheric delay information of reference stations around the monitoring point, and acquiring third atmospheric delay information above the monitoring point according to the second atmospheric delay information; b3. adding a tropospheric delay constraint equation to the tropospheric delay information in the first atmospheric delay information and adding an ionospheric delay constraint equation to the ionospheric delay information in the first atmospheric delay information, by the third atmospheric delay information.
In some embodiments, b2, interpolating the atmospheric delay information of the monitoring point by using a triangulation inverse distance weighting method.
In some embodiments, the tropospheric delay constraint equation is specifically expressed as:
Figure 426934DEST_PATH_IMAGE016
wherein the content of the first and second substances,
Figure 55361DEST_PATH_IMAGE017
in order to correct the tropospheric delay by a value,
Figure 91450DEST_PATH_IMAGE018
for the interpolated tropospheric delay parameter for the monitoring point,
Figure 717604DEST_PATH_IMAGE019
for the tropospheric delay parameter in the solution,
Figure 167040DEST_PATH_IMAGE020
is the virtual observation covariance of the tropospheric delay constraint,
Figure 271262DEST_PATH_IMAGE021
is a priori tropospheric delay accuracy.
In some embodiments, the ionospheric delay constraint equation is specifically expressed as:
Figure 427437DEST_PATH_IMAGE022
Figure 286808DEST_PATH_IMAGE023
wherein the content of the first and second substances,
Figure 895644DEST_PATH_IMAGE024
for the ionospheric delay correction value,
Figure 69137DEST_PATH_IMAGE025
star of said monitoring point interpolatedThe inter-single-difference ionospheric delay parameter,
Figure 637740DEST_PATH_IMAGE026
is a coefficient array, and is characterized in that,
Figure 605696DEST_PATH_IMAGE027
for the non-differential ionospheric delay parameter to be solved,
Figure 764145DEST_PATH_IMAGE028
is the virtual observation covariance of the ionospheric delay constraints,
Figure 210170DEST_PATH_IMAGE029
is a priori ionospheric delay accuracy.
In a second aspect, the present application further provides a precise single-point positioning deformation monitoring device, including: an acquisition module for acquiring precision correction information, the precision correction information comprising: receiver coordinate information, troposphere delay information and ionosphere delay information of the monitoring points; the processing module is used for performing parameter estimation on the receiver coordinate information, the troposphere delay information and the ionosphere delay information by adopting Kalman filtering to obtain a precision point positioning PPP (Point-to-Point protocol) deformation monitoring resolving result of the monitoring point in the current epoch; wherein, the parameter estimation process comprises: and adding a monitoring point coordinate constraint to the monitoring point, and/or adding an atmospheric delay information constraint to the monitoring point.
The application provides a precise single-point positioning deformation monitoring method which comprises the following steps: s1, acquiring precision correction information, wherein the precision correction information comprises: receiver coordinate information, troposphere delay information and ionosphere delay information of the monitoring points; s2, performing parameter estimation on the receiver coordinate information, the troposphere delay information and the ionosphere delay information by adopting Kalman filtering to obtain a precision point positioning PPP (Point-to-Point protocol) deformation monitoring resolving result of the monitoring point in the current epoch; wherein, the parameter estimation process comprises: and adding monitoring point coordinate constraint to the monitoring points, and/or adding atmospheric delay information constraint to the monitoring points, so as to accelerate PPP convergence speed, reduce error influence caused by hardware delay at a receiver end, and improve monitoring precision. In the parameter estimation process by adopting Kalman filtering precision correction information, on one hand, the monitoring point coordinate constraint is added to the monitoring point in the monitoring process to accelerate the PPP convergence speed, and the prior constraint information of the parameters of the coordinates, troposphere delay and ionosphere delay is added to accelerate the convergence and error separation of other parameters to quickly obtain a high-precision position solution, so that the problem of PPP reinitialization caused by the interruption of observation data, equipment failure and the daily discontinuity of precision ephemeris is solved; on the other hand, atmospheric delay information constraint is added to the monitoring points in the monitoring process, so that the monitoring precision is improved, the variation range of the parameters can be limited by the constraint on the parameters, and the influences of gross errors, cycle slip and the like on the monitoring results are resisted.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
Fig. 1 is a flowchart illustrating steps of a precise single-point positioning deformation monitoring method according to the present disclosure;
fig. 2 is a comparison graph of monitoring point coordinate constraint and unconstrained PPP monitoring results involved in the precise single-point positioning deformation monitoring method provided by the present application, wherein (a) is the PPP monitoring result of the monitoring point coordinate constraint and unconstrained in the east direction; (b) PPP monitoring results of the coordinate constraint and non-constraint of the monitoring points in the north direction are obtained; (c) The PPP monitoring results of the coordinate constraint and the unconstrained monitoring points in the elevation direction are obtained;
fig. 3 is a comparison diagram of the atmospheric delay information constraint and unconstrained PPP monitoring results involved in the precise point-location deformation monitoring method provided by the present application, where (a) is the atmospheric delay information constraint and unconstrained PPP monitoring results in the east direction; (b) PPP monitoring results of atmosphere delay information constraint and non-constraint in the north direction are obtained; (c) The PPP monitoring results in the elevation direction are the atmospheric delay information constraint and the unconstrained PPP monitoring results.
With the above figures, there are shown specific embodiments of the present application, which will be described in more detail below. These drawings and written description are not intended to limit the scope of the inventive concepts in any manner, but rather to illustrate the inventive concepts to those skilled in the art by reference to specific embodiments.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.
The terminology used in the embodiments of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the embodiments of the present application, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or to implicitly indicate the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present application, "plurality" or "a plurality" means two or more unless specifically limited otherwise.
It should be understood that the structures, ratios, sizes, and the like shown in the drawings are only used for matching the disclosure of the present disclosure to be understood and read by those skilled in the art, and are not used for limiting the practical limitations of the present disclosure, so they do not have the essential technical meaning, and any modifications of the structures, changes of the ratio relationships, or adjustments of the sizes, should still fall within the scope of the technical disclosure of the present disclosure without affecting the function and the achievable purpose of the present disclosure.
It should be understood that the term "and/or" as used herein is merely one type of association that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter associated objects are in an "or" relationship.
The words "if", as used herein, may be interpreted as "at \8230; \8230when" or "when 8230; \823030, when" or "in response to a determination" or "in response to a detection", depending on the context. Similarly, the phrase "if determined" or "if detected (a stated condition or event)" may be interpreted as "upon determining" or "in response to determining" or "upon detecting (a stated condition or event)" or "in response to detecting (a stated condition or event)", depending on the context.
It is also noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a good or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such good or system. Without further limitation, an element defined by the phrases "comprising one of 8230 \8230;" does not exclude the presence of additional like elements in an article or system comprising the element.
Detailed analysis of background art problems:
the relative positioning technology requires stable and reliable datum points to be arranged, and the monitoring points and the datum points are synchronously observed. Under the influence of real geological conditions, electric power and communication, stable reference points with good observation environment can be difficult to arrange in a monitoring area. Meanwhile, when the difference between the reference point and the observation environment of the monitoring point is large, the atmospheric error and the multipath error are difficult to be eliminated, and the deformation monitoring performance is reduced. For the monitoring of earthquake and crust deformation in a very large range, the relative positioning technology is not applicable any more.
The current PPP deformation monitoring resolving equation is as follows:
Figure 340937DEST_PATH_IMAGE030
Figure 542111DEST_PATH_IMAGE031
wherein the content of the first and second substances,
Figure 125539DEST_PATH_IMAGE032
、
Figure 437572DEST_PATH_IMAGE033
respectively receiver pseudorange and carrier phase observations,
Figure 422846DEST_PATH_IMAGE034
is the geometrical distance in space of the receiver to the satellite;
Figure 732604DEST_PATH_IMAGE035
、
Figure 367110DEST_PATH_IMAGE036
respectively the receiver and the satellite clock offset,
Figure 420517DEST_PATH_IMAGE037
indicating that the receiver is tilted to the tropospheric delay,
Figure 260297DEST_PATH_IMAGE038
is the first
Figure 803274DEST_PATH_IMAGE039
The wavelength of the observed value of each frequency,
Figure 95715DEST_PATH_IMAGE040
is shown as
Figure 952812DEST_PATH_IMAGE041
The ionospheric delay factor of each frequency,
Figure 709416DEST_PATH_IMAGE042
represents the diagonal ionospheric delay at the receiver L1 frequency,
Figure 360977DEST_PATH_IMAGE043
、
Figure 406293DEST_PATH_IMAGE044
is as follows
Figure 863819DEST_PATH_IMAGE039
Receiver-side and satellite-side pseudorange hardware delays at each frequency,
Figure 412612DEST_PATH_IMAGE045
for the phase hardware delay at the receiver end,
Figure 500654DEST_PATH_IMAGE046
、
Figure 331469DEST_PATH_IMAGE047
a phase hardware delay stabilization part and a time-varying part for the satellite,
Figure 264790DEST_PATH_IMAGE048
is multipath and unmodeled measurement noise.
And performing parameter estimation on the coordinates of the receiver, troposphere delay, ionosphere delay, ambiguity and the like by using observation data of the monitoring station acquired by the receiver and a precise ephemeris file downloaded by an analysis center such as IGS (integrated satellite System). In the aspect of parameter estimation, an extended Kalman filtering method is selected, the principle is that a recursion algorithm is adopted to predict and measure, update and obtain unknown parameters, and the calculation result of the current epoch is more reliable.
In Kalman filtering, a continuous 'prediction-correction' process is performed on parameter estimation according to an observed value and a predicted value, and the method comprises the following specific steps:
(1) Predicting the next epoch
Figure 995986DEST_PATH_IMAGE049
Figure 254929DEST_PATH_IMAGE050
Wherein the content of the first and second substances,
Figure 743679DEST_PATH_IMAGE051
and
Figure 808587DEST_PATH_IMAGE052
respectively representing the current epoch time and the last epoch observation time,
Figure 331972DEST_PATH_IMAGE053
is shown as
Figure 558554DEST_PATH_IMAGE051
The unknown parameter vector of the epoch is,
Figure 800180DEST_PATH_IMAGE054
is shown as
Figure 340882DEST_PATH_IMAGE052
Epoch to epoch
Figure 282556DEST_PATH_IMAGE051
The system state transition matrix of the epoch is,
Figure 883301DEST_PATH_IMAGE055
is shown as
Figure 346644DEST_PATH_IMAGE052
A covariance matrix of unknown parameters of the epoch,
Figure 753354DEST_PATH_IMAGE056
state parameter process noise arrays.
(2) Calculating a gain matrix
Figure 251332DEST_PATH_IMAGE057
Wherein, the first and the second end of the pipe are connected with each other,
Figure 757399DEST_PATH_IMAGE058
denotes the first
Figure 35934DEST_PATH_IMAGE051
A matrix of observation equation coefficients for epochs, a covariance matrix in which the effect of the gain matrix depends on the state parameters
Figure 918439DEST_PATH_IMAGE059
Covariance matrix of sum observed values
Figure 270923DEST_PATH_IMAGE060
。
(3) Correcting current epoch
Figure 10209DEST_PATH_IMAGE061
Figure 448144DEST_PATH_IMAGE062
Figure 134340DEST_PATH_IMAGE063
Wherein the content of the first and second substances,
Figure 899253DEST_PATH_IMAGE064
is shown as
Figure 12702DEST_PATH_IMAGE065
The observation vector of the epoch is used to estimate,
Figure 937933DEST_PATH_IMAGE066
representing the observation residual vector.
Interpretation of the terms:
kalman filtering: kalman filtering (Kalman filtering) is an algorithm that uses a linear system state equation to optimally estimate the state of a system by inputting and outputting observation data through the system. The optimal estimation can also be seen as a filtering process, since the observed data includes the effects of noise and interference in the system.
The following describes the technical solutions of the present application and how to solve the above technical problems with specific embodiments. These several specific embodiments may be combined with each other below, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.
Fig. 1 is a flowchart illustrating steps of a precise single-point positioning deformation monitoring method according to an embodiment of the present application, and as shown in fig. 1, the present application provides a precise single-point positioning deformation monitoring method, which includes the following steps: s1, acquiring precision correction information, wherein the precision correction information comprises: receiver coordinate information, troposphere delay information and ionosphere delay information of the monitoring points; s2, performing parameter estimation on the receiver coordinate information, the troposphere delay information and the ionosphere delay information by adopting Kalman filtering to obtain a precision point positioning PPP (Point-to-Point protocol) deformation monitoring resolving result of the monitoring point in the current epoch; wherein, the parameter estimation process comprises: and adding a monitoring point coordinate constraint to the monitoring point and/or adding an atmospheric delay information constraint to the monitoring point, so as to accelerate the PPP convergence rate, reduce the error influence caused by the hardware delay of a receiver end and improve the monitoring precision. According to the technical scheme, in the parameter estimation process by adopting Kalman filtering precision correction information, on one hand, the monitoring point coordinate constraint is added to the monitoring point in the monitoring process to accelerate PPP convergence speed, and the prior constraint information of the coordinate, troposphere delay and ionosphere delay parameters is added to accelerate convergence and error separation of other parameters, so that a high-precision position solution is quickly obtained, and the problem of PPP reinitialization caused by interruption of observation data, equipment failure and discontinuity of precision ephemeris every day is solved; on the other hand, atmospheric delay information constraint is added to the monitoring points in the monitoring process, so that the monitoring precision is improved, the variation range of the parameters can be limited by the constraint on the parameters, and the influences of gross errors, cycle slip and the like on the monitoring results are resisted.
It should be noted that, in this embodiment of the present application, in S2, kalman filtering is adopted to perform parameter estimation on the receiver coordinate information, the tropospheric delay information, the ionospheric delay information, the receiver clock error information, and the ambiguity information.
In some embodiments, adding a monitoring point coordinate constraint to a monitoring point comprises:
a1. and determining the single-day solution coordinates of the monitoring points according to the PPP static calculation results of the monitoring points in the preset days, and taking the single-day solution coordinates as the initial coordinates of the monitoring points.
Specifically, in the embodiment of the present application, since the monitoring point is often stable, the preset number of days may be set to one day, one month, or half a year, and the preset number of days is determined according to whether the monitoring point enters the fast sliding period. And performing PPP static calculation on the monitoring points every day to obtain a single-day solution coordinate, wherein the single-day solution coordinate is the initial coordinate of the monitoring points obtained by performing PPP static calculation on the monitoring points every day.
More specifically, in the embodiment of the application, a plurality of single-day solution coordinates form a single-day solution coordinate sequence, the single-day solution coordinate sequence of a plurality of years is analyzed, the deformation trend of the monitoring point can be extracted, and deformation modeling and prediction can be performed according to the deformation trend.
a2. And (3) constraining PPP coordinate parameters through the initial coordinates of the monitoring points, and adding a coordinate constraint equation in Kalman filtering.
Optionally, because the constraint scenario usually focuses on horizontal or elevation direction constraints, the XYZ direction constraint of the initial coordinate in the international earth reference coordinate system is converted into the ENU direction constraint in the station center coordinate system, so as to implement horizontal or elevation direction constraint.
In some embodiments, the coordinate constraint equation is expressed as:
Figure 224558DEST_PATH_IMAGE067
Figure 551634DEST_PATH_IMAGE068
wherein the content of the first and second substances,
Figure 835985DEST_PATH_IMAGE069
is the initial coordinate of the monitoring point in the international earth reference coordinate system,
Figure 45249DEST_PATH_IMAGE070
is the coordinates of the monitoring point to be found,
Figure 73248DEST_PATH_IMAGE071
is the correction value of the coordinate constraint,
Figure 317148DEST_PATH_IMAGE072
is a covariance matrix of virtual observations of the coordinate constraints,
Figure 772400DEST_PATH_IMAGE073
to be the accuracy of the initial coordinates, the coordinates of the initial coordinates,
Figure 672223DEST_PATH_IMAGE008
is the latitude and longitude to which the initial coordinates correspond,
Figure 802115DEST_PATH_IMAGE074
is a transformation matrix for transforming the international earth reference coordinate system to the station center coordinate system.
Specifically, in the embodiment of the present application, the coordinate constraint equation constrains the coordinate parameters based on the precise initial coordinate information.
In some embodiments, further comprising: and a new process noise constraint equation between epochs of the PPP coordinate parameters is added in the Kalman filtering.
Specifically, in the embodiment of the application, initial coordinate constraint is performed on the monitoring point, which is favorable for accelerating PPP convergence, and the problem of PPP calculation reinitialization caused by observation data interruption, equipment failure and precise ephemeris discontinuity every day is solved. Meanwhile, in a stable period, the deformation between the epochs of the monitoring points is small, and corresponding constraint can be added to the process noise between the epochs of the PPP coordinate parameters, so that the PPP positioning stability is improved.
In some embodiments, the inter-epoch process noise constraint equation is expressed as:
Figure 838204DEST_PATH_IMAGE075
wherein the content of the first and second substances,
Figure 464357DEST_PATH_IMAGE011
representing the observation time of the current epoch,
Figure 648214DEST_PATH_IMAGE012
the observation time of the last epoch is represented,
Figure 18016DEST_PATH_IMAGE076
is shown as
Figure 174190DEST_PATH_IMAGE011
The receiver coordinate parameters of the epoch predictions,
Figure 33562DEST_PATH_IMAGE014
is to assume the inter-epoch variation of the coordinate parameters,
Figure 642398DEST_PATH_IMAGE077
is the process noise added to the coordinate parameters.
Fig. 2 is a comparison graph of monitoring point coordinate constraint and unconstrained PPP monitoring results involved in the precise point location deformation monitoring method provided by the present application, and as shown in fig. 2, experimental data is actual engineering monitoring data, and additional prior initial coordinates and coordinate noise constraint between epochs, horizontal 2cm + elevation 2cm constraint, and unconstrained PPP monitoring results are compared. And taking the high-precision initial coordinate as a reference true value, and counting the positioning error in the northeast direction. As can be seen from the experimental results shown in fig. 2, compared with the unconstrained result, the PPP with the additional coordinate constraint can achieve instantaneous convergence, and is beneficial to resisting the influence of gross errors on the PPP result, thereby significantly improving the positioning accuracy in the elevation direction.
In some embodiments, adding atmospheric delay information constraints to the monitoring points includes:
b1. and dynamically obtaining first atmosphere delay information of the monitoring point through PPP, wherein the first atmosphere delay information comprises troposphere delay information and ionosphere delay information.
b2. And acquiring second atmospheric delay information of reference stations around the monitoring point, and acquiring third atmospheric delay information above the monitoring point according to the second atmospheric delay information.
Specifically, in the embodiment of the present application, the PPP static solution can obtain not only the high-precision initial coordinate but also the high-precision second atmosphere delay information.
The ionospheric delay information extracted by the PPP technology absorbs hardware delay at the receiver end, and therefore the ionospheric delay information obtained by the method is differentiated based on the single difference method between the satellites, and the influence of the hardware delay at the receiver end is eliminated.
Optionally, in this embodiment of the present application, the reference sites around the monitoring point include: the CORS (Continuously Operating Reference Stations) or other Reference points around the monitoring point.
Specifically, in the embodiment of the present application, the third atmospheric delay information, that is, the atmospheric delay information above the monitoring point is obtained through a region modeling or interpolation method according to the second atmospheric delay information.
In some embodiments, a triangulation inverse distance weighting method is used in b2 to interpolate third atmosphere delay information of the monitoring points, and the third atmosphere delay information is used for constraining tropospheric delay information and ionospheric delay information.
Specifically, in the embodiment of the present application, the triangulation refers to three reference points, and the atmospheric delay weight of each reference point is determined according to the distance between the three reference points and the monitoring point, for example, the closer the reference point is to the monitoring point, the greater the first atmospheric delay information weight thereof is.
It should be further noted that, in the embodiment of the present application, the inverse distance weighting method may be implemented based on the prior art, and is not described herein again.
b3. Adding a tropospheric delay constraint equation to the tropospheric delay information in the first atmospheric delay information and adding an ionospheric delay constraint equation to the ionospheric delay information in the first atmospheric delay information, by the third atmospheric delay information.
In some embodiments, the tropospheric delay constraint equation is specifically expressed as:
Figure 550311DEST_PATH_IMAGE078
wherein, the first and the second end of the pipe are connected with each other,
Figure 623309DEST_PATH_IMAGE017
for the tropospheric delay correction value,
Figure 591265DEST_PATH_IMAGE018
for the interpolated tropospheric delay parameter for the monitoring point,
Figure 687397DEST_PATH_IMAGE079
for the tropospheric delay parameter in the solution,
Figure 962783DEST_PATH_IMAGE080
is the virtual observation covariance of the tropospheric delay constraint,
Figure 93550DEST_PATH_IMAGE081
is a priori tropospheric delay accuracy.
It should be noted that, in the embodiment of the present application, the tropospheric delay constraint equation is a virtual observation equation established in kalman filtering, and the tropospheric delay constraint equation constrains tropospheric parameters based on precise tropospheric delay information.
In some embodiments, the ionospheric delay constraint equation is specifically expressed as:
Figure 232407DEST_PATH_IMAGE082
Figure 612573DEST_PATH_IMAGE083
wherein the content of the first and second substances,
Figure 127868DEST_PATH_IMAGE024
for the ionospheric delay to be corrected,
Figure 175459DEST_PATH_IMAGE084
for the interpolated inter-satellite single difference ionospheric delay parameters for the monitoring points,
Figure 485217DEST_PATH_IMAGE026
is a coefficient array, and is characterized by that,
Figure 290362DEST_PATH_IMAGE027
for the non-differential ionospheric delay parameter to be solved,
Figure 406086DEST_PATH_IMAGE085
is the virtual observation covariance of the ionospheric delay constraints,
Figure 245866DEST_PATH_IMAGE086
is a priori ionospheric delay accuracy.
Optionally, in this embodiment of the application, different from the troposphere delay constraint equation, the additional ionosphere delay constraint needs to select one reference satellite and perform single difference between the satellites on the ionosphere parameters, so as to eliminate the influence of hardware delay at the receiver.
Specifically, in the embodiment of the present application, the ionospheric delay constraint equation is an ionospheric constraint equation with an additional single difference between stars.
Fig. 3 is a comparison diagram of atmospheric delay information constraint and unconstrained PPP monitoring results involved in the precise point-location deformation monitoring method provided by the present application, and as shown in fig. 3, experimental data is actual engineering monitoring data, and additional prior atmospheric delay constraint, troposphere delay constraint of 5 cm, and ionosphere delay constraint of 2 dm are compared with unconstrained PPP monitoring results. And taking the high-precision initial coordinate as a reference true value, and counting the positioning error in the northeast direction. The experimental results were analyzed: the PPP monitoring sequence with the additional prior atmospheric delay constraint can realize rapid convergence, and is also favorable for improving the positioning precision of the northeast direction.
The application still provides a precision single point location deformation monitoring devices, includes: an acquisition module for acquiring precision correction information, the precision correction information comprising: receiver coordinate information, troposphere delay information and ionosphere delay information of the monitoring points; the processing module is used for performing parameter estimation on the receiver coordinate information, the troposphere delay information and the ionosphere delay information by adopting Kalman filtering to obtain a precise point positioning PPP (Point-to-Point protocol) deformation monitoring resolving result of the monitoring point in the current epoch; wherein, the parameter estimation process comprises: and adding monitoring point coordinate constraint to the monitoring points, and/or adding atmospheric delay information constraint to the monitoring points, so as to accelerate PPP convergence speed, reduce error influence caused by hardware delay at a receiver end, and improve monitoring precision.
It should be understood that, although the respective steps in the flowcharts in the above-described embodiments are sequentially shown as indicated by arrows, the steps are not necessarily performed sequentially as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least some of the steps in the figures may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, in different orders, and may be performed alternately or partially with other steps or at least some of the sub-steps or stages of other steps.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware related to instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, the computer program can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
It will be understood that the present application is not limited to the precise arrangements that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.

Claims (9)

1. A precise single-point positioning deformation monitoring method is characterized by comprising the following steps:
s1, acquiring precision correction information, wherein the precision correction information comprises: receiver coordinate information, troposphere delay information and ionosphere delay information of the monitoring points;
s2, performing parameter estimation on the receiver coordinate information, the troposphere delay information and the ionosphere delay information by adopting Kalman filtering to obtain a precise point positioning PPP (Point-to-Point protocol) deformation monitoring resolving result of the monitoring point in the current epoch;
wherein, the parameter estimation process comprises: adding a monitoring point coordinate constraint to the monitoring point, and/or adding an atmospheric delay information constraint to the monitoring point;
the method for increasing the coordinate constraint of the monitoring points comprises the following steps:
a1. determining a single-day solution coordinate of the monitoring point according to a PPP static calculation result of the monitoring point within preset days, taking the single-day solution coordinate as an initial monitoring point coordinate of the monitoring point, forming a single-day solution coordinate sequence by a plurality of single-day solution coordinates, analyzing the single-day solution coordinate sequence, extracting a deformation trend of the monitoring point, and performing deformation modeling and prediction on the initial monitoring point coordinate according to the deformation trend;
a2. and constraining PPP coordinate parameters through the initial coordinates of the monitoring points, and adding a coordinate constraint equation in the Kalman filtering.
2. The method for monitoring the precision single-point positioning deformation according to claim 1, wherein the coordinate constraint equation is expressed as:
Figure DEST_PATH_IMAGE001
Figure 794838DEST_PATH_IMAGE002
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE003
is the initial coordinate of the monitoring point in the international earth reference coordinate system,
Figure 997411DEST_PATH_IMAGE004
is the coordinate of the monitoring point to be found,
Figure DEST_PATH_IMAGE005
is the correction value of the coordinate constraint,
Figure 48413DEST_PATH_IMAGE006
is a covariance matrix of virtual observations of the coordinate constraints,
Figure DEST_PATH_IMAGE007
to be the accuracy of the initial coordinates, the coordinates of the initial coordinates,
Figure 269309DEST_PATH_IMAGE008
is the latitude and longitude to which the initial coordinates correspond,
Figure DEST_PATH_IMAGE009
is a transformation matrix for transforming the international earth reference coordinate system to the station center coordinate system.
3. The method for monitoring the precise single-point positioning deformation according to claim 2, further comprising: and newly adding a process noise constraint equation between epochs of the PPP coordinate parameter in the Kalman filtering.
4. The method for monitoring the precision single-point positioning deformation according to claim 3, wherein the inter-epoch process noise constraint equation is expressed as:
Figure 249029DEST_PATH_IMAGE010
wherein, the first and the second end of the pipe are connected with each other,
Figure DEST_PATH_IMAGE011
represents the observation time of the current epoch,
Figure 437434DEST_PATH_IMAGE012
the observation time of the last epoch is represented,
Figure DEST_PATH_IMAGE013
is shown as
Figure 308438DEST_PATH_IMAGE011
The receiver coordinate parameters of the epoch predictions,
Figure 665732DEST_PATH_IMAGE014
is to assume the inter-epoch variance of the coordinate parameters,
Figure DEST_PATH_IMAGE015
is the process noise added to the coordinate parameters.
5. The method for monitoring the precise single-point positioning deformation according to claim 1, wherein the adding of the atmospheric delay information constraint to the monitoring point comprises:
b1. acquiring first atmospheric delay information of the monitoring point through PPP dynamic solution, wherein the first atmospheric delay information comprises troposphere delay information and ionosphere delay information;
b2. acquiring second atmospheric delay information of reference stations around the monitoring point, and acquiring third atmospheric delay information above the monitoring point according to the second atmospheric delay information;
b3. adding a tropospheric delay constraint equation to the tropospheric delay information in the first atmospheric delay information and adding an ionospheric delay constraint equation to the ionospheric delay information in the first atmospheric delay information, by the third atmospheric delay information.
6. The method for monitoring the precise single-point positioning deformation according to claim 5, wherein b2, the atmosphere delay information of the monitoring point is interpolated by using a triangulation inverse distance weighting method.
7. The method for monitoring the precise single-point positioning deformation according to claim 5 or 6, wherein the tropospheric delay constraint equation is specifically expressed as:
Figure 331200DEST_PATH_IMAGE016
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE017
in order to correct the tropospheric delay by a value,
Figure 6901DEST_PATH_IMAGE018
for the interpolated tropospheric delay parameter for the monitoring point,
Figure DEST_PATH_IMAGE019
for the tropospheric delay parameter in the solution,
Figure 901170DEST_PATH_IMAGE020
is the virtual observation covariance of the tropospheric delay constraint,
Figure DEST_PATH_IMAGE021
is a priori tropospheric delay accuracy.
8. The method for monitoring the deformation of the precise single-point positioning system according to claim 5 or 6, wherein the ionospheric delay constraint equation is specifically expressed as:
Figure 96659DEST_PATH_IMAGE022
Figure DEST_PATH_IMAGE023
wherein the content of the first and second substances,
Figure 447874DEST_PATH_IMAGE024
for the ionospheric delay to be corrected,
Figure DEST_PATH_IMAGE025
for the interpolated inter-satellite single difference ionospheric delay parameters of the monitoring points,
Figure 846757DEST_PATH_IMAGE026
is a coefficient array, and is characterized in that,
Figure DEST_PATH_IMAGE027
for the non-differential ionospheric delay parameter to be solved,
Figure 793984DEST_PATH_IMAGE028
is the virtual observed covariance of the ionospheric delay constraint,
Figure DEST_PATH_IMAGE029
is a priori ionospheric delay accuracy.
9. A precision single-point positioning deformation monitoring device is characterized by comprising:
an acquisition module for acquiring precision correction information, the precision correction information comprising: receiver coordinate information, troposphere delay information and ionosphere delay information of the monitoring points;
the processing module is used for performing parameter estimation on the receiver coordinate information, the troposphere delay information and the ionosphere delay information by adopting Kalman filtering to obtain a precision point positioning PPP (Point-to-Point protocol) deformation monitoring resolving result of the monitoring point in the current epoch;
wherein, the parameter estimation process comprises: adding a monitoring point coordinate constraint to the monitoring point, and/or adding an atmospheric delay information constraint to the monitoring point;
the processing module is further used for determining single-day solution coordinates of the monitoring points according to PPP static calculation results of the monitoring points within preset days, taking the single-day solution coordinates as initial coordinates of the monitoring points, forming a single-day solution coordinate sequence by a plurality of single-day solution coordinates, analyzing the single-day solution coordinate sequence, extracting deformation trends of the monitoring points, and performing deformation modeling and prediction on the initial coordinates of the monitoring points according to the deformation trends; and restricting PPP coordinate parameters through the initial coordinates of the monitoring points, and adding a coordinate restriction equation in the Kalman filtering.
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