Positioning method, device and equipment for geological disaster monitoring and medium

Abstract

The invention discloses a positioning method, device and equipment for geological disaster monitoring, a medium and a product, and the method comprises the steps: receiving global navigation satellite system data under the condition that a geological disaster monitoring starting instruction is detected; the global navigation satellite system data is solved in real time through a precision single-point positioning algorithm solution model, correction information is output, and the precision single-point positioning algorithm solution model is constructed based on a precision single-point positioning algorithm; and sending the correction information and the observation value to a server side, so that the server side performs post differential positioning based on the correction information and the observation value. According to the embodiment of the invention, through a fusion processing method of two data resolving modes of real-time PPP and postmortem PPK, optimal configuration of GNSS data processing is realized, high-precision real-time positioning data can be provided, and the precision and reliability of positioning are further improved by sending the correction information and the observation value to the server side for postmortem differential positioning.

Description

Technical Field

[0001] The present invention relates to the field of Internet technology, and in particular to a positioning method, device, equipment and medium for geological disaster monitoring. Background Art

[0002] GNSS plays an important role in the field of geological disasters. Positioning is the core function and basic service of the GNSS system, which can be divided into relative positioning (representative technologies are real-time kinematic differential positioning RTK (Real-time Kinematic) and post-differential positioning PPK (Post Positioning Kinematic)) and absolute positioning (representative technology is precise point positioning PPP (Precise Point Positioning, PPP)).

[0003] At present, in the relevant technologies, PPK technology is generally used. The existing more mature software includes the Track module in the GAMIT / GLOBK software package. The essence of its solution is to use the discrete Kalman filter algorithm to perform single epoch positioning after fixing the integer ambiguity to obtain the trajectory of the moving carrier. It has not been widely used in the field of deformation monitoring, resulting in low accuracy in geological disaster monitoring and positioning, and cannot meet the real-time, high-precision and high-reliability requirements of modern engineering structure health monitoring. Summary of the invention

[0004] The invention provides a positioning method, device, equipment and medium for geological disaster monitoring.

[0005] In a first aspect, the present invention provides a positioning method for geological disaster monitoring, which is applied to a global navigation satellite system receiver, wherein the global navigation satellite system receiver is equipped with a precise single point positioning algorithm, and the method comprises:

[0006] Receiving GNSS data when a geohazard monitoring start command is detected;

[0007] The global navigation satellite system data is solved in real time by a precise point positioning algorithm solution model, and correction information is output, wherein the precise point positioning algorithm solution model is constructed based on a precise point positioning algorithm;

[0008] The correction information and the observation value are sent to a server side, so that the server side performs post-differential positioning based on the correction information and the observation value.

[0009] Optionally, the performing real-time solving of the global navigation satellite system data by a precise point positioning algorithm solving model and outputting correction information comprises:

[0010] The original pseudorange and carrier phase observation values ​​are linearized to obtain linearized pseudorange and linearized carrier phase observation values;

[0011] The linearized pseudorange is based on the satellite number, the station number, the frequency number, the satellite system, the geometric distance between the satellite and the global navigation satellite system receiver, the receiver clock error, the satellite clock error, the projection function of the tropospheric wet delay, the zenith tropospheric wet delay, the uncalibrated pseudorange hardware delay of the global navigation satellite system receiver, the uncalibrated pseudorange hardware delay of the satellite, and the noise of the pseudorange observation value of the global navigation satellite system receiver;

[0012] The linearized carrier phase observation value is based on the satellite number, the station number, the frequency number, the satellite system, the geometric distance between the satellite and the global navigation satellite system receiver, the receiver clock error, the satellite clock error, the projection function of the tropospheric wet delay, the zenith tropospheric wet delay, the uncorrected carrier phase hardware delay of the global navigation satellite system receiver, the uncorrected carrier phase hardware delay of the satellite, the carrier wavelength, the multipath effect, the phase ambiguity and the carrier observation value noise;

[0013] Constructing a pseudorange and carrier phase dual-frequency precise point positioning non-difference non-combined observation model based on the linearized pseudorange and the linearized carrier phase observation value;

[0014] The first parameter to be estimated in the pseudorange and carrier phase dual-frequency precise single-point positioning non-difference non-combined observation model is estimated to obtain a first parameter estimation value, and the first parameter estimation value is used to output correction information.

[0015] Optionally, estimating a first parameter to be estimated in the pseudorange and carrier phase dual-frequency precise point positioning non-difference non-combined observation model to obtain a first parameter estimate includes:

[0016] The first parameter to be estimated in the pseudorange and carrier phase dual-frequency precise single-point positioning non-difference non-combined observation model is estimated by the least square method or the Kalman filter parameter estimation method to obtain a first parameter estimation value.

[0017] Optionally, the first parameters to be estimated include receiver position parameters, receiver clock error parameters, receiver zenith tropospheric wet delay parameters, slant path ionospheric delay parameters corresponding to each satellite target frequency point, and floating point ambiguity parameters.

[0018] Optionally, the first parameter estimation value includes a floating point ambiguity parameter estimation value, an ionospheric parameter estimation value, and a tropospheric wet delay parameter estimation value.

[0019] Optionally, the observation value includes a Doppler frequency and a geometric factor combined observation value.

[0020] In a second aspect, the present invention provides a positioning method for geological disaster monitoring, which is applied to a server side, and the method comprises:

[0021] Receiving GNSS receiver corrections and observations;

[0022] Performing post-differential positioning based on the correction information and the observation value;

[0023] Among them, the correction information is obtained by the global navigation satellite system receiver receiving global navigation satellite system data when detecting the geological disaster monitoring start-up instruction, and performing real-time solving of the global navigation satellite system data through a precise single point positioning algorithm solution model, and the precise single point positioning algorithm solution model is constructed based on the precise single point positioning algorithm.

[0024] Optionally, the performing post differential positioning based on the correction information and the observation value includes:

[0025] Construct the initial PPK data processing model;

[0026] Fixing the arc segment ambiguity in the initial PPK data processing model according to the floating point ambiguity parameter estimation value in the correction information to obtain the arc segment ambiguity value, and using the arc segment ambiguity value as a virtual observation value;

[0027] Modify the initial PPK data processing model based on the correction information to obtain a target PPK data processing model;

[0028] Estimate the second parameter to be estimated in the target PKT data processing model by using the least squares method or the Kalman filter parameter estimation method to obtain a second parameter estimation value;

[0029] Obtaining a target coordinate result of the global navigation satellite system receiver based on the second parameter estimation value, the virtual observation value and the target PPK data processing model;

[0030] Evaluate satellite observation values ​​for a preset period of time according to the correction information to determine the faulty satellite;

[0031] Eliminate the faulty satellite and establish a post-test random model;

[0032] The positioning result is generated based on the weight value obtained from the posterior random model and the target PKT data processing model.

[0033] In a third aspect, the present invention provides a positioning device for geological disaster monitoring, the device comprising:

[0034] A receiving module, used for receiving global navigation satellite system data when a geological disaster monitoring start instruction is detected;

[0035] A correction information output module, used to perform real-time calculation on the global navigation satellite system data through a precise point positioning algorithm calculation model, and output correction information, wherein the precise point positioning algorithm calculation model is constructed based on a precise point positioning algorithm;

[0036] The positioning module is used to send the correction information and the observation value to the server side, so that the server side performs post-differential positioning based on the correction information and the observation value.

[0037] Optionally, the correction information output module includes:

[0038] The first correction information output module is used to linearize the original pseudorange and carrier phase observation values ​​to obtain linearized pseudorange and linearized carrier phase observation values;

[0039] The linearized pseudorange is based on the satellite number, the station number, the frequency number, the satellite system, the geometric distance between the satellite and the global navigation satellite system receiver, the receiver clock error, the satellite clock error, the projection function of the tropospheric wet delay, the zenith tropospheric wet delay, the uncalibrated pseudorange hardware delay of the global navigation satellite system receiver, the uncalibrated pseudorange hardware delay of the satellite, and the noise of the pseudorange observation value of the global navigation satellite system receiver;

[0040] The linearized carrier phase observation value is based on the satellite number, the station number, the frequency number, the satellite system, the geometric distance between the satellite and the global navigation satellite system receiver, the receiver clock error, the satellite clock error, the projection function of the tropospheric wet delay, the zenith tropospheric wet delay, the uncorrected carrier phase hardware delay of the global navigation satellite system receiver, the uncorrected carrier phase hardware delay of the satellite, the carrier wavelength, the multipath effect, the phase ambiguity and the carrier observation value noise;

[0041] A second correction information output module is used to construct a pseudorange and carrier phase dual-frequency precise single point positioning non-difference non-combined observation model based on the linearized pseudorange and the linearized carrier phase observation value;

[0042] The third correction information output module is used to estimate the first parameter to be estimated in the pseudorange and carrier phase dual-frequency precise single-point positioning non-difference non-combined observation model to obtain a first parameter estimation value, and the first parameter estimation value is used to output correction information.

[0043] Optionally, the third correction information output module includes:

[0044] The correction information output unit is used to estimate the first parameter to be estimated in the pseudorange and carrier phase dual-frequency precise single-point positioning non-difference non-combined observation model by the least square method or the Kalman filter parameter estimation method to obtain a first parameter estimation value.

[0045] Optionally, the device further comprises:

[0046] The second module is used to establish a resource library based on the project data corresponding to the scientific research project, and to edit, control permissions, control external release and share the project data through the resource library.

[0047] In a fourth aspect, the present invention provides a positioning device for geological disaster monitoring, the device comprising:

[0048] A receiving module for receiving correction information and observation values ​​from a global navigation satellite system receiver;

[0049] A positioning module, used for performing post-differential positioning based on the correction information and the observation value;

[0050] Among them, the correction information is obtained by the global navigation satellite system receiver receiving global navigation satellite system data when detecting the geological disaster monitoring start-up instruction, and performing real-time solving of the global navigation satellite system data through a precise single point positioning algorithm solution model, and the precise single point positioning algorithm solution model is constructed based on the precise single point positioning algorithm.

[0051] In a fifth aspect, the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, a positioning method for geological disaster monitoring as described above is implemented.

[0052] In a sixth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a positioning method for geological disaster monitoring as described above.

[0053] In the seventh aspect, the present invention also provides a computer program product, including a computer program / instruction, characterized in that when the computer program / instruction is executed by a processor, it implements any of the positioning methods for geological disaster monitoring as described above.

[0054] In an embodiment of the present invention, a method for applying to a global navigation satellite system receiver is disclosed, and the global navigation satellite system receiver is equipped with a precise single point positioning algorithm. The method includes: receiving global navigation satellite system data when a geological disaster monitoring start instruction is detected; performing real-time calculation on the global navigation satellite system data through a precise single point positioning algorithm calculation model, and outputting correction information, wherein the precise single point positioning algorithm calculation model is constructed based on the precise single point positioning algorithm; sending the correction information and observation values ​​to a server side, so that the server side performs post-differential positioning based on the correction information and the observation values. The positioning method for geological disaster monitoring in the embodiment of the present invention realizes real-time reception and calculation of global navigation satellite system data and outputs correction information by carrying a precise single point positioning algorithm on a global navigation satellite system receiver. The beneficial effect of this method is that, through the fusion processing method of the two data calculation modes of real-time PPP and post-PPK, the optimal configuration of GNSS data processing is realized, and high-precision real-time positioning data can be provided, and the correction information and observation values ​​are sent to the server side for post-differential positioning, which further improves the accuracy and reliability of positioning. This high-precision positioning data is crucial for geological disaster monitoring because it can help identify and assess geological disaster risks in a timely and accurate manner, so that effective prevention and response measures can be taken to protect people’s lives and property. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below.

[0056] Figure 1 The steps of a positioning method for geological disaster monitoring provided in an embodiment of the present invention are as follows: Figure 1 ;

[0057] Figure 2 The steps of a positioning method for geological disaster monitoring provided in an embodiment of the present invention are as follows: Figure 2 ;

[0058] Figure 3 A device block diagram of a positioning device for geological disaster monitoring provided in an embodiment of the present invention;

[0059] Figure 4 A device block diagram of another positioning device for geological disaster monitoring provided in an embodiment of the present invention;

[0060] Figure 5 A schematic diagram of the structure of a communication device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0061] To make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. However, it will be appreciated by those skilled in the art that in the embodiments of the present invention, many technical details are proposed in order to enable the reader to better understand the present application. However, even without these technical details and various changes and modifications based on the following embodiments, the technical scheme claimed in the present application can be implemented. The division of the following embodiments is for the convenience of description, and should not constitute any limitation on the specific implementation of the present invention. The various embodiments can be combined and referenced with each other without contradiction.

[0062] Reference Figure 1 , showing the steps of a positioning method for geological disaster monitoring provided by an embodiment of the present invention Figure 1 , the method may include:

[0063] Step 101, receiving global navigation satellite system data when a geological disaster monitoring start instruction is detected;

[0064] It should be noted that the present application can be applied to geological disaster monitoring scenarios. Therefore, when a geological disaster monitoring start instruction is detected, GNSS data, i.e., global navigation satellite system data, can be received first.

[0065] Specifically, in the present application, the transmission of real-time data stream can be achieved by adopting the NTRIP protocol.

[0066] Step 102, performing real-time calculation on the global navigation satellite system data through a precise point positioning algorithm calculation model, and outputting correction information, wherein the precise point positioning algorithm calculation model is constructed based on a precise point positioning algorithm;

[0067] It should be noted that in the embodiment of the present application, a PPP solution model can be constructed first, and then real-time solution can be performed based on the PPP solution model.

[0068] Among them, the real-time PPP solution process can be realized through IGS products such as CLK93 broadcasted in real time by RTCM-SSR.

[0069] Furthermore, step 102, i.e., performing real-time calculation on the global navigation satellite system data through a precise point positioning algorithm calculation model and outputting correction information includes:

[0070] The original pseudorange and carrier phase observation values ​​are linearized to obtain linearized pseudorange and linearized carrier phase observation values;

[0071] The linearized pseudorange is based on the satellite number, the station number, the frequency number, the satellite system, the geometric distance between the satellite and the global navigation satellite system receiver, the receiver clock error, the satellite clock error, the projection function of the tropospheric wet delay, the zenith tropospheric wet delay, the uncalibrated pseudorange hardware delay of the global navigation satellite system receiver, the uncalibrated pseudorange hardware delay of the satellite, and the noise of the pseudorange observation value of the global navigation satellite system receiver;

[0072] The linearized carrier phase observation value is based on the satellite number, the station number, the frequency number, the satellite system, the geometric distance between the satellite and the global navigation satellite system receiver, the receiver clock error, the satellite clock error, the projection function of the tropospheric wet delay, the zenith tropospheric wet delay, the uncorrected carrier phase hardware delay of the global navigation satellite system receiver, the uncorrected carrier phase hardware delay of the satellite, the carrier wavelength, the multipath effect, the phase ambiguity and the carrier observation value noise;

[0073] Constructing a pseudorange and carrier phase dual-frequency precise point positioning non-difference non-combined observation model based on the linearized pseudorange and the linearized carrier phase observation value;

[0074] The first parameter to be estimated in the pseudorange and carrier phase dual-frequency precise single-point positioning non-difference non-combined observation model is estimated to obtain a first parameter estimation value, and the first parameter estimation value is used to output correction information.

[0075] When processing GNSS data, the original pseudorange p and carrier phase observation value l can be expressed as follows after linearization:

[0076]

[0077] In the above formula 1, s and r are the satellite and station numbers respectively, i is the frequency number and (i=1,2), T represents the GPS, BeiDou, GLONASS and Galileo satellite systems, ρ is the geometric distance from the satellite to the receiver, and dt r and dt s，T are the clock differences between the receiver and the satellite, M w is the projection function of the tropospheric wet delay, Z w is the zenith tropospheric wet delay, is the ionospheric delay of the L1 band in the direction of satellite incidence, and is related to the frequency f i s，T The coefficient of correlation and and They represent the uncalibrated pseudorange hardware delay (Uncalibrated Code Delay, UCD) at the receiver and satellite, respectively. and Respectively represent the uncalibrated carrier phase hardware delay (UPD) at the receiver and satellite ends, is the wavelength of the carrier, is the phase ambiguity with integer characteristics, and are the noise in the pseudorange and carrier phase observations and the unmodeled multipath effect, respectively.

[0078] In addition, GNSS observations are also affected by other system errors, such as the phase center deviation of the receiver and satellite antennas, the rotation of the earth and the relativistic effect, and the ocean tide, which can be corrected or eliminated using the corresponding models. In formula 1, except for the phase ambiguity and UPD, which are in weeks, the other symbols are in meters.

[0079] Further, estimating the first parameter to be estimated in the pseudorange and carrier phase dual-frequency precise single point positioning non-difference non-combined observation model to obtain the first parameter estimate includes:

[0080] The first parameter to be estimated in the pseudorange and carrier phase dual-frequency precise single-point positioning non-difference non-combined observation model is estimated by the least square method or the Kalman filter parameter estimation method to obtain a first parameter estimation value.

[0081] Furthermore, the first parameters to be estimated include receiver position parameters, receiver clock error parameters, receiver zenith tropospheric wet delay parameters, slant path ionospheric delay parameters corresponding to each satellite target frequency point, and floating point ambiguity parameters.

[0082] Furthermore, the first parameter estimation value includes a floating point ambiguity parameter estimation value, an ionospheric parameter estimation value and a tropospheric wet delay parameter estimation value.

[0083] Furthermore, the observation value includes a Doppler frequency and a geometric factor combined observation value.

[0084] The linearized pseudorange and carrier phase dual-frequency PPP non-difference non-combined observation model is constructed as follows:

[0085]

[0086] The DCB correction number at the satellite end can be obtained from the NTRIP broadcast. Formulas 2 and 3 can be further organized as follows:

[0087]

[0088] in,

[0089]

[0090] The first parameters to be estimated corresponding to the non-differenced non-combined PPP model are: receiver position, receiver clock error, receiver zenith direction tropospheric delay parameter, slant path ionospheric delay of each satellite f1 frequency point and dual-frequency non-differenced floating point ambiguity parameter. The collection can be expressed as shown in Formula 6.

[0091]

[0092] At this time, the least squares or Kalman filter parameter estimation method can be used to estimate the first parameter to be estimated, and the floating point ambiguity parameters of each epoch can be obtained. Ionospheric parameters Tropospheric parameter estimation Z w and the combined observations of MW and GF MW and l GF , which is the first parameter estimate, as shown in Formula 7 below.

[0093]

[0094] Step 103: Send the correction information and the observation value to the server side, so that the server side performs post differential positioning based on the correction information and the observation value.

[0095] It should be noted that in the embodiments of the present application, in geological disaster monitoring applications, a precise single-point positioning algorithm can be embedded in the receiver to achieve real-time solution, and output various corrections and information, and transmit them to the server side. During precise positioning, the server side can simultaneously receive the observation values ​​and correction information of each measuring station to achieve PPK positioning.

[0096] In an embodiment of the present invention, a method for applying to a global navigation satellite system receiver is disclosed, and the global navigation satellite system receiver is equipped with a precise single point positioning algorithm. The method includes: receiving global navigation satellite system data when a geological disaster monitoring start instruction is detected; performing real-time calculation on the global navigation satellite system data through a precise single point positioning algorithm calculation model, and outputting correction information, wherein the precise single point positioning algorithm calculation model is constructed based on the precise single point positioning algorithm; sending the correction information and observation values ​​to a server side, so that the server side performs post-differential positioning based on the correction information and the observation values. The positioning method for geological disaster monitoring in the embodiment of the present invention realizes real-time reception and calculation of global navigation satellite system data and outputs correction information by carrying a precise single point positioning algorithm on a global navigation satellite system receiver. The beneficial effect of this method is that, through the fusion processing method of the two data calculation modes of real-time PPP and post-PPK, the optimal configuration of GNSS data processing is realized, and high-precision real-time positioning data can be provided, and the correction information and observation values ​​are sent to the server side for post-differential positioning, which further improves the accuracy and reliability of positioning. This high-precision positioning data is crucial for geological disaster monitoring because it can help identify and assess geological disaster risks in a timely and accurate manner, so that effective prevention and response measures can be taken to protect people’s lives and property.

[0097] In addition, the embodiment of the present invention improves the accuracy and reliability of PPK positioning by using a PPK positioning solution algorithm that adds PPP process information, a method for fixing arc segment ambiguity, and constructing a random model based on PPP post-verification residuals.

[0098] Reference Figure 2 , showing the steps of the positioning method for geological disaster monitoring provided by the embodiment of the present invention Figure 2 , the method may include:

[0099] Step 201, receiving global navigation satellite system receiver correction information and observation values;

[0100] Step 202, performing post-differential positioning based on the correction information and the observation value;

[0101] Among them, the correction information is obtained by the global navigation satellite system receiver receiving global navigation satellite system data when detecting the geological disaster monitoring start-up instruction, and performing real-time solving of the global navigation satellite system data through a precise single point positioning algorithm solution model, and the precise single point positioning algorithm solution model is constructed based on the precise single point positioning algorithm.

[0102] Further, step 202, namely, performing post-differential positioning based on the correction information and the observation value, includes:

[0103] Construct the initial PPK data processing model;

[0104] Fixing the arc segment ambiguity in the initial PPK data processing model according to the floating point ambiguity parameter estimation value in the correction information to obtain the arc segment ambiguity value, and using the arc segment ambiguity value as a virtual observation value;

[0105] Modify the initial PPK data processing model based on the correction information to obtain a target PPK data processing model;

[0106] Estimate the second parameter to be estimated in the target PKT data processing model by using the least squares method or the Kalman filter parameter estimation method to obtain a second parameter estimation value;

[0107] Obtaining a target coordinate result of the global navigation satellite system receiver based on the second parameter estimation value, the virtual observation value and the target PPK data processing model;

[0108] Evaluate satellite observation values ​​for a preset period of time according to the correction information to determine the faulty satellite;

[0109] Eliminate the faulty satellite and establish a post-test random model;

[0110] The positioning result is generated based on the weight value obtained from the posterior random model and the target PKT data processing model.

[0111] It should be noted that in the embodiment of the present application, a simplified PPK data processing model is constructed using the information obtained after PPP solution, such as the definition of the ambiguity arc, ionosphere and troposphere information, satellite availability and signal quality, etc. The specific model is:

[0112] Assume that stations p and q (specifically representing subscript r) observe satellite pair i and j (specifically representing superscript s) at the same epoch, and their pseudorange and carrier phase observation values ​​in double difference form can be expressed as

[0113]

[0114] Among them, in the above formula 8, is a double difference operator. The ionosphere, troposphere and ambiguity parameters in equation 8 can be corrected using the information after PPP solution, which can be specifically expressed as:

[0115]

[0116] Other systematic errors can be eliminated through differential operations.

[0117] According to the ambiguity arc given by PPP, the arc ambiguity is directly fixed in the PPK solution. Specifically, according to the double difference MW and GF combined observation values ​​obtained by formula 9, the floating point ambiguity of L1 and L2 can be obtained as follows:

[0118]

[0119] In the formula, g = f2 / f1. Directly round the above formula ( and ) as the ambiguity value of the arc segment.

[0120] Formula 4 rearranges Formula 8, uses least squares or Kalman filtering for parameter estimation, and uses fixed ambiguity values ​​as virtual observation values ​​for parameter estimation. Specifically, Formula 9 is substituted into Formula 8 and rearranged as

[0121]

[0122] The second parameter to be estimated is

[0123]

[0124] Then, the fixed ambiguity parameters are used as virtual observation values, and Formula 11 is further expressed as

[0125]

[0126] The least squares or Kalman filter estimation is used to obtain a high-precision coordinate result x, and the high-precision coordinate at this time can be the three-dimensional coordinate of the receiver.

[0127] The correction information after PPP solution, that is, the residual information, will be used to evaluate the quality of satellite observations during the period, eliminate faulty satellites, and establish a verified random model for use in PPK data solution.

[0128] It should be noted that in the embodiment of the present application, in the PPP (Precise Point Positioning) solution process, the post-fit residuals refer to the difference between the observed value and the model predicted value after applying the least squares method or other parameter estimation method. These residuals can be used to evaluate the quality of each satellite observation and help identify possible problems. The quality of the observation is evaluated by analyzing the pseudorange and carrier phase residuals of each satellite. Large residuals may indicate that there are problems with the observation, such as multipath effects, satellite failures, receiver problems, etc.

[0129] The residuals of each satellite after PPP solution are divided into segments according to their corresponding satellite altitude angles, with the satellite altitude angles being 1 degree apart, and the mean of the residuals in each segment is calculated. and its standard deviation σ a ;

[0130]

[0131] Where n is the total number of epochs per degree of satellite elevation angle, then the observation accuracy of each degree of satellite elevation angle can be obtained as a Then, the following function model is used to fit the random model, which is specifically expressed as the following formula 16:

[0132]

[0133] Where a and b are the coefficients to be estimated, and θ is the satellite altitude angle. Formula 16 can be applied to PPK data processing, and the standard deviation of the satellite is given by substituting the satellite altitude angle to determine the final weight value.

[0134] It should be noted that in the embodiment of the present application, in PPK (Post-Processing Kinematic) data processing, the satellite altitude angle is an important parameter, which is used to determine the weight of the satellite observation value. The higher the satellite altitude angle, the better the quality of the observation value, because the influence of atmospheric delay and other error sources is smaller. By considering the satellite altitude angle, a corresponding weight can be assigned to each satellite observation value to improve the accuracy and reliability of positioning. Therefore, the weight value obtained by the posterior random model corresponding to the above-constructed formula 16 and the target PKT data processing model generate the positioning result.

[0135] The positioning method for geological disaster monitoring in the embodiment of the present invention realizes real-time reception and solution of global navigation satellite system data and outputs correction information by carrying a precise single-point positioning algorithm on a global navigation satellite system receiver. The beneficial effect of this method is that it can provide high-precision real-time positioning data, and further improve the accuracy and reliability of positioning by sending the correction information and observation values ​​to the server for post-differential positioning. This high-precision positioning data is crucial for geological disaster monitoring because it can help to timely and accurately identify and assess geological disaster risks, thereby taking effective prevention and response measures to protect people's lives and property.

[0136] Reference Figure 3 , Figure 3 A device block diagram of a positioning device for geological disaster monitoring is provided, the device comprising:

[0137] The receiving module 301 is used to receive global navigation satellite system data when a geological disaster monitoring start instruction is detected;

[0138] A correction information output module 302 is used to perform real-time calculation on the global navigation satellite system data through a precise point positioning algorithm calculation model and output correction information, wherein the precise point positioning algorithm calculation model is constructed based on a precise point positioning algorithm;

[0139] The positioning module 303 is used to send the correction information and the observation value to the server side, so that the server side performs post-differential positioning based on the correction information and the observation value.

[0140] Optionally, the correction information output module includes:

[0141] The first correction information output module is used to linearize the original pseudorange and carrier phase observation values ​​to obtain linearized pseudorange and linearized carrier phase observation values;

[0142] The linearized pseudorange is based on the satellite number, the station number, the frequency number, the satellite system, the geometric distance between the satellite and the global navigation satellite system receiver, the receiver clock error, the satellite clock error, the projection function of the tropospheric wet delay, the zenith tropospheric wet delay, the uncalibrated pseudorange hardware delay of the global navigation satellite system receiver, the uncalibrated pseudorange hardware delay of the satellite, and the noise of the pseudorange observation value of the global navigation satellite system receiver;

[0143] The linearized carrier phase observation value is based on the satellite number, the station number, the frequency number, the satellite system, the geometric distance between the satellite and the global navigation satellite system receiver, the receiver clock error, the satellite clock error, the projection function of the tropospheric wet delay, the zenith tropospheric wet delay, the uncorrected carrier phase hardware delay of the global navigation satellite system receiver, the uncorrected carrier phase hardware delay of the satellite, the carrier wavelength, the multipath effect, the phase ambiguity and the carrier observation value noise;

[0144] A second correction information output module is used to construct a pseudorange and carrier phase dual-frequency precise single point positioning non-difference non-combined observation model based on the linearized pseudorange and the linearized carrier phase observation value;

[0145] The third correction information output module is used to estimate the first parameter to be estimated in the pseudorange and carrier phase dual-frequency precise single-point positioning non-difference non-combined observation model to obtain a first parameter estimation value, and the first parameter estimation value is used to output correction information.

[0146] Optionally, the third correction information output module includes:

[0147] The correction information output unit is used to estimate the first parameter to be estimated in the pseudorange and carrier phase dual-frequency precise single-point positioning non-difference non-combined observation model by the least square method or the Kalman filter parameter estimation method to obtain a first parameter estimation value.

[0148] Reference Figure 4 , Figure 4 A device block diagram of a positioning device for geological disaster monitoring is provided, the device comprising:

[0149] A receiving module 401 is used to receive correction information and observation values ​​from a global navigation satellite system receiver;

[0150] A positioning module 402, configured to perform post-differential positioning based on the correction information and the observation value;

[0151] Among them, the correction information is obtained by the global navigation satellite system receiver receiving global navigation satellite system data when detecting the geological disaster monitoring start-up instruction, and performing real-time solving of the global navigation satellite system data through a precise single point positioning algorithm solution model, and the precise single point positioning algorithm solution model is constructed based on the precise single point positioning algorithm.

[0152] In the embodiment of the present invention, digital twin technology is used as a starting point to construct a digital service platform and core functional modules for scientific and technological research, integrate the scientific research results of major projects, realize the intelligent management and display of scientific and technological achievements, visualize the analysis of scientific research data, and digitize and intelligentize the emergency management of safe production, realize efficient access to scientific research results, integrate scientific research data, restore the real-time scene on site, integrate major scientific and technological achievements and progress, comprehensively record and display the execution of scientific research projects, provide objective, detailed and accurate data support and analysis results for scientific research evaluation, establish and access major project sites, key laboratory video images and application systems, identify safety risks through continuous data monitoring and progress tracking, provide decision-making support for safe production and emergency management, integrate scientific research data, realize unified data management, provide unified data interface services, and provide data support for major scientific and technological research.

[0153] The embodiment of the present invention also provides a communication device, such as Figure 5 As shown, it includes a processor 501, a communication interface 502, a memory 503 and a communication bus 504, wherein the processor 501, the communication interface 502, and the memory 503 communicate with each other through the communication bus 504.

[0154] Memory 503, used for storing computer programs;

[0155] The processor 501, when used to execute the program stored in the memory 503, can implement the following steps:

[0156] Receiving GNSS data when a geohazard monitoring start command is detected;

[0157] The global navigation satellite system data is solved in real time by a precise point positioning algorithm solution model, and correction information is output, wherein the precise point positioning algorithm solution model is constructed based on a precise point positioning algorithm;

[0158] The correction information and the observation value are sent to a server side, so that the server side performs post-differential positioning based on the correction information and the observation value.

[0159] or,

[0160] Receiving GNSS receiver corrections and observations;

[0161] Performing post-differential positioning based on the correction information and the observation value;

[0162] Among them, the correction information is obtained by the global navigation satellite system receiver receiving global navigation satellite system data when detecting the geological disaster monitoring start-up instruction, and performing real-time solving of the global navigation satellite system data through a precise single point positioning algorithm solution model, and the precise single point positioning algorithm solution model is constructed based on the precise single point positioning algorithm.

[0163] Among them, the memory and the processor are connected in a bus manner, and the bus may include any number of interconnected buses and bridges, and the bus connects various circuits of one or more processors and memories together. The bus can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits together, which are all well known in the art, so this article will not further describe them. The bus interface provides an interface between the bus and the transceiver. The transceiver can be one element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices on a transmission medium. The data processed by the processor can be transmitted on a wired medium or on a wireless medium through an antenna. Further, the antenna also receives data and transmits the data to the processor. The processor is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. The memory can be used to store data used by the processor when performing operations.

[0164] The communication bus mentioned in the above terminal can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0165] The communication interface is used for communication between the above terminal and other devices.

[0166] The memory may include a random access memory (RAM) or a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0167] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0168] In another embodiment provided by the present invention, a computer-readable storage medium is provided, in which instructions are stored. When the computer-readable storage medium is run on a computer, the computer executes the data downloading method described in any one of the above embodiments.

[0169] In another embodiment of the present invention, a computer program product including instructions is provided. When the computer program product is run on a computer, the computer executes the data downloading method described in any one of the above embodiments.

[0170] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk Solid State Disk (SSD)), etc.

[0171] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0172] Each embodiment in this specification is described in a related manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0173] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.

Claims

1. A positioning method for geological disaster monitoring, characterized in that: Applied to a global navigation satellite system receiver, the global navigation satellite system receiver is equipped with a precise point positioning algorithm, the method comprises: Receiving GNSS data when a geohazard monitoring start command is detected; The global navigation satellite system data is solved in real time by a precise point positioning algorithm solution model, and correction information is output, wherein the precise point positioning algorithm solution model is constructed based on a precise point positioning algorithm; The correction information and the observation value are sent to a server side, so that the server side performs post-differential positioning based on the correction information and the observation value.

2. The method according to claim 1, characterized in that The real-time solving of the global navigation satellite system data by a precise point positioning algorithm solving model and outputting correction information include: The original pseudorange and carrier phase observation values ​​are linearized to obtain linearized pseudorange and linearized carrier phase observation values; Wherein, the linearized pseudorange is based on the satellite number, the station number, the frequency number, the satellite system, the geometric distance between the satellite and the global navigation satellite system receiver, the receiver clock error, the satellite clock error, the projection function of the tropospheric wet delay, the zenith tropospheric wet delay, the uncalibrated pseudorange hardware delay of the global navigation satellite system receiver, the uncalibrated pseudorange hardware delay of the satellite, the uncorrected carrier phase hardware delay of the global navigation satellite system receiver, the uncorrected carrier phase hardware delay of the satellite, the carrier wavelength, and the noise of the pseudorange observation value; The linearized carrier phase observation value is based on the satellite number, the station number, the frequency number, the satellite system, the geometric distance between the satellite and the global navigation satellite system receiver, the receiver clock error, the satellite clock error, the projection function of the tropospheric wet delay, the zenith tropospheric wet delay, the uncorrected carrier phase hardware delay of the global navigation satellite system receiver, the uncorrected carrier phase hardware delay of the satellite, the carrier wavelength, the multipath effect, the phase ambiguity and the carrier observation value noise; Constructing a pseudorange and carrier phase dual-frequency precise point positioning non-difference non-combined observation model based on the linearized pseudorange and the linearized carrier phase observation value; The first parameter to be estimated in the pseudorange and carrier phase dual-frequency precise single-point positioning non-difference non-combined observation model is estimated to obtain a first parameter estimation value, and the first parameter estimation value is used to output correction information.

3. The method according to claim 2, characterized in that The estimating the first parameter to be estimated in the pseudorange and carrier phase dual-frequency precise single point positioning non-difference non-combined observation model to obtain the first parameter estimation value comprises: The first parameter to be estimated in the pseudorange and carrier phase dual-frequency precise single-point positioning non-difference non-combined observation model is estimated by the least square method or the Kalman filter parameter estimation method to obtain a first parameter estimation value.

4. The method according to claim 2, characterized in that The first parameters to be estimated include receiver position parameters, receiver clock error parameters, receiver zenith tropospheric wet delay parameters, slant path ionospheric delay parameters corresponding to each satellite target frequency point, and floating point ambiguity parameters.

5. The method according to claim 2 or 3, characterized in that: The first parameter estimation values ​​include floating point ambiguity parameter estimation values, ionospheric parameter estimation values ​​and tropospheric wet delay parameter estimation values.

6. The method according to claim 1, characterized in that The observation values ​​include Doppler frequency and geometric factor combined observation values.

7. A positioning method for geological disaster monitoring, characterized in that: Applied to the server side, the method includes: Receiving GNSS receiver corrections and observations; Performing post-differential positioning based on the correction information and the observation value; Among them, the correction information is obtained by the global navigation satellite system receiver receiving global navigation satellite system data when detecting the geological disaster monitoring start-up instruction, and performing real-time solving of the global navigation satellite system data through a precise single point positioning algorithm solution model, and the precise single point positioning algorithm solution model is constructed based on the precise single point positioning algorithm.

8. The method according to claim 7, characterized in that The post differential positioning based on the correction information and the observation value comprises: Construct the initial PPK data processing model; Fixing the arc segment ambiguity in the initial PPK data processing model according to the floating point ambiguity parameter estimation value in the correction information to obtain the arc segment ambiguity value, and using the arc segment ambiguity value as a virtual observation value; Modify the initial PPK data processing model based on the correction information to obtain a target PPK data processing model; Estimate the second parameter to be estimated in the target PKT data processing model by using the least squares method or the Kalman filter parameter estimation method to obtain a second parameter estimation value; Obtaining a target coordinate result of the global navigation satellite system receiver based on the second parameter estimation value, the virtual observation value and the target PPK data processing model; Evaluate satellite observation values ​​for a preset period of time according to the correction information to determine the faulty satellite; Eliminate the faulty satellite and establish a post-test random model; The positioning result is generated based on the weight value obtained from the posterior random model and the target PKT data processing model.

9. A positioning device for geological disaster monitoring, characterized in that: The device comprises: A receiving module, used to receive global navigation satellite system data when a geological disaster monitoring start instruction is detected; A correction information output module, used to perform real-time calculation on the global navigation satellite system data through a precise point positioning algorithm calculation model, and output correction information, wherein the precise point positioning algorithm calculation model is constructed based on a precise point positioning algorithm; The positioning module is used to send the correction information and the observation value to the server side, so that the server side performs post-differential positioning based on the correction information and the observation value.

10. The device according to claim 9, characterized in that The correction information output module comprises: The first correction information output submodule is used to linearize the original pseudorange and carrier phase observation values ​​to obtain linearized pseudorange and linearized carrier phase observation values; The linearized pseudorange is based on the satellite number, the station number, the frequency number, the satellite system, the geometric distance between the satellite and the global navigation satellite system receiver, the receiver clock error, the satellite clock error, the projection function of the tropospheric wet delay, the zenith tropospheric wet delay, the uncalibrated pseudorange hardware delay of the global navigation satellite system receiver, the uncalibrated pseudorange hardware delay of the satellite, and the noise of the pseudorange observation value of the global navigation satellite system receiver; The linearized carrier phase observation value is based on the satellite number, the station number, the frequency number, the satellite system, the geometric distance between the satellite and the global navigation satellite system receiver, the receiver clock error, the satellite clock error, the projection function of the tropospheric wet delay, the zenith tropospheric wet delay, the uncorrected carrier phase hardware delay of the global navigation satellite system receiver, the uncorrected carrier phase hardware delay of the satellite, the carrier wavelength, the multipath effect, the phase ambiguity and the carrier observation value noise; A second correction information output submodule is used to construct a pseudorange and carrier phase dual-frequency precise single point positioning non-difference non-combined observation model based on the linearized pseudorange and the linearized carrier phase observation value; The third correction information output submodule is used to estimate the first parameter to be estimated in the pseudorange and carrier phase dual-frequency precise single-point positioning non-difference non-combined observation model to obtain a first parameter estimation value, and the first parameter estimation value is used to output correction information.

11. The device according to claim 9, characterized in that The third correction information output submodule includes: The correction information output unit is used to estimate the first parameter to be estimated in the pseudorange and carrier phase dual-frequency precise single-point positioning non-difference non-combined observation model by the least square method or the Kalman filter parameter estimation method to obtain a first parameter estimation value.

12. A positioning device for geological disaster monitoring, characterized in that: Applied to the server side, the device comprises: A receiving module for receiving correction information and observation values ​​from a global navigation satellite system receiver; A positioning module, used for performing post-differential positioning based on the correction information and the observation value; Among them, the correction information is obtained by the global navigation satellite system receiver receiving global navigation satellite system data when detecting the geological disaster monitoring start-up instruction, and performing real-time solving of the global navigation satellite system data through a precise single point positioning algorithm solution model, and the precise single point positioning algorithm solution model is constructed based on the precise single point positioning algorithm.

13. A communication device, characterized in that: include: A transceiver, a memory, a processor, and a program stored on the memory and executable on the processor; The processor is used to read the program in the memory to implement the positioning method for geological disaster monitoring as described in any one of claims 1-6, or the positioning method for geological disaster monitoring as described in any one of claims 7-8.

14. A readable storage medium for storing a program, characterized in that: When the program is executed by the processor, it implements the positioning method for geological disaster monitoring as described in any one of claims 1-6, or the positioning method for geological disaster monitoring as described in any one of claims 7-8.

15. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by the processor, the positioning method for geological disaster monitoring as described in any one of claims 1-6 is implemented, or the positioning method for geological disaster monitoring as described in any one of claims 7-8.

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