Equipment positioning method and device based on water vapor parameters, equipment and medium

Abstract

The embodiment of the invention discloses an equipment positioning method and device based on water vapor parameters, equipment and a medium. The method comprises the steps that ground meteorological data and satellite positioning data are acquired; determining an observation distance between a satellite and a receiver according to a precise point positioning algorithm and the satellite positioning data; on the basis of a preset atmosphere model, the observation distance and the ground meteorological data, estimating propagation delay of a signal during atmospheric propagation; estimating water vapor parameters in the atmosphere according to the propagation delay, the observation distance and the satellite positioning data; and transmitting the water vapor parameter to a data receiving center based on a preset Beidou short message communication mechanism, so that the data receiving center positions target equipment according to the water vapor parameter. According to the scheme, the equipment positioning precision can be improved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method, apparatus, device and medium for positioning a device based on water vapor parameters. Background Art

[0002] Users of the BeiDou-3 satellite navigation system can obtain real-time decimeter-centimeter level location information by using high-precision positioning terminals and the Continuously Operating Reference Station (CORS) service. However, there are currently large areas in some regions that are not covered by CORS and communication network services, resulting in the inability to obtain atmospheric parameter information in these areas, and thus the inability to provide high-precision positioning services. In addition, establishing 4G (fourth-generation mobile information system) network communication facilities and BeiDou reference stations in these areas is time-consuming, labor-intensive, and costly, and also poses security risks.

[0003] Compared with foreign systems such as GPS (Global Positioning System) and GLONASS, the BeiDou-3 satellite navigation system has unique satellite-based precise point positioning (PPPB2b) service and BeiDou-3 short message communication service. Chinese users can receive high-precision orbit and clock correction information via satellite without the help of 4G network.

[0004] The core of the determination of key atmospheric parameters based on Beidou short messages lies in tropospheric modeling. There are many methods for tropospheric modeling, and the most commonly used is the Saastamoinen model (a mathematical model). This model is based on the continuity assumption of the atmospheric medium and uses parameters such as atmospheric pressure, temperature and water vapor content to establish the relationship between atmospheric delay and altitude, thereby effectively simulating the impact of tropospheric delay. However, this method has low accuracy in polar regions and high-latitude regions due to the large difference between atmospheric conditions and standard atmospheric conditions. Summary of the invention

[0005] The embodiments of the present application provide a device positioning system, method, electronic device and storage medium based on water vapor parameters, which can improve the positioning accuracy of the device.

[0006] In a first aspect, an embodiment of the present application provides a device positioning method based on water vapor parameters, including: Obtain ground-based meteorological data and satellite positioning data; Determine the observation distance between the satellite and the receiver according to the precise point positioning algorithm and the satellite positioning data; Based on a preset atmospheric model, the observation distance and the ground meteorological data, estimating a propagation delay of a signal during atmospheric propagation; estimating water vapor parameters in the atmosphere according to the propagation delay, the observation distance and the satellite positioning data; The water vapor parameters are transmitted to a data receiving center based on a preset Beidou short message communication mechanism, so that the data receiving center can locate the target device according to the water vapor parameters.

[0007] Optionally, in some embodiments of the present application, estimating the propagation delay of the signal during atmospheric propagation based on the preset atmospheric model, the observation distance and the ground meteorological data includes: Demodulating the satellite positioning data to obtain a phase signal corresponding to the satellite positioning data; The propagation delay of the signal when propagating in the atmosphere is estimated according to the phase signals of multiple frequencies, a preset atmospheric model and the ground meteorological data.

[0008] Optionally, in some embodiments of the present application, estimating the propagation delay of the signal during atmospheric propagation according to the phase signals of multiple frequencies, the preset atmospheric model and the ground meteorological data includes: Inputting the ground meteorological data into a preset atmospheric model to estimate the delay of the signal in the troposphere; Estimate the delay of the signal in the ionosphere based on phase signals of multiple frequencies; Estimate the propagation delay of the signal as it propagates through the atmosphere based on the signal delay in the troposphere and the signal delay in the ionosphere.

[0009] Optionally, in some embodiments of the present application, estimating water vapor parameters in the atmosphere according to the propagation delay, the observation distance, and the satellite positioning data includes: determining a geometric distance between the satellite and the receiver; Water vapor parameters in the atmosphere are estimated according to the geometric distance, the propagation delay, the observation distance and the satellite positioning data.

[0010] Optionally, in some embodiments of the present application, estimating water vapor parameters in the atmosphere according to the geometric distance, the propagation delay, the observation distance, and the satellite positioning data includes: Calculating a distance residual between the observed distance and the geometric distance; A water vapor parameter in the atmosphere is estimated based on the range residual, the propagation delay and the satellite positioning data.

[0011] Optionally, in some embodiments of the present application, estimating water vapor parameters in the atmosphere based on the range residual, the propagation delay, and the satellite positioning data includes: Determining a total tropospheric delay based on the satellite positioning data; Calculating static delay based on the ground meteorological data, distance residual and a preset formula; Calculate the difference between the total tropospheric delay and the static delay to obtain the wet delay; Water vapor parameters in the atmosphere are estimated according to the ground meteorological data, the propagation delay and the wet delay.

[0012] Optionally, in some embodiments of the present application, transmitting the water vapor parameters to a data receiving center based on a preset Beidou short message communication mechanism so that the data receiving center locates the target device according to the water vapor parameters includes: Compressing the water vapor parameter based on a Huffman coding method, and encrypting the compressed data to obtain encrypted data; The encrypted data is sent to the satellite according to a preset short message service, and the satellite forwards the encrypted data to a data receiving center so that the data receiving center can locate the target device according to the encrypted data.

[0013] In a second aspect, an embodiment of the present application provides a device positioning apparatus based on water vapor parameters, including: An acquisition module is used to obtain ground meteorological data and satellite positioning data; A determination module, used to determine the observation distance between the satellite and the receiver according to the precise point positioning algorithm and the satellite positioning data; A first estimation module, used for estimating the propagation delay of the signal when propagating in the atmosphere based on a preset atmospheric model, the observation distance and the ground meteorological data; A second estimation module, used for estimating water vapor parameters in the atmosphere according to the propagation delay, the observation distance and the satellite positioning data; The positioning module is used to transmit the water vapor parameters to a data receiving center based on a preset Beidou short message communication mechanism, so that the data receiving center can locate the target device according to the water vapor parameters.

[0014] Correspondingly, the present application also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the steps of any of the above methods when executing the program.

[0015] The present application also provides a storage medium, wherein the storage medium stores a computer program, and the computer program implements any of the above methods when the computer program is executed by a processor.

[0016] The present application provides a device positioning method, apparatus, equipment and medium based on water vapor parameters. After acquiring ground meteorological data and satellite positioning data, the observation distance between the satellite and the receiver is determined according to a precise single-point positioning algorithm and the satellite positioning data. Then, based on a preset atmospheric model, the observation distance and the ground meteorological data, the propagation delay of the signal during atmospheric propagation is estimated. Then, based on the propagation delay, the observation distance and the satellite positioning data, the water vapor parameters in the atmosphere are estimated. Finally, based on a preset Beidou short message communication mechanism, the water vapor parameters are transmitted to a data receiving center so that the data receiving center can locate the target device according to the water vapor parameters. In the device positioning solution based on water vapor parameters provided in the present application, it does not rely on the signal of the ground network. It estimates the propagation delay of the signal in the atmosphere based on the preset atmospheric model, observation distance and ground meteorological data, and then estimates the water vapor parameters in the atmosphere based on the propagation delay, observation distance and satellite positioning data. Finally, the water vapor parameters are transmitted back to the monitoring center, so as to grasp the water vapor information of the operating area in real time, ensure high-precision positioning under no network conditions, and realize high-precision positioning of the equipment in the absence of a network, that is, improve the accuracy of equipment positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 is a flow chart of a device positioning method based on water vapor parameters provided in an embodiment of the present application; Figure 2 This is a process of atmospheric monitoring and data transmission based on the Beidou satellite navigation system provided in an embodiment of the present application; Figure 3 A schematic diagram of the structure of a device positioning device based on water vapor parameters provided in an embodiment of the present application; Figure 4 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0019] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Instead, they are merely examples of systems and methods consistent with the examples detailed in the attached claims, or with some aspects of the present application.

[0020] It should be noted that, in this article, the terms "include", "comprises" or any other variants thereof are intended to cover descriptions such as 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, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element. In addition, components, features, and elements with the same name in different embodiments of the present application may have the same meaning or different meanings, and their specific meanings need to be determined by their explanation in the specific embodiment or further combined with the context of the specific embodiment.

[0021] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0022] In the subsequent description, the suffixes such as "module", "component" or "unit" used to represent elements are only used to facilitate the description of the present application, and have no specific meanings. Therefore, "module", "component" or "unit" can be used in a mixed manner.

[0023] Embodiments of the present application provide a device positioning method, apparatus, electronic device, and storage medium based on water vapor parameters.

[0024] The device positioning device based on water vapor parameters can be deployed in a drone. A drone (Unmanned Aerial Vehicle, UAV), also known as a remote-controlled aircraft or an unmanned aircraft system (Unmanned Aircraft System, UAS), is an aircraft that does not require a pilot to operate in the cabin. The drone can communicate with the server via wired or wireless means. The server can include an independently operated server or a distributed server, or a server cluster composed of multiple servers. The terminal can include a mobile phone, a tablet computer or a personal computer (Personal Computer, PC).

[0025] It should be noted that the order of description of the following embodiments is not intended to limit the priority order of the embodiments.

[0026] The present application provides a device positioning method based on water vapor parameters, including: acquiring ground meteorological data and satellite positioning data; determining the observation distance between the satellite and the receiver based on a precise single-point positioning algorithm and the satellite positioning data; estimating the propagation delay of a signal during atmospheric propagation based on a preset atmospheric model, the observation distance and ground meteorological data; estimating water vapor parameters in the atmosphere based on the propagation delay, the observation distance and the satellite positioning data; and transmitting the water vapor parameters to a data receiving center based on a preset Beidou short message communication mechanism, so that the data receiving center can locate the target device based on the water vapor parameters.

[0027] See also Figure 1 , Figure 1 : is a flow chart of a device positioning method based on water vapor parameters provided by the present application, and the device positioning method based on water vapor parameters specifically includes the following process: 101. Obtain ground meteorological data and satellite positioning data.

[0028] Ground meteorological data can include temperature, humidity, and air pressure. Temperature: The temperature of the atmosphere affects the density and refractive index of the atmosphere, which in turn affects the propagation speed and path of the Global Navigation Satellite System (GNSS) signal. Humidity: Humidity is a key factor affecting the water vapor content in the atmosphere, and the water vapor content in the atmosphere is one of the main sources of GNSS signal propagation delay. Air pressure: The air pressure of the atmosphere also affects the density and refractive index of the atmosphere, which has a direct impact on the propagation of GNSS signals.

[0029] Satellite positioning data is obtained by the GNSS system and is used to determine the precise location of the receiver on the earth. This data usually includes the following types of information: Pseudorange observation data: The distance calculated by the receiver based on the received satellite signal is called pseudorange. Since the receiver clock cannot be as accurate as the satellite clock, this distance is "pseudo", that is, it contains clock errors.

[0030] Phase observation data: Compared with pseudorange, phase observation can provide higher accuracy because it measures the phase change of the signal. Phase observation is more sensitive to atmospheric delay and can be used to make more refined atmospheric delay estimates.

[0031] Satellite ephemeris: Data describing the precise position and motion of a satellite in orbit. Ephemeris data allows a receiver to calculate the position of a satellite.

[0032] Satellite clock error: The time difference between the atomic clock on the satellite and the receiver clock. This time difference needs to be calculated and corrected to ensure the accuracy of positioning.

[0033] Atmospheric delay: GNSS signals are delayed when passing through the atmosphere, mainly including tropospheric delay and ionospheric delay. Atmospheric delay needs to be estimated and corrected to improve positioning accuracy.

[0034] Multipath effect: When GNSS signals are reflected or diffracted to reach the receiver, multipath effect occurs, which affects the accurate reception of the signal. Measures need to be taken to reduce or eliminate this effect.

[0035] For example, weather monitoring stations are deployed at key geographical locations to collect data such as temperature, humidity, and air pressure. Various sensors and instruments, such as thermometers, hygrometers, and barometers, can be used to collect ground weather data in real time. The collected data is transmitted to a data processing center or a positioning system through a wired or wireless communication network. The data from different monitoring stations are integrated to obtain regional weather information. In addition, GNSS receivers are deployed at locations where positioning is required, and then signals from GNSS satellites are received by the receivers. In this way, ground weather data and satellite positioning data are obtained.

[0036] 102. Determine the observation distance between the satellite and the receiver based on the precise point positioning algorithm and satellite positioning data.

[0037] Precise Point Positioning (PPP) is a technology that uses GNSS satellite signals to locate the receiver with high precision. The PPP algorithm takes into account multiple error sources and uses various correction data to improve positioning accuracy. The observed distance refers to the straight-line distance between the satellite and the receiver in GNSS positioning.

[0038] For example, specifically, the receiver captures signals from GNSS satellites, including pseudorange and phase observation data. Then, the satellite's position in space is determined using satellite ephemeris data. Next, the receiver and satellite clock differences are corrected. Then, the delays incurred when the signal propagates in the atmosphere are corrected, including tropospheric and ionospheric delays. Finally, the PPP algorithm is applied to process the observation data, combined with all corrections, and the estimated position of the receiver and the satellite position, to calculate the propagation time of the satellite signal from the satellite to the receiver. Finally, the propagation time is multiplied by the speed of light to obtain the observed distance between the satellite and the receiver.

[0039] 103. Based on the preset atmospheric model, observation distance and ground meteorological data, the propagation delay of the signal during atmospheric propagation is estimated.

[0040] Atmospheric models are mathematical models used to describe and estimate the impact of the Earth's atmosphere on GNSS signal propagation. These models take into account the physical properties of the atmosphere, such as temperature, humidity, air pressure, etc., and how they affect the propagation speed and path of electromagnetic waves. Atmospheric models can specifically include the following: Standard atmosphere model: provides a standard profile of how atmospheric parameters (such as temperature, pressure, and density) vary with altitude.

[0041] Saastamoinen model: A classic tropospheric delay model used to estimate the propagation delay of signals in the troposphere. It is based on parameters such as atmospheric pressure, temperature, and water vapor content.

[0042] GPT2 (Global Pressure and Temperature) model: used to calculate atmospheric refractivity and delay on a global scale, taking into account atmospheric pressure, temperature and water vapor pressure.

[0043] Hopfield model: Another tropospheric delay model, similar to the Saastamoinen model, but using different coefficients.

[0044] For example, specifically, an atmospheric model, such as the Saastamoinen model, can be determined to describe the effect of the atmosphere on signal propagation. The atmospheric model is used in combination with ground meteorological data to estimate the troposphere delay and ionosphere delay. Using ground meteorological data and the atmospheric model, the propagation delay of the signal in the troposphere is calculated. This includes calculating the water vapor content in the atmosphere (Precipitable Water Vapor, PWV) and the dry delay (ZenithHydrostatic Delay, ZHD).

[0045] Using dual-frequency signals, the ionospheric delay is estimated through the ionospheric mapping function (IMF) and dual-frequency observation data. The impact of multipath effects on signal propagation delay is evaluated and corrections are attempted. All atmospheric delay corrections are combined to obtain the total propagation delay of the signal in the atmosphere. The observed distance is combined with the atmospheric delay correction to calculate the propagation delay of the signal in the atmosphere.

[0046] Optionally, in some embodiments of the present application, the step of “estimating the propagation delay of the signal during atmospheric propagation based on a preset atmospheric model, an observation distance, and ground meteorological data” may specifically include: Demodulate the satellite positioning data to obtain a phase signal corresponding to the satellite positioning data; The propagation delay of the signal when propagating in the atmosphere is estimated according to the phase signals of multiple frequencies, a preset atmospheric model and the ground meteorological data.

[0047] For example, specifically, after the receiver receives a signal from a GNSS satellite, the signal may include phase and pseudorange signals of multiple frequencies. Optionally, in some embodiments of the present application, the above-mentioned signal is processed by the RF chip of the receiver, including filtering, amplification and analog-to-digital conversion. The received digital intermediate frequency signal is further processed by the baseband chip, including digital demodulation and data parsing. Then, the phase observation value at each frequency is extracted using the multiple frequency signals received by the receiver. It should be noted that the phase observation value has high resolution and is very sensitive to atmospheric delay. A preset atmospheric model, such as the Saastamoinen model, is applied to estimate the tropospheric delay in combination with ground meteorological data (temperature, humidity, air pressure, etc.). Specifically, the atmospheric delay is accurately estimated using GNSS observation data and an atmospheric refraction model in combination with ground meteorological data, thereby simulating the influence of tropospheric delay. At the same time, a dual-frequency signal is used to estimate the ionospheric delay through a dual-frequency algorithm of ionospheric delay, thereby reducing the influence of ionospheric delay. By constructing a double-difference observation value, the multipath effect is effectively eliminated and the accuracy of atmospheric delay estimation is improved. Next, the propagation time of the signal in the atmosphere is estimated using the phase observations and the atmospheric delay model. Finally, the atmospheric delay correction is applied to the propagation time of the signal to calculate the propagation delay of the signal in the atmosphere.

[0048] Optionally, in some embodiments of the present application, the step of “estimating the propagation delay of the signal during atmospheric propagation according to the phase signals of multiple frequencies, the preset atmospheric model and the ground meteorological data” may specifically include: The ground-based meteorological data is input into a preset atmospheric model to estimate the signal delay in the troposphere; Estimate the delay of the signal in the ionosphere based on phase signals of multiple frequencies; Estimate the propagation delay of the signal as it propagates through the atmosphere based on the signal delay in the troposphere and the signal delay in the ionosphere.

[0049] The receiver terminal collects ground meteorological data, such as temperature, humidity and air pressure, which are essential for modeling tropospheric delay. The collected ground meteorological data is input into atmospheric models, such as the Saastamoinen model, to estimate the delay of the signal in the troposphere. Specifically, the large model establishes the relationship between atmospheric delay and altitude based on parameters such as atmospheric pressure, temperature and water vapor content. The receiver uses PPP technology for precise positioning calculations, and adopts an atmospheric delay estimation method based on the phase of GNSS signals, using phase observation data and atmospheric refraction models to make a more accurate estimate of atmospheric delay. The receiver uses phase signals of multiple frequencies to estimate the delay of the signal in the ionosphere through a dual-frequency algorithm for ionospheric delay.

[0050] By combining the delay estimates of the troposphere and ionosphere, the receiver can estimate the total propagation delay of the signal in the atmosphere. This includes the delay caused by the change in atmospheric refractive index in the troposphere and the delay caused by the change in free electron density in the ionosphere. In addition, data processing and filtering techniques, such as constructing double-difference observations, can effectively reduce the impact of multipath effects and improve the accuracy of atmospheric delay estimation.

[0051] Specifically, the received satellite signals and auxiliary information such as precise ephemeris and clock errors are used to perform PPP (Precise Point Positioning, a positioning technology of the global navigation satellite system) positioning calculation. This includes solving the receiver's position, clock error, atmospheric delay and other parameters. From the PPP positioning calculation process, an accurate estimate of the receiver's position, as well as information such as the distance between the satellite and the receiver and the observation residual, are obtained. These results will serve as the basic data for estimating the water vapor content.

[0052] An atmospheric delay estimation method based on the GNSS signal phase is used to model the tropospheric delay. The phase observation data is combined with the atmospheric delay model, and the atmospheric delay is estimated through the optimization algorithm of the differential carrier phase.

[0053] Due to the uneven distribution of the atmosphere in the troposphere, the atmospheric refractive index changes with the position. Therefore, when the GNSS signal propagates in the troposphere, the speed is not a constant value, and the path is also an irregular curve. If only the influence of the troposphere is considered, the propagation time of the GNSS signal in the troposphere can be expressed as: (1) in, The calculation function representing the propagation time of the signal in the troposphere, represents the actual propagation time of the signal in the troposphere, S represents the propagation path of the signal in the troposphere, v represents the propagation speed of the GNSS signal, and n represents the atmospheric refractive index.

[0054] However, assuming that there is no atmospheric refraction effect, the signal propagation time in the troposphere should be expressed as: (2) in, It represents the propagation time of the signal in the troposphere without the influence of atmospheric refraction. represents the geometric distance from the satellite to the receiver, and c represents the speed of light.

[0055] Therefore, the delay time ∆t of the signal due to the atmospheric refractive index in the troposphere can be expressed as: (3) When GNSS observes the distance between the receiver and the satellite, the direct observation is the propagation time from the signal being transmitted from the satellite to the signal being received by the receiver. The distance is then obtained by multiplying the time by the speed of light in a vacuum.

[0056] Therefore, the equivalent distance STD of the signal delay time caused by the atmospheric refraction phenomenon in the troposphere can be expressed as: (4) in, represents the delay of the GNSS signal caused by the slower propagation speed due to atmospheric refraction, (S−R) represents the longer propagation path due to the bending of the path, S represents the propagation path of the signal in the troposphere, and R represents the geometric distance from the satellite to the receiver.

[0057] In terms of accuracy improvement, phase observation of GNSS signals has higher accuracy because phase observation can provide more precise measurements than pseudorange observation (code observation).

[0058] The phase observation value Φ (unit: week) can be expressed as: (5) Where Φ is the phase observation value, is the geometric distance of signal propagation, c is the speed of light, dT and dTs are the clock differences of the receiver and the satellite respectively, λ is the signal wavelength, N is the phase ambiguity (integer number of cycles), ΔΦ ion is the ionospheric delay, ΔΦ trop is the tropospheric delay, ϵ Φ are the observation noise and multipath error.

[0059] In terms of eliminating multipath effects, the multipath effects in phase observation can be eliminated or reduced through a variety of techniques. First, by constructing double difference observations, the multipath effects can be effectively eliminated.

[0060] (6) in, is the double-difference phase observation. and are the phase observations from satellite i to receivers A and B respectively. and are the phase observations from satellite j to receivers A and B respectively.

[0061] The double-difference observations effectively eliminate the receiver clock error, satellite clock error and most of the system errors, while weakening the impact of multipath effects.

[0062] By using multi-frequency signals, the ionospheric delay and multipath error can be effectively separated.

[0063] For the phase observation values ​​corresponding to two different frequencies, that is, the phase observation value Φ1 corresponding to frequency f1 and the phase observation value Φ2 corresponding to frequency f2, the influence of ionospheric delay can be eliminated by the following formula: (7) Among them, ΔΦ trop is the tropospheric delay. Through multi-frequency observation, the influence of ionospheric delay can be weakened, so as to estimate the tropospheric delay more accurately.

[0064] 104. Estimate the water vapor parameters in the atmosphere based on propagation delay, observation distance and satellite positioning data.

[0065] In GNSS positioning, propagation delay usually refers to the delay of the signal in the atmosphere (ionosphere and troposphere) and the delay caused by the clock difference. From the above formula (5), it can be seen that the phase observation value (i.e., estimated distance) = propagation delay + observation distance. By subtracting the propagation time in vacuum and the ionospheric delay from the measured propagation delay, the tropospheric delay can be separated.

[0066] Optionally, in some embodiments of the present application, the step of “estimating water vapor parameters in the atmosphere according to propagation delay, observation distance, and satellite positioning data” may specifically include: determining a geometric distance between a satellite and the receiver; Estimate atmospheric water vapor parameters based on geometric distance, propagation delay, observation distance, and satellite positioning data.

[0067] The geometric distance is the straight-line distance from the satellite to the receiver, ignoring the effects of the atmosphere. The propagation delay includes the propagation time of the signal in the atmosphere, which is mainly affected by the delays in the troposphere and ionosphere. These delays can be estimated using atmospheric models and dual-frequency measurements. Adding the propagation delay, the observed distance, to the geometric distance gives the estimated distance from the satellite to the receiver. This is actually a phase observation, which includes the propagation delay of the signal in the atmosphere.

[0068] The geometric distance is the straight-line distance between the satellite and the receiver, excluding atmospheric delay.

[0069] In actual calculations, the geometric distance is usually obtained by processing the receiver's PPP algorithm, which corrects for atmospheric delays, clock differences and other errors. The observed distance is the distance calculated by the receiver based on the received GNSS signal, including the geometric distance and propagation delay. The ionospheric delay can be estimated independently using dual-frequency signals, because signals of different frequencies are affected differently by ionospheric delays. Through the GNSS signal, the total tropospheric delay can be calculated, and then, combined with the ground meteorological data and the distance residual between the observed distance and the geometric distance, the water vapor parameters in the atmosphere are estimated, that is, optionally, in some embodiments of the present application, the step of "estimating the water vapor parameters in the atmosphere based on the geometric distance, propagation delay, observed distance and satellite positioning data" can specifically include: Calculate the distance residual between the observed distance and the geometric distance; Estimate atmospheric water vapor parameters based on range residuals, propagation delays, and satellite positioning data.

[0070] The observed distance is measured from the GNSS receiver and includes the geometric path and the effect of atmospheric delay. The geometric distance is the straight-line distance between the satellite and the receiver, theoretically without any delay. The distance residual is the difference between the observed distance and the geometric distance.

[0071] For example, satellite positioning data and ground meteorological data are input into the atmospheric model, and the atmospheric model outputs the predicted distance of the model, and calculates the predicted residual between the predicted distance and the geometric distance. The propagation delay can also be added to the predicted residual. By comparing the distance residual and the predicted residual, other error sources other than atmospheric delay, such as multipath effect, can be identified. Then, the atmospheric model is adjusted based on the error source. Specifically, the ionospheric delay is estimated using dual-frequency GNSS signals. Since radio signals of different frequencies are affected by the ionosphere to different degrees, the total ionospheric delay can be calculated by comparing the delays on the two frequencies, and this delay can be subtracted from the observed distance. At the same time, advanced data processing techniques are used to identify and correct the multipath effect caused by the signal reaching the receiver through reflection or diffraction, as well as to correct the synchronization problem of the satellite and receiver clocks. The satellite's broadcast ephemeris or precise ephemeris data is usually used. After the above method, the position of the receiver is adjusted, and the total tropospheric delay can be output. Then, based on the total tropospheric delay (ZTD) and ground meteorological data, the water vapor parameters in the atmosphere are estimated.

[0072] Optionally, in some embodiments of the present application, the step of “estimating water vapor parameters in the atmosphere based on range residuals, propagation delays, and satellite positioning data” may specifically include: Based on satellite positioning data, the total tropospheric delay is determined; Calculate static delay based on ground meteorological data, distance residual and preset formula; Calculate the difference between the total tropospheric delay and the static delay to obtain the wet delay; Estimate atmospheric water vapor parameters based on surface meteorological data, propagation delay, and wet delay.

[0073] For example, the total tropospheric delay is estimated by the precise point positioning (PPP) algorithm using GNSS phase observation data. This includes all delay effects of the signal in the troposphere. The static delay is calculated using ground meteorological data (such as air pressure, temperature and humidity) and the preset static equation. ZHD has nothing to do with water vapor in the atmosphere and is mainly affected by atmospheric pressure and temperature. The static delay (ZHD) is subtracted from the total tropospheric delay (ZTD) to obtain the wet delay (ZWD). Finally, the wet delay (ZWD) and ground meteorological data are used to calculate the total amount of water vapor in the atmosphere through the appropriate conversion formula.

[0074] Specifically, the relationship between the observed residuals and the model predicted residuals can be used to infer the water vapor content in the atmosphere, and the observed residuals can be superimposed with propagation delays to reduce errors. This inversion method uses the GNSS-PWV inversion algorithm to improve the real-time water vapor inversion accuracy by building a high-quality real-time ZHD model.

[0075] The basic principle of PWV inversion is to use the tropospheric delay accurately calculated by GNSS technology to invert the total water vapor content on the signal propagation path. The specific steps are as follows: First, the total tropospheric delay (ZTD) is accurately calculated using GNSS observation data using PPP or network RTK technology; then, the static delay is calculated using ground meteorological elements combined with the static delay formula, as shown in Formula 8, and then the static delay (ZHD) is subtracted from the total tropospheric delay (ZTD) to obtain the wet delay (ZWD), as shown in Formula 9; secondly, the conversion factor (Π) for converting the wet delay to PWV is calculated using ground meteorological data (such as temperature and humidity). The conversion factor is usually estimated based on atmospheric conditions, and the commonly used formula is shown in Formula 10. Finally, the wet delay (ZWD) and the conversion factor (Π) are used to convert the wet delay to precipitable water (PWV), and the calculation formula is shown in Formula 12.

[0076] (8) Where P is the surface air pressure, φ is the latitude, H is the altitude, and f(φ,H)f is a correction function that takes into account the effects of latitude and altitude.

[0077] ZWD=ZTD−ZHD(9) (10) Π is the conversion factor, κ is an empirical constant, usually taken as 0.15. ρw is the density of water, which is about 1000 kg / m³. Tm is the weighted mean temperature, which is calculated as shown in Formula 11 and can be calculated from the atmospheric temperature T. Ts is the ground temperature.

[0078] (11) PWV = Π⋅ZWD (12) Where e(t) is the water vapor pressure and z is the altitude.

[0079] Through these steps, GNSS technology and ground-based meteorological data can be effectively used to monitor the water vapor content in the atmosphere and provide valuable information for related fields.

[0080] 105. Transmit the water vapor parameters to a data receiving center based on a preset Beidou short message communication mechanism, so that the data receiving center can locate the target device according to the water vapor parameters.

[0081] For example, data compression technology is used to compress water vapor parameters (PWV) and other related data to adapt to the data length limit of Beidou short message communication. In order to ensure the security of data transmission, the compressed data is encrypted using the encryption technology provided by the Beidou short message communication mechanism. The encrypted data is packaged into a message that conforms to the Beidou short message format. The short message is digitally modulated and prepared for transmission through the Beidou satellite. Using the Beidou system's short message communication service, the message is sent to the satellite, which is then forwarded to the data receiving center. After receiving the short message, the data receiving center decrypts and decompresses it to restore the original water vapor parameter data. The data receiving center further processes and analyzes the received water vapor parameters for positioning services of the target device, such as using water vapor parameters to correct the atmospheric delay of the target device to improve positioning accuracy.

[0082] This provides an effective means of data transmission for areas without terrestrial communication infrastructure. It is particularly suitable for remote or difficult-to-cover areas and can support real-time transmission of critical data and positioning services.

[0083] Optionally, in some embodiments of the present application, the step of “transmitting the water vapor parameters to the data receiving center based on a preset Beidou short message communication mechanism so that the data receiving center locates the target device according to the water vapor parameters” may specifically include: The water vapor parameters are compressed based on the Huffman coding method, and the compressed data is encrypted to obtain encrypted data; The encrypted data is sent to the satellite according to a preset short message service, and the satellite forwards the encrypted data to a data receiving center so that the data receiving center can locate the target device according to the encrypted data.

[0084] Huffman Coding is a widely used lossless data compression algorithm that is used to create variable-length codes, where the most common data is assigned shorter codes and the less common data is assigned longer codes.

[0085] Huffman coding is used to compress water vapor parameter data such as PWV. Huffman coding is a lossless data compression algorithm that can effectively reduce the amount of data. The compressed data is encrypted to ensure the security and integrity of the data during transmission. Possible encryption technologies include source encryption. Next, the encrypted data is packaged into a format suitable for the Beidou short message service, and the short message data is digitally modulated. The encrypted compressed data is sent to the satellite using the Beidou system's short message communication service. After receiving the short message, the Beidou satellite forwards it to the data receiving center. The data receiving center receives the encrypted compressed data, first decrypts it, and then decompresses the data to restore the original water vapor parameters. The recovered water vapor parameter data is further processed and analyzed for precise positioning services for target devices.

[0086] As can be seen from the above, the embodiment of the present application provides a device positioning method based on water vapor parameters. After obtaining ground meteorological data and satellite positioning data, the observation distance between the satellite and the receiver is determined according to the precise single point positioning algorithm and the satellite positioning data. Then, based on the preset atmospheric model, the observation distance and the ground meteorological data, the propagation delay of the signal during atmospheric propagation is estimated. Then, according to the propagation delay, the observation distance and the satellite positioning data, the water vapor parameters in the atmosphere are estimated. Finally, based on the preset Beidou short message communication mechanism, the water vapor parameters are transmitted to the data receiving center so that the data receiving center can locate the target device according to the water vapor parameters. In the device positioning scheme based on water vapor parameters provided in the present application, it does not rely on the signal of the ground network. Based on the preset atmospheric model, the observation distance and the ground meteorological data, the propagation delay of the signal during atmospheric propagation is estimated. Then, according to the propagation delay, the observation distance and the satellite positioning data, the water vapor parameters in the atmosphere are estimated. Finally, the water vapor parameters are transmitted back to the monitoring center, so as to grasp the water vapor information of the operating area in real time, ensure high-precision positioning under no network conditions, and realize high-precision positioning of the device without a network, that is, improve the accuracy of device positioning.

[0087] In order to further understand the device positioning method based on water vapor parameters of this application, the following is a specific description based on the atmospheric monitoring and data transmission process of the Beidou satellite navigation system. Figure 2, the satellite-based PPP-B2B solution terminal receives navigation signals and other necessary auxiliary information from satellites, including satellite ephemeris, clock error, orbit, hardware delay, and collects ground meteorological data such as temperature, humidity, and air pressure, and uses these data for tropospheric delay modeling and water vapor solution. Among them, the satellite-based PPP-B2B solution terminal refers to a terminal device that uses satellite signals for precise point positioning (PPP), and specifically uses satellite-based augmentation services to improve positioning accuracy. The solution terminal is a device that can perform positioning solution, that is, calculate the precise position of the receiver. This usually involves receiving GNSS signals, applying PPP algorithms, and combining satellite ephemeris, clock error, atmospheric model and other data to estimate the three-dimensional position of the receiver. Satellite-based augmentation systems (such as WAAS in the United States, EGNOS in Europe, SDCM in Russia, and SBAS in China) broadcast additional correction information through satellites in geostationary orbit to improve the accuracy and reliability of GNSS signals. The satellite-based PPP-B2B solution terminal uses PPP technology to perform precise positioning calculations on the terminal position. Based on the PPP positioning calculation results, the atmospheric delay estimation method based on the GNSS signal phase is used to model the tropospheric delay. The satellite-based PPP-B2B solution terminal estimates the water vapor content in the atmosphere by analyzing the PPP positioning calculation results and the atmospheric delay model. The satellite-based PPP-B2B solution terminal compresses and encodes the water vapor content, tropospheric delay, atmospheric temperature, and humidity information in the above steps through the Beidou short message transmission coding technology, reduces the data length, and then encrypts and transmits it to the monitoring center. In this way, it is possible to obtain high-precision atmospheric key parameters without a network and transmit them back to the monitoring center, so as to grasp the water vapor information in the operating area in real time and ensure high-precision positioning without a network.

[0088] Specifically, the BeiDou satellite system is used to monitor key parameters in the atmosphere, especially the water vapor content. Through the Integrated GNSS Remote Sensing Tracking System (IGSRTS), in the IGS RTS, accurate satellite orbit information is the basis. The satellite orbit data of the Global Navigation Satellite System (GNSS) is provided by the International GNSS Service (IGS) and other organizations to calculate the accurate distance from the satellite to the ground receiver; the clock error includes the satellite clock error and the receiver clock error. Since the calculation of the signal transmission time depends on accurate time measurement, clock error correction is essential to eliminate time measurement errors. In the IGS RTS, clock error correction helps to improve the accuracy of positioning data; hardware delay involves the propagation delay of the signal in the receiver hardware, including antennas, RF front ends, samplers and other parts. These delays are inherent in the signal processing process and must be compensated by correction models to ensure the accuracy of the data. In the IGS RTS, signals from multiple GNSS satellites are collected, as well as the related orbit and clock error data. The collected data is processed using professional software, orbit and clock error information is applied, and hardware delays are corrected at the same time. The precise positioning of the target is achieved by comprehensively considering the correction of orbit, clock error and hardware delay. The terminal uses satellite precise point positioning (PPP) technology to perform two-way calculation of the water vapor content in the atmosphere. The terminal establishes an atmospheric delay model based on the observation data between the satellite and the receiver. By comparing the actual observation residual with the expected observation residual, the water vapor content in the atmosphere is inverted.

[0089] The monitoring center receives and processes data from the terminal to monitor and analyze the atmospheric water vapor content. Three Beidou satellites are used for data transmission and positioning services.

[0090] The RF chip amplifies the received signal to ensure that the signal strength is sufficient for subsequent processing. The amplified signal is sent to the digital intermediate frequency processing module, where the signal is converted into digital form. The digital intermediate frequency processing module converts the analog signal into a 2- or 4-bit digital signal, which determines the quantization accuracy of the signal. The digital intermediate frequency processing module uses a 50MHz sampling clock to sample the signal to ensure the digitization quality of the signal. The sampling frequency is high enough to avoid aliasing and retain the high-frequency components of the signal. The digital signal is sent to the RDSS baseband chip for further processing. The RDSS baseband chip is responsible for further processing the digital intermediate frequency signal into a baseband signal, including demodulation, decoding, and error correction. When data needs to be sent, the RDSS baseband chip BPSK modulates the data. BPSK is a commonly used digital modulation technology that transmits information by changing the phase of the carrier. The modulated BPSK signal is loaded onto the transmitting carrier and then sent to the satellite through the transmitting link of the RF chip. Before sending, the RDSS baseband chip compresses and encrypts the data to improve transmission efficiency and security. The RDSS baseband chip can process and generate short messages for communication via satellite.

[0091] In order to better implement the device positioning method based on water vapor parameters in the embodiment of the present application, the embodiment of the present application also provides a device positioning device based on water vapor parameters. The meanings of the terms are the same as those in the above-mentioned device positioning system based on water vapor parameters, and the specific implementation details can refer to the description in the system embodiment.

[0092] See also Figure 3 , Figure 3 A schematic diagram of the structure of a device positioning apparatus based on water vapor parameters provided in an embodiment of the present application, wherein the device positioning apparatus based on water vapor parameters may specifically include an acquisition module 201, a determination module 202, a first estimation module 203, a second estimation module 204 and a positioning module 205, which may be specifically as follows: Acquisition module 201, used to acquire ground meteorological data and satellite positioning data; The determination module 202 is used to determine the observation distance between the satellite and the receiver according to the precise point positioning algorithm and the satellite positioning data.

[0093] The first estimation module 203 is used to estimate the propagation delay of the signal when it propagates in the atmosphere based on a preset atmospheric model, the observation distance and the ground meteorological data.

[0094] Optionally, in some embodiments of the present application, the first estimation module 203 may specifically include: A demodulation unit, used to demodulate the satellite positioning data to obtain a phase signal corresponding to the satellite positioning data; The first estimation unit is used to estimate the propagation delay of the signal when it propagates in the atmosphere according to phase signals of multiple frequencies, a preset atmospheric model and the ground meteorological data.

[0095] Optionally, in some embodiments of the present application, the first estimation unit can be specifically used to: input ground meteorological data into a preset atmospheric model to estimate the delay of the signal in the troposphere; estimate the delay of the signal in the ionosphere based on phase signals of multiple frequencies; and estimate the propagation delay of the signal when propagating in the atmosphere based on the delay of the signal in the troposphere and the delay of the signal in the ionosphere.

[0096] The second estimation module 204 is used to estimate the water vapor parameters in the atmosphere according to the propagation delay, the observation distance and the satellite positioning data.

[0097] Optionally, in some embodiments of the present application, the second estimation module 204 may specifically include: A determination unit, configured to determine a geometric distance between the satellite and the receiver; The second estimation unit is used to estimate the water vapor parameters in the atmosphere according to the geometric distance, propagation delay, observation distance and satellite positioning data.

[0098] Optionally, in some embodiments of the present application, the second estimation unit may specifically include: A calculation subunit, used to calculate the distance residual between the observed distance and the geometric distance; The estimation subunit is used to estimate the water vapor parameters in the atmosphere based on the range residual, the propagation delay and the satellite positioning data.

[0099] Optionally, in some embodiments of the present application, the estimation subunit may be specifically used for: Based on satellite positioning data, the total tropospheric delay is determined; Calculate static delay based on ground meteorological data, distance residual and preset formula; Calculate the difference between the total tropospheric delay and the static delay to obtain the wet delay; Estimate atmospheric water vapor parameters based on surface meteorological data, propagation delay, and wet delay.

[0100] The positioning module 205 is used to transmit the water vapor parameters to the data receiving center based on the preset Beidou short message communication mechanism, so that the data receiving center can locate the target device according to the water vapor parameters.

[0101] Optionally, in some embodiments of the present application, the positioning module 205 can be specifically used to: compress water vapor parameters based on Huffman coding, and encrypt the compressed data to obtain encrypted data; send the encrypted data to the satellite according to a preset short message service, and the satellite forwards the encrypted data to a data receiving center, so that the data receiving center can locate the target device according to the encrypted data.

[0102] An embodiment of the present application provides a device positioning apparatus based on water vapor parameters. After the acquisition module 201 acquires ground meteorological data and satellite positioning data, the determination module 202 determines the observation distance between the satellite and the receiver according to the precise single-point positioning algorithm and the satellite positioning data. Then, the first estimation module 203 estimates the propagation delay of the signal during atmospheric propagation based on a preset atmospheric model, the observation distance and the ground meteorological data. Then, the second estimation module 204 estimates the water vapor parameters in the atmosphere according to the propagation delay, the observation distance and the satellite positioning data. Finally, the positioning module 205 transmits the water vapor parameters to the data receiving center based on the preset Beidou short message communication mechanism, so that the data receiving center can locate the target device according to the water vapor parameters. In the device positioning solution based on water vapor parameters provided in the present application, it does not rely on the signal of the ground network. It estimates the propagation delay of the signal in the atmosphere based on the preset atmospheric model, observation distance and ground meteorological data, and then estimates the water vapor parameters in the atmosphere based on the propagation delay, observation distance and satellite positioning data. Finally, the water vapor parameters are transmitted back to the monitoring center, so as to grasp the water vapor information of the operating area in real time, ensure high-precision positioning under no network conditions, and realize high-precision positioning of the equipment in the absence of a network, that is, improve the accuracy of equipment positioning.

[0103] In addition, the present application also provides an electronic device, such as Figure 4 As shown, it shows a schematic diagram of the structure of the electronic device involved in the embodiment of the present application, specifically: The electronic device may include components such as a processor 301 with one or more processing cores, a memory 302 with one or more computer-readable storage media, a power supply 303, and an input unit 304. Those skilled in the art will appreciate that Figure 4 The electronic device structure shown in the figure does not constitute a limitation on the electronic device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. The processor 301 is the control center of the electronic device. It uses various interfaces and lines to connect various parts of the entire electronic device. By running or executing software programs and / or modules stored in the memory 302, and calling data stored in the memory 302, it executes various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole. Optionally, the processor 301 may include one or more processing cores; preferably, the processor 301 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 301.

[0104] The memory 302 can be used to store software programs and modules. The processor 301 executes various functional applications and a device positioning method based on water vapor parameters by running the software programs and modules stored in the memory 302. The memory 302 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 302 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 302 may also include a memory controller to provide the processor 301 with access to the memory 302.

[0105] The electronic device also includes a power supply 303 for supplying power to each component. Preferably, the power supply 303 can be logically connected to the processor 301 through a power management system, so that the power management system can manage charging, discharging, power consumption and other functions. The power supply 303 can also include one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, power status indicators and other arbitrary components.

[0106] The electronic device may further include an input unit 304, which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0107] Although not shown, the electronic device may further include a display unit, etc., which will not be described in detail herein. Specifically in this embodiment, the processor 301 in the electronic device will load the executable files corresponding to the processes of one or more application programs into the memory 302 according to the following instructions, and the processor 301 will run the application programs stored in the memory 302, thereby realizing various functions, as follows: Acquire ground meteorological data and satellite positioning data; determine the observation distance between the satellite and the receiver based on the precise single-point positioning algorithm and the satellite positioning data; estimate the propagation delay of the signal in the atmosphere based on the preset atmospheric model, observation distance and ground meteorological data; estimate the water vapor parameters in the atmosphere based on the propagation delay, observation distance and satellite positioning data; transmit the water vapor parameters to the data receiving center based on the preset Beidou short message communication mechanism, so that the data receiving center can locate the target device according to the water vapor parameters.

[0108] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0109] After acquiring ground meteorological data and satellite positioning data, the embodiment of the present application determines the observation distance between the satellite and the receiver according to the precise single point positioning algorithm and the satellite positioning data, then estimates the propagation delay of the signal in the atmosphere based on the preset atmospheric model, the observation distance and the ground meteorological data, and then estimates the water vapor parameters in the atmosphere based on the propagation delay, the observation distance and the satellite positioning data, and finally transmits the water vapor parameters to the data receiving center based on the preset Beidou short message communication mechanism so that the data receiving center can locate the target device according to the water vapor parameters. In the device positioning scheme based on water vapor parameters provided in the present application, it does not rely on the signal of the ground network, estimates the propagation delay of the signal in the atmosphere based on the preset atmospheric model, the observation distance and the ground meteorological data, and then estimates the water vapor parameters in the atmosphere based on the propagation delay, the observation distance and the satellite positioning data, and finally transmits the water vapor parameters back to the monitoring center, so as to grasp the water vapor information of the operation area in real time, ensure high-precision positioning under no network conditions, and realize high-precision positioning of the device without a network, that is, improve the accuracy of device positioning.

[0110] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0111] To this end, an embodiment of the present application provides a storage medium in which a plurality of instructions are stored, and the instructions can be loaded by a processor to execute the steps in any of the device positioning methods based on water vapor parameters provided in the embodiments of the present application. For example, the instructions can execute the following steps: Acquire ground meteorological data and satellite positioning data; determine the observation distance between the satellite and the receiver based on the precise single-point positioning algorithm and the satellite positioning data; estimate the propagation delay of the signal in the atmosphere based on the preset atmospheric model, observation distance and ground meteorological data; estimate the water vapor parameters in the atmosphere based on the propagation delay, observation distance and satellite positioning data; transmit the water vapor parameters to the data receiving center based on the preset Beidou short message communication mechanism, so that the data receiving center can locate the target device according to the water vapor parameters.

[0112] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0113] The storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0114] Since the instructions stored in the storage medium can execute the steps in any one of the device positioning methods based on water vapor parameters provided in the embodiments of the present application, the beneficial effects that can be achieved by any one of the device positioning methods based on water vapor parameters provided in the embodiments of the present application can be achieved. Please see the previous embodiments for details and will not be repeated here.

[0115] The above is a detailed introduction to a device positioning method, apparatus, equipment and medium based on water vapor parameters provided in an embodiment of the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A device positioning method based on water vapor parameters, It is characterized in that include: Obtain ground meteorological data and satellite positioning data; Determine the observation distance between the satellite and the receiver according to the precise point positioning algorithm and the satellite positioning data; Based on a preset atmospheric model, the observation distance and the ground meteorological data, estimating a propagation delay of a signal during atmospheric propagation; estimating water vapor parameters in the atmosphere according to the propagation delay, the observation distance and the satellite positioning data; The water vapor parameters are transmitted to a data receiving center based on a preset Beidou short message communication mechanism, so that the data receiving center can locate the target device according to the water vapor parameters.

2. The device positioning method based on water vapor parameters according to claim 1, It is characterized in that The estimating the propagation delay of the signal during atmospheric propagation based on the preset atmospheric model, the observation distance and the ground meteorological data includes: Demodulating the satellite positioning data to obtain a phase signal corresponding to the satellite positioning data; The propagation delay of the signal when propagating in the atmosphere is estimated according to the phase signals of multiple frequencies, a preset atmospheric model and the ground meteorological data.

3. The device positioning method based on water vapor parameters according to claim 2, It is characterized in that The method of estimating the propagation delay of a signal during atmospheric propagation according to the phase signals of multiple frequencies, a preset atmospheric model and the ground meteorological data comprises: Inputting the ground meteorological data into a preset atmospheric model to estimate the delay of the signal in the troposphere; Estimate the delay of the signal in the ionosphere based on phase signals of multiple frequencies; Estimate the propagation delay of the signal as it propagates through the atmosphere based on the signal delay in the troposphere and the signal delay in the ionosphere.

4. The device positioning method based on water vapor parameters according to claim 1, It is characterized in that The estimating the water vapor parameters in the atmosphere according to the propagation delay, the observation distance and the satellite positioning data comprises: determining a geometric distance between the satellite and the receiver; Water vapor parameters in the atmosphere are estimated according to the geometric distance, the propagation delay, the observation distance and the satellite positioning data.

5. The device positioning method based on water vapor parameters according to claim 4, It is characterized in that The estimating the water vapor parameters in the atmosphere according to the geometric distance, the propagation delay, the observation distance and the satellite positioning data comprises: Calculating a distance residual between the observed distance and the geometric distance; A water vapor parameter in the atmosphere is estimated based on the range residual, the propagation delay and the satellite positioning data.

6. The device positioning method according to claim 5, It is characterized in that The estimating the water vapor parameter in the atmosphere based on the range residual, the propagation delay and the satellite positioning data comprises: Determining a total tropospheric delay based on the satellite positioning data; Calculating static delay based on the ground meteorological data, distance residual and a preset formula; Calculate the difference between the total tropospheric delay and the static delay to obtain the wet delay; Water vapor parameters in the atmosphere are estimated according to the ground meteorological data, the propagation delay and the wet delay.

7. The device positioning method based on water vapor parameters according to claim 1, It is characterized in that The method of transmitting the water vapor parameters to a data receiving center based on a preset Beidou short message communication mechanism so that the data receiving center can locate the target device according to the water vapor parameters includes: Compressing the water vapor parameter based on a Huffman coding method, and encrypting the compressed data to obtain encrypted data; The encrypted data is sent to the satellite according to a preset short message service, and the satellite forwards the encrypted data to a data receiving center so that the data receiving center can locate the target device according to the encrypted data.

8. A device positioning device based on water vapor parameters, It is characterized in that include: An acquisition module is used to obtain ground meteorological data and satellite positioning data; A determination module, used to determine the observation distance between the satellite and the receiver according to the precise point positioning algorithm and the satellite positioning data; A first estimation module, used for estimating the propagation delay of the signal when propagating in the atmosphere based on a preset atmospheric model, the observation distance and the ground meteorological data; A second estimation module, used for estimating water vapor parameters in the atmosphere according to the propagation delay, the observation distance and the satellite positioning data; The positioning module is used to transmit the water vapor parameters to a data receiving center based on a preset Beidou short message communication mechanism, so that the data receiving center can locate the target device according to the water vapor parameters.

9. An electronic device, It is characterized in that include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the device positioning method based on water vapor parameters as described in any one of claims 1 to 7 are performed.

10. A storage medium, It is characterized in that A computer program is stored which can be loaded by a processor and execute the device positioning method based on water vapor parameters as described in any one of claims 1 to 7.

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