Geological disaster monitoring method, device and equipment based on GNSS (Global Navigation Satellite System) and medium

Abstract

The embodiment of the invention provides a geological disaster monitoring method and device based on GNSS, equipment and a medium. The method comprises the following steps: acquiring a carrier phase observation value and a pseudo-range observation value acquired by a single observation station in a global navigation satellite system (GNSS) for an orbit period of any satellite; constructing an ionosphere-free combined GNSS observation equation based on the carrier phase observation value and the pseudo-range observation value; converting the ionosphere-free combined GNSS observation equation into a matrix form; performing least square solution on the ionosphere-free combined GNSS observation equation in the matrix form to obtain an ambiguity floating point solution parameter corresponding to the orbit period of the current satellite; determining a precise point positioning ambiguity fixed solution according to the ambiguity floating point solution parameter and a least square model; and positioning an ambiguity fixed solution according to a precise single point. According to the invention, the fixed ambiguity of the GNSS observation data of a single observation station can be realized, and the geological structure change can be accurately monitored.

Description

Technical Field

[0001] The present invention relates to the field of geographical technology, and in particular to a GNSS-based geological disaster monitoring method, a GNSS-based geological disaster monitoring device, an electronic device and a computer-readable medium. Background Art

[0002] In geological disaster monitoring, GNSS data is mostly solved in the form of an observation network to form a baseline between each station. If the double difference mode is used, the difference between GNSS observation sites can eliminate common errors at the observation value level; while in the non-difference precision single point positioning solution model, the GNSS observation network can serve to fix the ambiguity and achieve precise positioning.

[0003] Although the base station network solution is more rigorous and reliable in theory, it mainly faces the following problems: 1) The number of observation stations has increased dramatically, and it is difficult to solve the data in the entire network. When the number of observation stations is large, the number of parameters to be estimated in the parameter estimation model is huge, and it is difficult for general computers to process it. If the network solution is adopted, the advantage of the rigor of the base station network solution will be weakened. 2) The observation environment and equipment status of each station in the base station network are not uniform. The data quality of the observation value is closely related to the observation environment and hardware equipment of the station, but in the base station network solution, it is impossible to evaluate the quality of all data and give a reasonable weight ratio. When the data quality is poor, it may even propagate errors through the solution model, affecting the positioning results of other stations in the network. 3) Although the ambiguity fixed solution of single-station precise single-point positioning can be obtained through the wide and narrow lane ambiguity fractional cycle bias correction method, it is heavily dependent on external correction information. At the same time, the fractional cycle bias (FCB) correction parameter is also obtained through the base station network solution. Summary of the invention

[0004] The embodiment of the present invention provides a GNSS-based geological disaster monitoring method, device, electronic device and computer-readable storage medium, so as to obtain a GNSS precise point positioning (PPP, Precise Point Positioning) ambiguity fixed solution for geological disaster monitoring without relying on external decimal week deviation correction.

[0005] The embodiment of the present invention discloses a geological disaster monitoring method based on GNSS, comprising:

[0006] For any satellite's orbital period, obtain the carrier phase observations and pseudorange observations collected by a single station in the Global Navigation Satellite System (GNSS);

[0007] Constructing an ionospheric-free combined GNSS observation equation based on the carrier phase observation value and the pseudorange observation value;

[0008] Converting the ionospheric-free combined GNSS observation equation into a matrix form;

[0009] Performing a least squares solution on the ionosphere-free combined GNSS observation equation in the matrix form to obtain ambiguity floating-point solution parameters corresponding to the orbital period of the current satellite;

[0010] Determining a precise point positioning ambiguity fixed solution according to the ambiguity floating point solution parameters and a least squares model;

[0011] Based on the precise point positioning ambiguity fixed solution, the geological structure changes are monitored to determine whether a geological disaster is likely to occur.

[0012] Optionally, the pseudo-range observation value collected by a single measuring station in the global navigation satellite system GNSS is linearized and expressed as:

[0013]

[0014] Where 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 in the station, and dt r and dt s,T are the clock errors of the receiver and satellite in the station, 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 frequency The coefficient of correlation and and represent the uncalibrated pseudorange hardware delays at the receiver and satellite ends in the station, and denote the uncorrected carrier phase hardware delays at the receiver and satellite ends in the station, is the wavelength of the carrier, is the phase ambiguity with integer characteristics, is the noise in the pseudorange observations and the unmodeled multipath effect.

[0015] Optionally, the carrier phase observation value collected by a single measuring station in the global navigation satellite system GNSS is expressed after being personalized as follows:

[0016]

[0017] Where 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 in the station, and dt r and dt s,T are the clock errors of the receiver and satellite in the station, 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 frequency The coefficient of correlation and and represent the uncalibrated pseudorange hardware delays at the receiver and satellite ends in the station, and denote the uncorrected carrier phase hardware delays at the receiver and satellite ends in the station, is the wavelength of the carrier, is the phase ambiguity with integer characteristics, is the noise in the carrier phase observation and the unmodeled multipath effect.

[0018] Optionally, the ionosphere-free combined GNSS observation equation constructed based on the carrier phase observation value and the pseudorange observation value is expressed as:

[0019]

[0020] in,

[0021] Where i is the satellite number, p is the receiver in the station. P is the original pseudorange observation value, L is the carrier phase observation value. λ1 is the wavelength of the carrier phase observation value of the first frequency of the GNSS satellite, represents the geometric distance from satellite i to receiver p in the measuring station; c is the speed of light in vacuum; dt p 、dt i They represent the clock difference between the receiver and the satellite in the station, in seconds; T is the tropospheric delay caused by the satellite signal passing through the atmosphere; b p 、b i are the pseudorange hardware delays of the receiver and satellite in the station; N is the ionospheric-free combination form of the carrier phase integer ambiguity; B p , B iare the carrier phase hardware delays of the receiver in the measuring station and the satellite end respectively; e and ε are the observation noises of the ionospheric-free combination of pseudorange and carrier phase including multipath information.

[0022] Optionally, the step of converting the ionospheric-free combined GNSS observation equation into a matrix form comprises:

[0023] Assume that the station coordinate parameter is vector x, the ambiguity parameter is b, and the other parameters to be estimated are u. The coefficient matrices corresponding to the parameters at any epoch are A e , B e , C e ; Then the observation equation can be written in matrix form as

[0024] v e =A e x+B e b+C e ul e ,P e

[0025] Among them, v e is the residual vector, l e is the vector of observed values ​​minus calculated values, and the weight matrix of observed values ​​is P e .

[0026] Alternatively, the normal equation for any epoch is:

[0027]

[0028] Alternatively, the normal equation for all epochs is:

[0029]

[0030] Among them, N and w are vectors obtained by superimposing the elements in the normal equation of any epoch.

[0031] Optionally, the step of performing least squares solution on the ionosphere-free combined GNSS observation equation in the matrix form to obtain ambiguity floating-point solution parameters corresponding to the orbital period of the current satellite includes:

[0032] The least squares solution of the normal equations of all epochs is performed to obtain the ambiguity floating point solution parameters corresponding to the orbital period of the current satellite, which is expressed as:

[0033]

[0034] Where Q is the variance-covariance matrix obtained after the solution. Assuming the number of observations and the number of parameters to be estimated are n and t respectively, the unit weight variance is for:

[0035]

[0036] Optionally, the step of determining a precise point positioning ambiguity fixed solution according to the ambiguity floating point solution parameters and a least squares model comprises:

[0037] The ambiguity floating point solution parameters are decomposed into wide lane ambiguity and narrow lane ambiguity with integer characteristics, which are expressed as:

[0038]

[0039] Where g = f1 / f2, is the floating point wide lane ambiguity, is a floating point narrow lane ambiguity; for the wide lane ambiguity, the satellite hardware delay and the hardware delay of the receiver in the measuring station are eliminated to obtain a double difference wide lane ambiguity;

[0040] Eliminating the satellite hardware delay and the hardware delay of the receiver in the measuring station for the narrow lane ambiguity to obtain a double difference narrow lane ambiguity;

[0041] The double-difference wide lane ambiguity and the double-difference narrow lane ambiguity are solved using a least squares model to obtain a precise single point positioning ambiguity fixed solution.

[0042] Optionally, the step of eliminating satellite hardware delay and hardware delay of a receiver in a measuring station for the wide lane ambiguity to obtain a double difference wide lane ambiguity comprises:

[0043] The wide lane ambiguity of the floating point is expressed as a non-integer form, and the wide lane ambiguity of the floating point for two consecutive days is expressed as:

[0044]

[0045] Among them, subscript 1 represents the first day, subscript 2 represents the second day, is the satellite hardware delay, δη p(wl) is the receiver hardware delay in the station, and

[0046] The wide lane ambiguity of the floating point for two consecutive days is differentiated to eliminate the satellite hardware delay, and the hardware delay of the receiver in the station is eliminated by using inter-satellite difference. The obtained double difference wide lane ambiguity is expressed as:

[0047]

[0048] Optionally, the step of eliminating satellite hardware delay and hardware delay of a receiver in a measuring station for the narrow lane ambiguity to obtain a double difference narrow lane ambiguity comprises:

[0049] The narrow lane ambiguity of the floating point for two consecutive days is differentiated to eliminate the satellite hardware delay, and the hardware delay of the receiver in the station is eliminated by using inter-satellite difference. The obtained double-difference narrow lane ambiguity is expressed as:

[0050]

[0051] Optionally, the step of solving the double-difference wide lane ambiguity and the double-difference narrow lane ambiguity using a least squares model to obtain a fixed solution for the precise point positioning ambiguity includes:

[0052] Determine the double-difference ionospheric-free combined ambiguity parameter based on the double-difference wide-lane ambiguity and the double-difference narrow-lane ambiguity It is expressed as:

[0053]

[0054] The double-difference ionospheric-free combined ambiguity parameters are used as virtual observation values, and the vector of the virtual observation values ​​is expressed as:

[0055] v b =Db-b c ,P b

[0056] b c is the fixed solution of the double-difference ionosphere-free combined precise point positioning ambiguity, D is the ambiguity mapping matrix, P b is the weight of the virtual observation value, which is preset to 10 10 ;

[0057] The vector of the virtual observation value is superimposed on the ambiguity floating point solution parameter corresponding to the orbital period of the current satellite, which is expressed as:

[0058]

[0059] in,

[0060]

[0061] The vector of the virtual observation value is superimposed on the ambiguity floating point solution parameter corresponding to the orbital period of the current satellite, and a least squares solution is performed to obtain a precise single point positioning ambiguity fixed solution.

[0062] The embodiment of the present invention further discloses a GNSS-based geological disaster monitoring device, comprising:

[0063] An observation value acquisition module is used to obtain carrier phase observation values ​​and pseudorange observation values ​​collected by a single measurement station in the global navigation satellite system GNSS for the orbit period of any satellite;

[0064] An observation equation determination module, used for constructing an ionosphere-free combined GNSS observation equation based on the carrier phase observation value and the pseudorange observation value;

[0065] A conversion module, used for converting the ionosphere-free combined GNSS observation equation into a matrix form;

[0066] A solution module, used for performing least squares solution on the ionosphere-free combined GNSS observation equation in the matrix form to obtain ambiguity floating point solution parameters corresponding to the orbital period of the current satellite;

[0067] A precise point positioning ambiguity fixed solution determination module, used to determine the precise point positioning ambiguity fixed solution according to the ambiguity floating point solution parameters and the least squares model;

[0068] The monitoring module is used to monitor the changes in geological structure based on the precise single-point positioning ambiguity fixed solution to determine whether a geological disaster may occur.

[0069] The embodiment of the present invention further discloses an electronic device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

[0070] The memory is used to store computer programs;

[0071] The processor is used to implement the method described in the embodiment of the present invention when executing the program stored in the memory.

[0072] The embodiment of the present invention further discloses one or more computer-readable media on which instructions are stored. When executed by one or more processors, the processors are enabled to execute the method described in the embodiment of the present invention.

[0073] The embodiments of the present invention include the following advantages:

[0074] According to the GNSS-based geological disaster monitoring method provided by the embodiment of the present invention, for the orbital period of any satellite, the carrier phase observation value and pseudo-range observation value collected by a single station in the global navigation satellite system GNSS are obtained; the ionosphere-free combined GNSS observation equation is constructed based on the carrier phase observation value and the pseudo-range observation value; the ionosphere-free combined GNSS observation equation is converted into a matrix form; the ionosphere-free combined GNSS observation equation in the matrix form is solved by least squares to obtain the ambiguity floating point solution parameters corresponding to the orbital period of the current satellite; the precise single-point positioning ambiguity fixed solution is determined according to the ambiguity floating point solution parameters and the least squares model; the geological structure changes are monitored according to the precise single-point positioning ambiguity fixed solution to determine whether geological disasters may occur. It can be achieved by relying on the fixed ambiguity of the GNSS observation data of a single station, without the need to perform the baseline group between stations, greatly alleviating the pressure of solving the large-scale reference station network, not being affected by the quality of the observation data of other stations, not relying too much on external correction information, and the theoretical model is simple, and the same solution effect of the reference station network can be obtained, so as to realize accurate monitoring of geological structure changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 is a flowchart of a method for monitoring geological disasters based on GNSS provided in an embodiment of the present invention;

[0076] Figure 2 It is a structural block diagram of a GNSS-based geological disaster monitoring device provided in an embodiment of the present invention;

[0077] Figure 3 is a block diagram of an electronic device provided in an embodiment of the present invention;

[0078] Figure 4 is a schematic diagram of a computer-readable medium provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0079] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0080] Reference Figure 1 , shows a flowchart of a method for monitoring geological disasters based on GNSS provided in an embodiment of the present invention, which may specifically include the following steps:

[0081] Step 101, for any satellite's orbital period, obtain carrier phase observations and pseudorange observations collected by a single station in a global navigation satellite system GNSS;

[0082] In the embodiment of the present invention, in order to calculate relatively accurate geographic positioning, the carrier phase observation value and pseudorange observation value collected by a single station in the global navigation satellite system GNSS can be first obtained for the orbital period of any satellite.

[0083] The pseudo-range observation value collected by a single station in the global navigation satellite system GNSS is linearized and expressed as:

[0084]

[0085] The carrier phase observation value collected by a single measuring station in the global navigation satellite system GNSS is expressed as follows after being personalized:

[0086]

[0087] Where 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 in the station, and dt r and dt s,T are the clock errors of the receiver and satellite in the station, 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 frequency The coefficient of correlation and and represent the uncalibrated pseudorange hardware delays at the receiver and satellite ends in the station, and denote the uncorrected carrier phase hardware delays at the receiver and satellite ends in the station, is the wavelength of the carrier, is the phase ambiguity with integer characteristics, is the noise of the pseudorange observations and the unmodeled multipath effect, is the noise in the carrier phase observation and the unmodeled multipath effect.

[0088] 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 tide, which can be corrected or eliminated using the corresponding models. Except for the phase ambiguity and UPD, which are in weeks, the remaining symbols are in meters.

[0089] Step 102, constructing an ionospheric-free combined GNSS observation equation based on the carrier phase observation value and the pseudorange observation value;

[0090] In the specific implementation, in order to eliminate the first-order term of the ionosphere, the dual-frequency ionosphere-free combined observation value is usually used to construct a mathematical model, which is expressed as follows:

[0091]

[0092] in,

[0093]

[0094] The above formula can be further expressed as

[0095]

[0096] in, Where: i represents the satellite number, p represents the receiver. P is the original pseudorange observation value, L is the carrier phase observation value. λ1 is the wavelength of the carrier phase observation value of the first frequency of the GNSS satellite, represents the geometric distance from satellite i to receiver p; c is the speed of light in vacuum; dt p 、dt i represents the clock difference of the receiver and the satellite respectively, in seconds; T is the tropospheric delay caused by the satellite signal passing through the atmosphere; b p 、b i are the pseudorange hardware delays of the receiver and the satellite respectively; N is the carrier phase integer ambiguity ionosphere-free combination form; B p , B i are the carrier phase hardware delays of the receiver and satellite, respectively; e and ε are the observation noises of the pseudorange and carrier phase ionosphere-free combination including multipath information.

[0097] Step 103, converting the ionospheric-free combined GNSS observation equation into a matrix form;

[0098] In the specific implementation, during the high-precision positioning process, precise ephemeris and clock error products are generally used to obtain precise satellite orbits and clock errors, and these two parameters are fixed. Other errors such as satellite and receiver antenna phase center corrections, phase winding errors, relativistic effects, ocean load tides, etc. will be corrected using theoretical or empirical models.

[0099] Therefore, the parameters to be estimated in the ionosphere-free combined GNSS observation equation are only the station position, receiver clock error, zenith tropospheric delay and ambiguity parameters.

[0100] Assume that the station coordinate parameter is vector x, the ambiguity parameter is b, and the other parameters to be estimated are u. The coefficient matrices corresponding to the parameters at any epoch are Ae , B e , C e ; Then the observation equation can be written in matrix form as

[0101] v e =A e x+B e b+C e ul e ,P e

[0102] Among them, v e is the residual vector, l e is the vector of observed values ​​minus calculated values, and the weight matrix of observed values ​​is P e .

[0103] Specifically, the normal equation for any epoch is:

[0104]

[0105] Specifically, the normal equation for all epochs is:

[0106]

[0107] Wherein, N is the matrix obtained by superimposing the elements in the normal equation of any epoch, and w is the vector obtained by superimposing the elements in the normal equation of any epoch.

[0108] Optionally, the step of performing least squares solution on the ionosphere-free combined GNSS observation equation in the matrix form to obtain ambiguity floating-point solution parameters corresponding to the orbital period of the current satellite includes:

[0109] The least squares solution of the normal equations of all epochs is performed to obtain the ambiguity floating point solution parameters corresponding to the orbital period of the current satellite, which is expressed as:

[0110]

[0111] Where Q is the variance-covariance matrix obtained after the solution. Assuming the number of observations and the number of parameters to be estimated are n and t respectively, the unit weight variance is for:

[0112]

[0113] Step 104, performing a least squares solution on the ionosphere-free combined GNSS observation equation in the matrix form to obtain ambiguity floating point solution parameters corresponding to the orbital period of the current satellite;

[0114] Step 105, determining a precise point positioning ambiguity fixed solution according to the ambiguity floating point solution parameters and a least squares model;

[0115] Specifically, the ambiguity floating point solution of the station precise point positioning can be obtained based on the ionosphere-free combined GNSS observation equation in matrix form, that is, the ambiguity is a non-integer value. The ionosphere-free combined ambiguity itself does not have an integer characteristic. In order to restore the integer characteristic of the ambiguity, the IF combined ambiguity can be decomposed into wide lane and narrow lane ambiguities with integer characteristics, and the ambiguity fixed solution can be obtained by fixing them.

[0116] Therefore, the ambiguity floating point solution parameters are decomposed into wide lane ambiguity and narrow lane ambiguity with integer characteristics, which are expressed as:

[0117]

[0118] Where g = f1 / f2, is the floating point wide lane ambiguity, is the narrow lane ambiguity of floating point;

[0119] Thereafter, the satellite hardware delay and the hardware delay of the receiver in the measuring station may be eliminated for the wide lane ambiguity to obtain a double difference wide lane ambiguity;

[0120] Specifically, the wide lane ambiguity parameters can be obtained by taking the Hatch-Melbourne–Wübbena (HMW) combined average of the entire continuous ambiguity arc segment, that is,

[0121]

[0122] Due to the hardware delay between the satellite and the receiver, the wide lane ambiguity obtained by the above formula is in non-integer form, that is,

[0123]

[0124] in, and δη p(wl) The hardware delays of the satellite and the receiver in the station cause the wide lane ambiguity to be non-integer and cannot be rounded directly. The current solution is: 1) Use the reference station network to form a baseline and construct a double-difference MW combined observation value to eliminate δη p(wl) and ; 2) For single-station data solution, inter-satellite single difference can be used to eliminate the hardware delay at the receiver end, and then the satellite FCB product obtained through global or regional network solution can be used for correction.

[0125] For example, the repetition period of the GPS satellite constellation is 23 hours, 56 minutes and 04 seconds, which is close to 24 hours (one solar day). In the current base station network solution and high-precision positioning applications, GPS data solutions are all processed in 24-hour periods. However, within 24 hours, a single station has only one complete arc segment relative to each GPS satellite. If 48 hours, that is, two consecutive days of data, are used for solution, a single station and satellite will have two complete arc segments. During the data processing process, if only one set of position parameters is set for two days of data (that is, the coordinates of the two-day station are considered constant), the zenith troposphere and receiver clock errors are still estimated according to the original strategy, then the ambiguity parameters are twice that of the single-day solution (assuming that the working status of each satellite is the same and no cycle slip occurs in the complete arc segment).

[0126]

[0127] Where, the subscripts 1 and 2 represent the wide-lane ambiguity parameters of the corresponding day’s floating point. Satellite hardware delay Has the property of remaining stable over a period of time (several months), then

[0128]

[0129] It can be seen that the hardware delay of the satellite end can be eliminated by performing floating-point wide-lane ambiguity difference calculation on the arc segments of the same satellite for two consecutive days. If the hardware delay δηp of the receiver in the measurement station is eliminated by using inter-satellite difference ( wl), the double-difference wide-lane ambiguity can be expressed as

[0130]

[0131] Therefore, the double-difference widelane ambiguity will have an integer nature.

[0132] In order to determine whether the above double-difference wide lane ambiguity can be fixed to an integer, the present invention sequentially substitutes the estimated value and standard deviation of the floating-point double-difference wide lane ambiguity into the decision function for verification:

[0133]

[0134] in,

[0135]

[0136] Where n is the floating point double difference ambiguity estimate, σ is the standard deviation of the ambiguity, and N is the integer value closest to n. Given a confidence level α, if the probability ξ that the ambiguity can be fixed to an integer is greater than 1-α, the floating point ambiguity n can be fixed to N. Usually α is taken as 0.1%. In order to avoid incorrect fixing of the ambiguity, if the decimal part of the floating point ambiguity is greater than the threshold, that is,

[0137] |n-round(n)|>0.2cycle

[0138] No matter how small the standard deviation is, the ambiguity parameter still retains a floating point solution. 0.2 is an empirical value.

[0139] Further, for the narrow lane ambiguity, a satellite hardware delay and a receiver hardware delay in the measuring station are eliminated to obtain a double difference narrow lane ambiguity;

[0140] Specifically, referring to the calculation method of double-difference wide-lane ambiguity, the double-difference narrow-lane ambiguity can also be obtained: It is expressed as:

[0141]

[0142] Afterwards, a calculation method similar to the double-difference wide lane ambiguity is further adopted to verify the fixed narrow lane ambiguity through the decision function.

[0143] The double-difference wide lane ambiguity and the double-difference narrow lane ambiguity are solved using a least squares model to obtain a precise single point positioning ambiguity fixed solution.

[0144] Determine the double-difference ionospheric-free combined ambiguity parameter based on the double-difference wide-lane ambiguity and the double-difference narrow-lane ambiguity It is expressed as:

[0145]

[0146] The double-difference ionospheric-free combined ambiguity parameters are used as virtual observation values, and the vector of the virtual observation values ​​is expressed as:

[0147] v b =Db-b c ,P b

[0148] b c is the fixed solution of the double-difference ionosphere-free combined precise point positioning ambiguity, D is the ambiguity mapping matrix, P b is the weight of the virtual observation value, which is preset to 10 10 ;

[0149] The vector of the virtual observation value is superimposed on the ambiguity floating point solution parameter corresponding to the orbital period of the current satellite, which is expressed as:

[0150]

[0151] in,

[0152]

[0153] The vector of the virtual observation value is superimposed on the ambiguity floating point solution parameter corresponding to the orbital period of the current satellite, and a least squares solution is performed to obtain a precise single point positioning ambiguity fixed solution.

[0154] Step 106: monitor the geological structure changes based on the precise point positioning ambiguity fixed solution to determine whether a geological disaster may occur.

[0155] In summary, the solution strategy for precise single-point positioning using the data of adjacent orbital periods of a single GNSS station as the solution unit can perform single difference between satellites and then double difference between arc segments for the non-differenced ambiguity, eliminating the hardware delay between the receiver and the satellite, and achieving high-precision positioning ambiguity fixed solution relying only on single-station GNSS data. The present invention is suitable for high-precision static positioning applications. In scenarios with a large number of reference stations such as global plate movement monitoring and geological disaster monitoring, it greatly reduces the solution pressure of the computer and can obtain a fixed ambiguity solution, which has significant advantages over traditional algorithms.

[0156] After that, when the precise single-point positioning ambiguity fixed solution is obtained, the millimeter-level or even sub-millimeter-level surface deformation monitoring can be realized, thereby detecting geological disasters such as landslides, ground subsidence, and earthquake activities.

[0157] According to the GNSS-based geological disaster monitoring method provided by the embodiment of the present invention, for the orbital period of any satellite, the carrier phase observation value and pseudo-range observation value collected by a single station in the global navigation satellite system GNSS are obtained; the ionosphere-free combined GNSS observation equation is constructed based on the carrier phase observation value and the pseudo-range observation value; the ionosphere-free combined GNSS observation equation is converted into a matrix form; the ionosphere-free combined GNSS observation equation in the matrix form is solved by least squares to obtain the ambiguity floating point solution parameters corresponding to the orbital period of the current satellite; the precise single-point positioning ambiguity fixed solution is determined according to the ambiguity floating point solution parameters and the least squares model; the geological structure changes are monitored according to the precise single-point positioning ambiguity fixed solution to determine whether geological disasters may occur. It can be achieved by relying on the fixed ambiguity of the GNSS observation data of a single station, without the need to perform the baseline group between stations, greatly alleviating the pressure of solving the large-scale reference station network, not being affected by the quality of the observation data of other stations, not relying too much on external correction information, and the theoretical model is simple, and the same solution effect of the reference station network can be obtained, so as to realize accurate monitoring of geological structure changes.

[0158] It should be noted that, for the sake of simplicity, the method embodiments are described as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0159] Reference Figure 2 , shows a structural block diagram of a GNSS-based geological disaster monitoring device provided in an embodiment of the present invention, which may specifically include the following modules:

[0160] An observation value acquisition module is used to obtain carrier phase observation values ​​and pseudorange observation values ​​collected by a single measurement station in the global navigation satellite system GNSS for the orbit period of any satellite;

[0161] An observation equation determination module, used for constructing an ionosphere-free combined GNSS observation equation based on the carrier phase observation value and the pseudorange observation value;

[0162] A conversion module, used for converting the ionosphere-free combined GNSS observation equation into a matrix form;

[0163] A solution module, used for performing least squares solution on the ionosphere-free combined GNSS observation equation in the matrix form to obtain ambiguity floating point solution parameters corresponding to the orbital period of the current satellite;

[0164] A precise point positioning ambiguity fixed solution determination module, used to determine the precise point positioning ambiguity fixed solution according to the ambiguity floating point solution parameters and the least squares model;

[0165] The monitoring module is used to monitor the changes in geological structure based on the precise single-point positioning ambiguity fixed solution to determine whether a geological disaster may occur.

[0166] Optionally, the pseudo-range observation value collected by a single measuring station in the global navigation satellite system GNSS is linearized and expressed as:

[0167]

[0168] Where 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 in the station, and dt r and dt s,T are the clock errors of the receiver and satellite in the station, M w is the projection function of the tropospheric wet delay, Zw is the zenith tropospheric wet delay, is the ionospheric delay of the L1 band in the direction of satellite incidence, and is related to frequency The coefficient of correlation and and represent the uncalibrated pseudorange hardware delays at the receiver and satellite ends in the station, and denote the uncorrected carrier phase hardware delays at the receiver and satellite ends in the station, is the wavelength of the carrier, is the phase ambiguity with integer characteristics, is the noise in the pseudorange observations and the unmodeled multipath effect.

[0169] Optionally, the carrier phase observation value collected by a single measuring station in the global navigation satellite system GNSS is expressed after being personalized as follows:

[0170]

[0171] Where 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 in the station, and dt r and dt s,T are the clock errors of the receiver and satellite in the station, 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 frequency The coefficient of correlation and and represent the uncalibrated pseudorange hardware delays at the receiver and satellite ends in the station, and denote the uncorrected carrier phase hardware delays at the receiver and satellite ends in the station, is the wavelength of the carrier, is the phase ambiguity with integer characteristics, is the noise in the carrier phase observation and the unmodeled multipath effect.

[0172] Optionally, the ionosphere-free combined GNSS observation equation constructed based on the carrier phase observation value and the pseudorange observation value is expressed as:

[0173]

[0174] in,

[0175] Where i is the satellite number, p is the receiver in the station. P is the original pseudorange observation value, L is the carrier phase observation value. λ1 is the wavelength of the carrier phase observation value of the first frequency of the GNSS satellite, represents the geometric distance from satellite i to receiver p in the measuring station; c is the speed of light in vacuum; dt p 、dt i They represent the clock difference between the receiver and the satellite in the station, in seconds; T is the tropospheric delay caused by the satellite signal passing through the atmosphere; b p , b i are the pseudorange hardware delays of the receiver and satellite in the station; N is the ionospheric-free combination form of the carrier phase integer ambiguity; B p , B i are the carrier phase hardware delays of the receiver in the measuring station and the satellite end respectively; e and ε are the observation noises of the ionospheric-free combination of pseudorange and carrier phase including multipath information.

[0176] Optionally, the conversion module includes:

[0177] In the conversion submodule, the station coordinate parameter is vector x, the ambiguity parameter is b, and the other parameters to be estimated are u. The coefficient matrices corresponding to the parameters at any epoch are A e , B e , C e ; Then the observation equation can be written in matrix form as

[0178] v e =A e x+B e b+C e ul e ,P e

[0179] Among them, v e is the residual vector, l e is the vector of observed values ​​minus calculated values, and the weight matrix of observed values ​​is P e .

[0180] Alternatively, the normal equation for any epoch is:

[0181]

[0182] Alternatively, the normal equation for all epochs is:

[0183]

[0184] Among them, N and w are vectors obtained by superimposing the elements in the normal equation of any epoch.

[0185] Optionally, the solution module includes:

[0186] The solver module is used to perform least squares solution on the normal equations of all epochs to obtain the floating-point solution parameters of the ambiguity corresponding to the orbital period of the current satellite, expressed as:

[0187]

[0188] Where Q is the variance-covariance matrix obtained after the solution. Assuming the number of observations and the number of parameters to be estimated are n and t respectively, the unit weight variance is for:

[0189]

[0190] Optionally, the precise point positioning ambiguity fixed solution determination module includes:

[0191] The decomposition submodule is used to decompose the ambiguity floating point solution parameters into wide lane ambiguity and narrow lane ambiguity with integer characteristics, which are expressed as:

[0192]

[0193] Where g = f1 / f2, is the floating point wide lane ambiguity, is the narrow lane ambiguity of floating point;

[0194] A double-difference wide-lane ambiguity determination submodule is used to eliminate the satellite hardware delay and the hardware delay of the receiver in the measuring station for the wide-lane ambiguity to obtain the double-difference wide-lane ambiguity;

[0195] A double-difference narrow lane ambiguity determination submodule is used to eliminate the satellite hardware delay and the hardware delay of the receiver in the measuring station for the narrow lane ambiguity to obtain the double-difference narrow lane ambiguity;

[0196] The precise point positioning ambiguity fixed solution operator module is used to solve the double-difference wide lane ambiguity and the double-difference narrow lane ambiguity using a least squares model to obtain a precise point positioning ambiguity fixed solution.

[0197] Optionally, the double-difference wide lane ambiguity determination submodule includes:

[0198] A two-day wide lane ambiguity determination unit is used to express the wide lane ambiguity of the floating point in a non-integer form, and the wide lane ambiguity of the floating point for two consecutive days is expressed as:

[0199]

[0200] Among them, subscript 1 represents the first day, subscript 2 represents the second day, is the satellite hardware delay, δη p(wl) is the receiver hardware delay in the station, and

[0201] The double-difference wide-lane ambiguity determination unit is used to obtain the difference of the wide-lane ambiguity of the floating point for two consecutive days to eliminate the satellite hardware delay, and use inter-satellite difference to eliminate the hardware delay of the receiver in the measuring station. The obtained double-difference wide-lane ambiguity is expressed as:

[0202]

[0203] Optionally, the double-difference narrow lane ambiguity determination submodule is configured to include:

[0204] The double-difference narrow lane ambiguity determination unit is used to calculate the difference of the narrow lane ambiguity of the floating point for two consecutive days to eliminate the satellite hardware delay, and use inter-satellite difference to eliminate the hardware delay of the receiver in the measuring station. The obtained double-difference narrow lane ambiguity is expressed as:

[0205]

[0206] Optionally, the precise point positioning ambiguity fixed solution operator module includes:

[0207] A double-difference ionospheric-free combined ambiguity parameter determination unit, configured to determine a double-difference ionospheric-free combined ambiguity parameter based on the double-difference wide lane ambiguity and the double-difference narrow lane ambiguity. It is expressed as:

[0208]

[0209] A virtual observation value representation unit is used to use the double-difference ionospheric-free combined ambiguity parameter as a virtual observation value, and the vector representation of the virtual observation value is:

[0210] v b =Db-b c ,P b

[0211] b c is the fixed solution of the double-difference ionosphere-free combined precise point positioning ambiguity, D is the ambiguity mapping matrix, P b is the weight of the virtual observation value, which is preset to 10 10 ;

[0212] The superposition unit is used to superimpose the vector of the virtual observation value onto the ambiguity floating point solution parameter corresponding to the orbital period of the current satellite, expressed as:

[0213]

[0214] in,

[0215]

[0216] The fixed solution determination unit is used to perform least squares solution on the vector of the virtual observation value superimposed on the ambiguity floating point solution parameter corresponding to the orbital period of the current satellite to obtain a fixed solution for the precise point positioning ambiguity.

[0217] As for the device 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.

[0218] In addition, an embodiment of the present invention further provides an electronic device, such as Figure 3 As shown, it includes a processor 301, a communication interface 302, a memory 303 and a communication bus 304, wherein the processor 301, the communication interface 302, and the memory 303 communicate with each other through the communication bus 304.

[0219] Memory 303, used for storing computer programs;

[0220] The processor 301 is used to execute the program stored in the memory 303 to implement the following steps:

[0221] For any satellite's orbital period, obtain the carrier phase observations and pseudorange observations collected by a single station in the Global Navigation Satellite System (GNSS);

[0222] Constructing an ionospheric-free combined GNSS observation equation based on the carrier phase observation value and the pseudorange observation value;

[0223] Converting the ionospheric-free combined GNSS observation equation into a matrix form;

[0224] Performing a least squares solution on the ionosphere-free combined GNSS observation equation in the matrix form to obtain ambiguity floating-point solution parameters corresponding to the orbital period of the current satellite;

[0225] Determining a precise point positioning ambiguity fixed solution according to the ambiguity floating point solution parameters and a least squares model;

[0226] Based on the precise point positioning ambiguity fixed solution, the geological structure changes are monitored to determine whether a geological disaster is likely to occur.

[0227] Optionally, the pseudo-range observation value collected by a single measuring station in the global navigation satellite system GNSS is linearized and expressed as:

[0228]

[0229] Where 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 in the station, and dt r and dt s,T are the clock errors of the receiver and satellite in the station, 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 frequency The coefficient of correlation and and represent the uncalibrated pseudorange hardware delays at the receiver and satellite ends in the station, and denote the uncorrected carrier phase hardware delays at the receiver and satellite ends in the station, is the wavelength of the carrier, is the phase ambiguity with integer characteristics, is the noise in the pseudorange observations and the unmodeled multipath effect.

[0230] Optionally, the carrier phase observation value collected by a single measuring station in the global navigation satellite system GNSS is expressed after being personalized as follows:

[0231]

[0232] Where 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 in the station, and dt r and dt s,T are the clock errors of the receiver and satellite in the station, 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 frequency The coefficient of correlation and and represent the uncalibrated pseudorange hardware delays at the receiver and satellite ends in the station, and denote the uncorrected carrier phase hardware delays at the receiver and satellite ends in the station, is the wavelength of the carrier, is the phase ambiguity with integer characteristics, is the noise in the carrier phase observation and the unmodeled multipath effect.

[0233] Optionally, the ionosphere-free combined GNSS observation equation constructed based on the carrier phase observation value and the pseudorange observation value is expressed as:

[0234]

[0235] in,

[0236] Where i is the satellite number, p is the receiver in the station. P is the original pseudorange observation value, L is the carrier phase observation value. λ1 is the wavelength of the carrier phase observation value of the first frequency of the GNSS satellite, represents the geometric distance from satellite i to receiver p in the measuring station; c is the speed of light in vacuum; dt p 、dt i They represent the clock difference between the receiver and the satellite in the station, in seconds; T is the tropospheric delay caused by the satellite signal passing through the atmosphere; b p , b i are the pseudorange hardware delays of the receiver and satellite in the station; N is the ionospheric-free combination form of the carrier phase integer ambiguity; B p , B i are the carrier phase hardware delays of the receiver in the measuring station and the satellite end respectively; e and ε are the observation noises of the ionospheric-free combination of pseudorange and carrier phase including multipath information.

[0237] Optionally, the step of converting the ionospheric-free combined GNSS observation equation into a matrix form comprises:

[0238] Assume that the station coordinate parameter is vector x, the ambiguity parameter is b, and the other parameters to be estimated are u. The coefficient matrices corresponding to the parameters at any epoch are A e , B e , C e ; Then the observation equation can be written in matrix form as

[0239] v e =A e x+B e b+C e ul e ,P e

[0240] Among them, v e is the residual vector, l e is the vector of observed values ​​minus calculated values, and the weight matrix of observed values ​​is Pe .

[0241] Alternatively, the normal equation for any epoch is:

[0242]

[0243] Alternatively, the normal equation for all epochs is:

[0244]

[0245] Among them, N and w are vectors obtained by superimposing the elements in the normal equation of any epoch.

[0246] Optionally, the step of performing least squares solution on the ionosphere-free combined GNSS observation equation in the matrix form to obtain ambiguity floating-point solution parameters corresponding to the orbital period of the current satellite includes:

[0247] The least squares solution of the normal equations of all epochs is performed to obtain the ambiguity floating point solution parameters corresponding to the orbital period of the current satellite, which is expressed as:

[0248]

[0249] Where Q is the variance-covariance matrix obtained after the solution. Assuming the number of observations and the number of parameters to be estimated are n and t respectively, the unit weight variance is for:

[0250]

[0251] Optionally, the step of determining a precise point positioning ambiguity fixed solution according to the ambiguity floating point solution parameters and a least squares model comprises:

[0252] The ambiguity floating point solution parameters are decomposed into wide lane ambiguity and narrow lane ambiguity with integer characteristics, which are expressed as:

[0253]

[0254] Where g = f1f2, is the floating point wide lane ambiguity, is the narrow lane ambiguity of floating point;

[0255] Eliminating the satellite hardware delay and the hardware delay of the receiver in the measuring station for the wide lane ambiguity to obtain a double difference wide lane ambiguity;

[0256] Eliminating the satellite hardware delay and the hardware delay of the receiver in the measuring station for the narrow lane ambiguity to obtain a double difference narrow lane ambiguity;

[0257] The double-difference wide lane ambiguity and the double-difference narrow lane ambiguity are solved using a least squares model to obtain a precise single point positioning ambiguity fixed solution.

[0258] Optionally, the step of eliminating satellite hardware delay and hardware delay of a receiver in a measuring station for the wide lane ambiguity to obtain a double difference wide lane ambiguity comprises:

[0259] The wide lane ambiguity of the floating point is expressed as a non-integer form, and the wide lane ambiguity of the floating point for two consecutive days is expressed as:

[0260]

[0261] Among them, subscript 1 represents the first day, subscript 2 represents the second day, is the satellite hardware delay, δη p(wl) is the receiver hardware delay in the station, and

[0262] The wide lane ambiguity of the floating point for two consecutive days is differentiated to eliminate the satellite hardware delay, and the hardware delay of the receiver in the station is eliminated by using inter-satellite difference. The obtained double difference wide lane ambiguity is expressed as:

[0263]

[0264] Optionally, the step of eliminating satellite hardware delay and hardware delay of a receiver in a measuring station for the narrow lane ambiguity to obtain a double difference narrow lane ambiguity comprises:

[0265] The narrow lane ambiguity of the floating point for two consecutive days is differentiated to eliminate the satellite hardware delay, and the hardware delay of the receiver in the station is eliminated by using inter-satellite difference. The obtained double-difference narrow lane ambiguity is expressed as:

[0266]

[0267] Optionally, the step of solving the double-difference wide lane ambiguity and the double-difference narrow lane ambiguity using a least squares model to obtain a fixed solution for the precise point positioning ambiguity includes:

[0268] Determine the double-difference ionospheric-free combined ambiguity parameter based on the double-difference wide-lane ambiguity and the double-difference narrow-lane ambiguity It is expressed as:

[0269]

[0270] The double-difference ionospheric-free combined ambiguity parameters are used as virtual observation values, and the vector of the virtual observation values ​​is expressed as:

[0271] v b =Db-bc ,P b

[0272] b c is the fixed solution of the double-difference ionosphere-free combined precise point positioning ambiguity, D is the ambiguity mapping matrix, P b is the weight of the virtual observation value, which is preset to 10 10 ;

[0273] The vector of the virtual observation value is superimposed on the ambiguity floating point solution parameter corresponding to the orbital period of the current satellite, which is expressed as:

[0274]

[0275] in,

[0276]

[0277] The vector of the virtual observation value is superimposed on the ambiguity floating point solution parameter corresponding to the orbital period of the current satellite, and a least squares solution is performed to obtain a precise single point positioning ambiguity fixed solution.

[0278] The communication bus mentioned in the above terminal can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. 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.

[0279] The communication interface is used for communication between the above terminal and other devices.

[0280] 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.

[0281] 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 gates or transistor logic devices, discrete hardware components.

[0282] like Figure 4 As shown, in another embodiment provided by the present invention, a computer-readable storage medium 401 is also provided, in which instructions are stored. When the computer-readable storage medium 401 is run on a computer, the computer executes the GNSS-based geological disaster monitoring method described in the above embodiment.

[0283] In another embodiment provided by the present invention, a computer program product including instructions is also provided, which, when executed on a computer, enables the computer to execute the GNSS-based geological disaster monitoring method described in the above embodiment.

[0284] 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.

[0285] 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 "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0286] 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.

[0287] 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 GNSS-based geological disaster monitoring method, characterized in that: include: For any satellite's orbital period, obtain the carrier phase observations and pseudorange observations collected by a single station in the Global Navigation Satellite System (GNSS); Constructing an ionospheric-free combined GNSS observation equation based on the carrier phase observation value and the pseudorange observation value; Converting the ionospheric-free combined GNSS observation equation into a matrix form; Performing a least squares solution on the ionosphere-free combined GNSS observation equation in the matrix form to obtain ambiguity floating-point solution parameters corresponding to the orbital period of the current satellite; Determining a precise point positioning ambiguity fixed solution according to the ambiguity floating point solution parameters and a least squares model; Based on the precise point positioning ambiguity fixed solution, the geological structure changes are monitored to determine whether a geological disaster is likely to occur.

2. The method according to claim 1, characterized in that The pseudo-range observation value collected by a single measuring station in the global navigation satellite system GNSS is linearized and expressed as: Where 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 in the station, and dt r and dt s,T are the clock errors of the receiver and satellite in the station, 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 represent the uncalibrated pseudorange hardware delays at the receiver and satellite ends in the station, and denote the uncorrected carrier phase hardware delays at the receiver and satellite ends in the station, is the wavelength of the carrier, is the phase ambiguity with integer characteristics, is the noise in the pseudorange observations and the unmodeled multipath effect.

3. The method according to claim 1, characterized in that The carrier phase observation value collected by a single measuring station in the global navigation satellite system GNSS is expressed as follows after being personalized: Where 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 in the station, and dt r and dt s,T are the clock errors of the receiver and satellite in the station, 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 represent the uncalibrated pseudorange hardware delays at the receiver and satellite ends in the station, and denote the uncorrected carrier phase hardware delays at the receiver and satellite ends in the station, is the wavelength of the carrier, is the phase ambiguity with integer characteristics, is the noise in the carrier phase observation and the unmodeled multipath effect.

4. The method according to claim 1, characterized in that: The ionospheric-free combined GNSS observation equation constructed based on the carrier phase observation value and the pseudorange observation value is expressed as: in, Where i is the satellite number, p is the receiver in the station. P is the original pseudorange observation value, L is the carrier phase observation value. λ1 is the wavelength of the carrier phase observation value of the first frequency of the GNSS satellite, represents the geometric distance from satellite i to receiver p in the measuring station; c is the speed of light in vacuum; dt p 、dt i They represent the clock difference between the receiver and the satellite in the station, in seconds; T is the tropospheric delay caused by the satellite signal passing through the atmosphere; b p , b i are the pseudorange hardware delays of the receiver and satellite in the station; N is the ionospheric-free combination form of the carrier phase integer ambiguity; B p , B i are the carrier phase hardware delays of the receiver in the measuring station and the satellite end respectively; e and ε are the observation noises of the ionospheric-free combination of pseudorange and carrier phase including multipath information.

5. The method according to claim 1, characterized in that The step of converting the ionospheric-free combined GNSS observation equation into a matrix form comprises: Assume that the station coordinate parameter is vector x, the ambiguity parameter is b, and the other parameters to be estimated are u. The coefficient matrices corresponding to the parameters at any epoch are A e , B e , C e ; Then the observation equation can be written in matrix form as v e =A e x+B e b+C e u-l e ,P e Among them, v e is the residual vector, l e is the vector of observed values ​​minus calculated values, and the weight matrix of observed values ​​is P e .

6. The method according to claim 5, characterized in that The normal equation for any epoch is:

7. The method according to claim 6, characterized in that The normal equation for all epochs is: Wherein, N is the matrix obtained by superimposing the elements in the normal equation of any epoch, and w is the vector obtained by superimposing the elements in the normal equation of any epoch.

8. The method according to claim 7, characterized in that The step of performing least squares solution on the ionosphere-free combined GNSS observation equation in the matrix form to obtain the ambiguity floating point solution parameters corresponding to the orbital period of the current satellite includes: The least squares solution of the normal equations of all epochs is performed to obtain the ambiguity floating point solution parameters corresponding to the orbital period of the current satellite, which is expressed as: Where Q is the variance-covariance matrix obtained after the solution. Assuming the number of observations and the number of parameters to be estimated are n and t respectively, the unit weight variance is for:

9. The method according to claim 8, characterized in that The step of determining the precise point positioning ambiguity fixed solution according to the ambiguity floating point solution parameters and the least squares model comprises: The ambiguity floating point solution parameters are decomposed into wide lane ambiguity and narrow lane ambiguity with integer characteristics, which are expressed as: Where g = f1 / f2, is the floating point wide lane ambiguity, is the narrow lane ambiguity of floating point; Eliminating the satellite hardware delay and the hardware delay of the receiver in the measuring station for the wide lane ambiguity to obtain a double difference wide lane ambiguity; Eliminating the satellite hardware delay and the hardware delay of the receiver in the measuring station for the narrow lane ambiguity to obtain a double difference narrow lane ambiguity; The double-difference wide lane ambiguity and the double-difference narrow lane ambiguity are solved using a least squares model to obtain a precise single point positioning ambiguity fixed solution.

10. The method according to claim 9, characterized in that The step of eliminating the satellite hardware delay and the hardware delay of the receiver in the measuring station for the wide lane ambiguity to obtain the double difference wide lane ambiguity comprises: The wide lane ambiguity of the floating point is expressed as a non-integer form, and the wide lane ambiguity of the floating point for two consecutive days is expressed as: Among them, subscript 1 represents the first day, subscript 2 represents the second day, is the satellite hardware delay, δη p(wl) is the receiver hardware delay in the station, and The wide lane ambiguity of the floating point for two consecutive days is differentiated to eliminate the satellite hardware delay, and the hardware delay of the receiver in the station is eliminated by using inter-satellite difference. The obtained double difference wide lane ambiguity is expressed as:

11. The method according to claim 9, characterized in that The step of eliminating the satellite hardware delay and the hardware delay of the receiver in the measuring station for the narrow lane ambiguity to obtain the double difference narrow lane ambiguity comprises: The narrow lane ambiguity of the floating point for two consecutive days is differentiated to eliminate the satellite hardware delay, and the hardware delay of the receiver in the station is eliminated by using inter-satellite difference. The obtained double-difference narrow lane ambiguity is expressed as:

12. The method according to claim 9, characterized in that The step of solving the double-difference wide lane ambiguity and the double-difference narrow lane ambiguity using a least squares model to obtain a fixed solution for precise point positioning ambiguity includes: Determine the double-difference ionospheric-free combined ambiguity parameter based on the double-difference wide-lane ambiguity and the double-difference narrow-lane ambiguity It is expressed as: The double-difference ionospheric-free combined ambiguity parameters are used as virtual observation values, and the vector of the virtual observation values ​​is expressed as: v b =Db-b c ,P b b c is the fixed solution of the double-difference ionosphere-free combined precise point positioning ambiguity, D is the ambiguity mapping matrix, P b is the weight of the virtual observation value, which is preset to 10 10 ; The vector of the virtual observation value is superimposed on the ambiguity floating point solution parameter corresponding to the orbital period of the current satellite, which is expressed as: in, The vector of the virtual observation value is superimposed on the ambiguity floating point solution parameter corresponding to the orbital period of the current satellite, and a least squares solution is performed to obtain a precise single point positioning ambiguity fixed solution.

13. A GNSS-based geological disaster monitoring device, characterized in that: include: An observation value acquisition module is used to obtain carrier phase observation values ​​and pseudorange observation values ​​collected by a single measurement station in the global navigation satellite system GNSS for the orbit period of any satellite; An observation equation determination module, used for constructing an ionosphere-free combined GNSS observation equation based on the carrier phase observation value and the pseudorange observation value; A conversion module, used for converting the ionosphere-free combined GNSS observation equation into a matrix form; A solution module, used for performing least squares solution on the ionosphere-free combined GNSS observation equation in the matrix form to obtain ambiguity floating point solution parameters corresponding to the orbital period of the current satellite; A precise point positioning ambiguity fixed solution determination module, used to determine the precise point positioning ambiguity fixed solution according to the ambiguity floating point solution parameters and the least squares model; The monitoring module is used to monitor the changes in geological structure based on the precise single-point positioning ambiguity fixed solution to determine whether a geological disaster may occur.

14. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; The memory is used to store computer programs; The processor is used to implement the method according to any one of claims 1 to 12 when executing the program stored in the memory.

15. One or more computer-readable media having instructions stored thereon, which when executed by one or more processors cause the processors to perform the method of any one of claims 1-12.

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