Low earth orbit satellite observation data simulation method, system, equipment and medium

Abstract

The invention provides a low-earth-orbit satellite observation data simulation method, system and device and a medium. The method comprises the steps that low-earth-orbit satellite orbit and position information is acquired; based on historical data, precise point positioning calculation is carried out on the GNSS satellite, and errors in a transmission path are determined; performing satellite-borne low-orbit observation value simulation and ground low-orbit observation value simulation based on the low-orbit satellite orbit and position information and the error in the transmission path; wherein noise and cycle slip are added to the satellite-borne low-orbit observation value and the ground low-orbit observation value. According to the method, the low-orbit observation data reflecting real conditions can be obtained, cycle slip can be added according to scene requirements, and corresponding noise can be added according to the performance of a low-orbit satellite receiver. And the real receiver clock error is adopted to replace the fitted receiver clock error, so that the performance of the low-orbit satellite receiver clock can be reflected better. By performing environmental error grafting processing on the observation data, low-orbit ground observation data in a complex environment can be obtained.

Description

Technical Field

[0001] The present invention relates to the field of satellite navigation, and in particular to a method, system, device and medium for simulating low-orbit satellite observation data. Background Art

[0002] There are few existing methods for simulating low-orbit satellite observation data and they are imperfect. The simulation of observation data mainly focuses on GNSS (Global Navigation Satellite System) data. The corresponding satellite ephemeris is generated through the designed GNSS satellite constellation or LEO (Low Earth Orbit) satellite constellation; then the GNSS / low-orbit satellite / ground monitoring station clock error is simulated; finally, based on the simulated ephemeris and clock error data, according to the GNSS precise single-point positioning model and various system noise characteristics, the low-orbit observation data is simulated, but only the low-orbit observation data in an open environment is simulated, and no simulation processing is performed on the low-orbit satellite observation data in a complex environment. Summary of the invention

[0003] The embodiments of the present application provide a low-orbit satellite observation data simulation method, system, device and medium for simulating low-orbit satellite observation data in a complex environment.

[0004] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by the practice of the present application.

[0005] According to the first aspect of the embodiment of the present application, a method for simulating low-orbit satellite observation data is provided, including: obtaining low-orbit satellite orbit and position information; performing precise single-point positioning solution on GNSS satellites based on historical data to determine the error in the transmission path; based on the low-orbit satellite orbit and position information and the error in the transmission path, performing on-board low-orbit observation value simulation and ground-based low-orbit observation value simulation; wherein noise and cycle slips are added to the on-board low-orbit observation values ​​and ground-based low-orbit observation values. The simulation method of the present application can more realistically reflect the true characteristics of the observation data.

[0006] In one embodiment of the present application, the low-orbit satellite observation data simulation method further includes grafting environmental errors on the basis of the simulated ground low-orbit observation values ​​to obtain ground low-orbit observation data in a complex environment.

[0007] In one embodiment of the present application, the obtaining of low-orbit satellite orbit and position information specifically includes: obtaining low-orbit satellite orbit and position information based on initial parameters and a dynamic model of a low-orbit satellite constellation.

[0008] In one embodiment of the present application, the historical data includes GNSS satellite observation data during a low-orbit satellite observation period.

[0009] In one embodiment of the present application, the error in the transmission path includes tropospheric delay and ground receiver clock error.

[0010] In one embodiment of the present application, the satellite-borne low-orbit observation value simulation includes: determining the GNSS satellite position at the time of information transmission based on the low-orbit satellite position information and the corresponding clock error and the GNSS satellite orbit and the corresponding clock error; calculating the geometric distance between the GNSS satellite and the low-orbit satellite; superimposing the GNSS satellite error, the first propagation error and the low-orbit satellite error on the geometric distance between the GNSS satellite and the low-orbit satellite to obtain the satellite-borne low-orbit observation value; wherein the satellite-borne low-orbit observation value includes the satellite-borne low-orbit pseudorange observation value and the satellite-borne low-orbit carrier phase observation value.

[0011] In one embodiment of the present application, after calculating the geometric distance between the GNSS satellite and the low-orbit satellite, it also includes determining whether the GNSS satellite and the low-orbit satellite are in line of sight.

[0012] In one embodiment of the present application, the simulation of ground low-orbit observation values ​​includes: determining the low-orbit satellite position at the time of information transmission based on the low-orbit satellite orbit and corresponding clock error, ground monitoring station position information and ground receiver clock error; calculating the geometric distance between the low-orbit satellite and the ground monitoring station; superimposing the low-orbit satellite error, the second propagation error and the ground receiver error on the basis of the geometric distance between the low-orbit satellite and the ground monitoring station to obtain the ground low-orbit observation value; wherein the ground low-orbit observation value includes the ground low-orbit pseudorange observation value and the ground low-orbit carrier phase observation value.

[0013] In one embodiment of the present application, the second propagation error includes ionospheric delay and tropospheric delay.

[0014] In one embodiment of the present application, after calculating the geometric distance between the low-orbit satellite and the ground monitoring station, it also includes determining whether the low-orbit satellite and the ground monitoring station are in line of sight.

[0015] In one embodiment of the present application, the clock error of the low-orbit satellite is represented by a pre-estimated ground receiver clock error.

[0016] In one embodiment of the present application, the low-orbit satellite observation data simulation method further includes adding noise to the onboard low-orbit observation values ​​and the ground low-orbit observation values ​​according to the type of low-orbit receiver and satellite altitude information.

[0017] In one embodiment of the present application, the low-orbit satellite observation data simulation method also includes adding cycle slips to the satellite-borne low-orbit carrier phase observation values ​​and the ground low-orbit phase observation values ​​according to the probability of cycle slips; the probability of cycle slips is set in advance according to the environment.

[0018] In one embodiment of the present application, the method of grafting environmental errors on the basis of ground low orbit observation values ​​obtained by simulation to obtain ground low orbit observation data in a complex environment specifically includes: extracting environmental errors; modeling environmental errors based on a semi-celestial model to generate an environmental error correction table; and grafting corresponding environmental errors on the basis of ground low orbit observation values ​​through the environmental error correction table to obtain ground low orbit observation data in a complex environment.

[0019] In one embodiment of the present application, the extracted environmental error is obtained by solving GNSS satellite observation data.

[0020] According to the second aspect of an embodiment of the present application, a system is provided, including: a position information acquisition module, used to acquire low-orbit satellite orbit and position information; an error solution module, which performs precise single-point positioning solution on the GNSS satellite based on historical data and determines the error in the transmission path; an observation value simulation module, which performs satellite-borne low-orbit observation value simulation and ground-based low-orbit observation value simulation based on the low-orbit satellite orbit and position information and the error in the transmission path; wherein noise and cycle slips are added to the satellite-borne low-orbit observation values ​​and the ground-based low-orbit observation values.

[0021] According to a third aspect of an embodiment of the present application, an electronic device is provided, including a memory and a processor, wherein the memory stores a computer program corresponding to the low-orbit satellite observation data simulation method described in the first aspect and capable of being loaded and executed by the processor.

[0022] According to a fourth aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which computer program instructions are stored. When the program instructions are executed by a processor, they are used for a process corresponding to the low-orbit satellite observation data simulation method described in the first aspect.

[0023] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 This is a low-orbit satellite observation data simulation flow chart of an embodiment of the present application.

[0026] Figure 2 This is a flow chart of obtaining low-orbit satellite position information according to an embodiment of the present application.

[0027] Figure 3 This is a flow chart of the simulation of satellite low-orbit observation data according to an embodiment of the present application.

[0028] Figure 4 This is a flow chart of the simulation of ground low-orbit observation data according to an embodiment of the present application.

[0029] Figure 5 This is a flowchart of environmental error extraction and grafting according to an embodiment of the present application.

[0030] Figure 6 A schematic diagram of an electronic device according to an embodiment of the present application.

[0031] Figure 7 A schematic diagram of the structure of a computer system suitable for implementing the embodiments of the present application.

[0032] Reference numerals: 500-electronic device, 501-memory, 502-processor; 600-computer system, 601-CPU, 602-ROM, 603-RAM, 604-bus, 605-I / O interface, 606-input part, 607-output part, 608-storage part, 609-communication part, 610-drive, 611-removable medium. DETAILED DESCRIPTION

[0033] To make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme in the embodiment of the present application will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application. In the absence of conflict, the embodiments in the present application and the features in the embodiments can be combined with each other arbitrarily. In addition, although the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in an order different from that here.

[0034] The terms "first" and "second" in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the term "comprising" and any variation thereof are intended to cover non-exclusive protection. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0035] The current simulation method takes into account the errors on the propagation path, but ignores the impact of the receiver's own noise errors and ambiguity cycle slips. At the same time, the use of fitting simulation clock errors cannot truly reflect the clock error situation. There is no corresponding research on the simulation of observation data in complex scenarios.

[0036] Based on this, the embodiment of the present application proposes a method for simulating low-orbit satellite observation data, which adds corresponding receiver noise and cycle slips during simulation, can better reflect the real low-orbit data, and further process the low-orbit satellite. Figure 1 , the specific plan is as follows: S100, obtaining low-orbit satellite orbit and position information; When simulating a low-orbit satellite, it is necessary to first model the low-orbit satellite constellation. Generally, the low-orbit satellite constellation design often adopts the Walker constellation configuration, where the Walker constellation is composed of circular orbits with the same orbital height and inclination, and has good regional coverage characteristics. It can be represented by five parameters T / P / F / h / i, where T represents the number of satellites, P represents the number of orbital planes, F represents the phase factor of satellites in adjacent orbital planes, h is the satellite orbit height in the constellation, and i is the satellite orbit inclination in the constellation.

[0037] The satellite moves under the influence of two-body motion and various perturbations, which include conservative forces and non-conservative forces. In addition, empirical force perturbations must also be considered. The satellite's motion equation in the inertial coordinate system can be expressed as: (1) in, is the sum of the forces acting on the satellite, is the satellite's position; is the distance from the satellite to the center of the Earth; is the Earth's gravitational constant multiplied by the Earth's mass; It is a conservative force, including central gravity, tidal gravity, general relativity, N-body gravity, etc.; are non-conservative forces, including solar radiation pressure, atmospheric forces, and earth radiation pressure; is the empirical acceleration. In the embodiments of the present application, the dynamic model used is shown in Table 1.

[0038] Table 1 Kinetic model

[0039] For low-orbit satellites, the initial position and velocity can be used to obtain the integral through the dynamic model. t Position at the moment : (2) in, , , Respectively represent the low-orbit satellite position, velocity and dynamic model at the initial moment, is the state transfer matrix from the initial time to time t, which can be calculated by the variational equation. Based on formula (2), the position of the low-orbit satellite at any time can be obtained by dynamic integration (such as Runge-Kutta method or Adams method).

[0040] Please refer to Figure 2 , showing the process of obtaining the position information of the low-orbit satellite in the embodiment of the present application. First, set the low-orbit constellation parameters to complete the modeling, and determine all the low-orbit satellites and orbits that need to be simulated. Then, select one of the low-orbit satellites, obtain its initial position and velocity, and set the dynamic parameters (including the gravity of the center of the earth, the non-spherical gravity of the earth, the N-body gravitational perturbation, the solid tide and the sea tide perturbation, the solar light pressure perturbation, the relativistic effect, and the atmospheric drag). After the setting is completed, the position information of the low-orbit satellite is calculated by the dynamic integral formula. Finally, determine whether the selected low-orbit satellite is the last low-orbit satellite. If so, output the calculated position information of all low-orbit satellites. If not, select the next low-orbit satellite and calculate the position information of the low-orbit satellite until the position information calculation of all low-orbit satellites is completed.

[0041] S200, performing precise single-point positioning calculation on the GNSS satellite based on historical data to determine the error in the transmission path; To simulate the low-orbit satellite observation values, it is essential to introduce errors. The embodiment of the present application is based on the historical data of GNSS satellites and combines precise point positioning (PPP) to obtain various error parameters. The specific solution formula is as follows: (3) in, represents the GNSS satellite pseudorange observation value, represents the GNSS satellite carrier phase observation value, the superscript s, subscript r and j represent the PRN number of the GNSS satellite, the ground receiver ID and the observation value frequency, respectively, which characterizes the observation frequency. In this embodiment, j is 1 and 2, i.e., two simulation frequencies. Taking the BDS system as an example, j=1 represents the frequency of BDS B1I, and j=2 represents the frequency of BDS B3I; is the geometric distance between the GNSS satellite and the ground receiver, in meters; and are the ground receiver clock error and the GNSS satellite clock error, respectively, in meters; is the tropospheric delay, in meters; is the frequency The corresponding ionospheric delay is in meters; is the frequency-dependent ionospheric delay amplification factor; is the integer ambiguity, in weeks; For frequency The corresponding carrier wavelength; and They are ground receiver pseudorange hardware delay and GNSS satellite pseudorange hardware delay, in meters; and They are the ground receiver phase hardware delay and the GNSS satellite phase hardware delay, in meters; and They are the multipath, observation noise and other influences on the pseudorange observation values ​​of each frequency and the multipath, observation noise and other influences on the carrier phase observation values.

[0042] It should be noted that the historical data selected for the solution is related to the simulation time. For example, when simulating the low-orbit satellite observation values ​​of the day, the GNSS satellite observation data of the day is used to solve the errors in the transmission path of the day.

[0043] Specifically, in the embodiment of the present application, the tropospheric delay in the transmission path and the ground receiver clock error are mainly solved. , which can be divided into two components: dry delay and wet delay, expressed as: (4) in, and denote the dry delay and wet delay in the zenith tropospheric delay, and are functions of the dry and wet delay projections of the zenith tropospheric delay, respectively.

[0044] In order to simulate the subsequent complex environment, when solving the ground receiver clock error, the deviation ISB between different systems can also be solved at the same time. The systems involved include BDS, GPS, Galileo, etc. Different systems refer to BDS and GPS, or BDS and Galileo, etc. After determining the ground receiver clock error of one system, the receiver clock error of other systems can be determined through the deviation ISB.

[0045] At this point, the required error for a certain day can be calculated by combining formula (3) with the GNSS satellite observation data for that day.

[0046] S300: Based on the low-orbit satellite constellation position information and the error in the transmission path, perform on-board low-orbit observation value simulation and ground-based low-orbit observation value simulation.

[0047] After solving the existing errors, the low-orbit satellite observation data can be simulated. The embodiment of the present application mainly includes two parts: simulation of satellite-borne low-orbit observation values ​​and simulation of ground-based low-orbit observation values.

[0048] Please refer to Figure 3 , showing a simulation flow chart of satellite-borne low-orbit observation values. In practical applications, since the time to obtain information is the time when the ground receiver obtains the observation data, it takes time for the transmission path from the GNSS satellite to the receiver, which is not the time when the information is transmitted. Therefore, in the simulation process, for any GNSS satellite, it is necessary to iteratively calculate the GNSS satellite position at the time of information transmission based on the GNSS satellite orbit and the GNSS satellite clock error, the low-orbit satellite position information and the low-orbit satellite receiving end clock error, and then calculate the geometric distance between the GNSS satellite and the low-orbit satellite. In one embodiment, after calculating the geometric distance between the GNSS satellite and the low-orbit satellite, it is also necessary to make a line of sight judgment between the two. If the line of sight is met, the subsequent observation value simulation is performed, otherwise the next GNSS satellite is switched for simulation, that is, according to the next GNSS satellite orbit and the GNSS satellite clock error, as well as the low-orbit satellite position information and the low-orbit satellite receiving end clock error, the GNSS satellite position at the time of corresponding information transmission is calculated, and then the geometric distance between the GNSS satellite and the low-orbit satellite is determined until the simulation of all GNSS satellites is completed.

[0049] Furthermore, by superimposing the GNSS satellite error, the first propagation error and the low-orbit satellite error on the geometric distance between the GNSS satellite and the low-orbit satellite, the onboard low-orbit observation value can be obtained; in this embodiment, the GNSS satellite error includes the GNSS satellite PCO / PCV correction, pseudorange and carrier phase hardware delay, relativistic effect, and antenna phase winding, among which the GNSS PCO and PCV can be obtained through the IGS20.atx file released by various institutions; the relativistic effect and antenna phase winding error can be obtained through existing model calculations; the pseudorange and carrier phase hardware delay are added using the corresponding DCB (Differential Code Bias) and UPD (Uncalibrated Phase Delay) products. The first propagation error includes ionospheric delay, which can be obtained through existing product equipment. The low-orbit satellite error includes the low-orbit satellite PCO / PCV correction, pseudorange and carrier phase hardware delay, relativistic effect and antenna phase winding, and the acquisition method is the same as the GNSS satellite error.

[0050] Specifically, the satellite-borne low-orbit observation values ​​include satellite-borne low-orbit pseudo-range observation values ​​and satellite-borne low-orbit carrier phase observation values. The simulation formula is as follows: (5) in, represents the satellite-borne low-orbit pseudorange observation value, represents the satellite-borne low-orbit carrier phase observation value, and the subscript leo refers to the low-orbit satellite. Indicates the geometric distance from the GNSS satellite to the low-orbit satellite. represents the clock error of the low-orbit satellite receiving end, represents the GNSS satellite clock error, represents the ionospheric delay from GNSS to low-orbit satellites, Indicates the pseudo-range hardware delay of the low-orbit satellite receiver. Indicates the GNSS satellite pseudorange hardware delay, Indicates the phase hardware delay of the low-orbit satellite receiver. Indicates the GNSS satellite phase hardware delay, represents the frequency-dependent ionospheric delay amplification factor, Indicates frequency The corresponding carrier wavelength, Represents the ambiguity parameter from the GNSS satellite to the low-orbit satellite. During the simulation, the GNSS satellite position is obtained using precise orbit products. The GNSS satellite clock error uses a precise clock error product. Due to the cost constraints of the low-orbit satellite constellation, the receiver clock used is usually a rubidium clock or an atomic clock. The clock error obtained by fitting is difficult to show the actual clock error. In this embodiment, the clock error of the low-orbit satellite receiver is randomly selected from the ground receiver clock error set, which can better reflect the performance of the low-orbit satellite clock; wherein, the ground receiver clock error set is generated by pre-estimating different ground receiver clocks.

[0051] Please refer to Figure 4 , showing a flow chart of ground low-orbit observation value simulation. Similar to the simulation process of satellite-borne low-orbit observation values, when simulating ground low-orbit observation values, for any low-orbit satellite, the low-orbit satellite position at the time of information transmission is iteratively calculated according to the low-orbit satellite orbit and the low-orbit satellite transmitter clock error, the ground receiver position information and the ground receiver clock error, and then the geometric distance between the low-orbit satellite and the ground monitoring station is calculated. In one embodiment, after calculating the geometric distance between the ground monitoring station and the low-orbit satellite, it is also necessary to make a line of sight judgment between the two. If the line of sight is met, the subsequent observation value simulation is performed, otherwise the next low-orbit satellite is switched for simulation, that is, the low-orbit satellite position at the time of information transmission is determined according to the next low-orbit satellite orbit and the low-orbit satellite transmitter clock error, as well as the ground monitoring station position information and the ground receiver clock error, and then the geometric distance between the ground monitoring station and the low-orbit satellite is calculated.

[0052] Furthermore, by superimposing the low-orbit satellite error, the second propagation error, and the ground receiver error on the geometric distance between the ground monitoring station and the low-orbit satellite, the ground low-orbit observation value can be obtained. In the simulation of ground low-orbit observation values, the low-orbit satellite error includes the low-orbit satellite PCO / PCV correction, pseudorange and carrier phase hardware delay, relativistic effect, and antenna phase winding, which are obtained in the same way as the simulation process of satellite-borne low-orbit observations. The second propagation error includes ionospheric delay and tropospheric delay, among which the ionospheric delay can be obtained through existing products or equipment, and the tropospheric delay can be obtained by S200 using historical data solution. The ground receiver error includes the ground receiver PCO / PCV correction, pseudorange and carrier phase hardware delay, solid tide, polar tide, and ocean load tide. The ground receiver error is also directly obtained through existing products and equipment or calculated through the corresponding theoretical model.

[0053] Specifically, the ground low orbit observation value includes the ground low orbit pseudorange observation value and the ground low orbit carrier phase observation value. The simulation formula is as follows: (6) in, represents the ground low-orbit pseudorange observation value, Represents the ground low-orbit carrier phase observation value, and the superscript leo refers to the low-orbit satellite. represents the geometric distance from the low-orbit satellite to the ground receiver, represents the ground receiver clock error, represents the clock error of the low-orbit satellite transmitter, represents the ionospheric delay from the ground receiver to the low-orbit satellite, represents the ground receiver pseudorange hardware delay, Indicates the pseudo-range hardware delay of the low-orbit satellite transmitter. represents the ambiguity from the low-orbit satellite to the ground receiver, represents the ground receiver phase hardware delay, Indicates the phase hardware delay of the low-orbit satellite transmitter. represents the frequency-dependent ionospheric delay amplification factor, Indicates frequency Corresponding carrier wavelength. During the simulation process, the position of the ground monitoring station adopts the celestial coordinates of the monitoring station provided by IGS or the a priori true coordinate value. Due to the cost constraints of the low-orbit satellite constellation, in this embodiment, the clock error of the low-orbit satellite transmitter is randomly selected from the ground receiver clock error set, wherein the ground receiver clock error set is generated by estimating different ground receiver clocks in advance. Combined with the tropospheric delay determined by S200, the zenith tropospheric dry delay and zenith tropospheric wet delay calculated by the Saastamoninen model are used, and the GMF projection function model is used to simulate the troposphere on the signal propagation path. For the ground receiver clock error, the ground receiver clock error of the required system can be determined by superimposing the deviation ISB between different systems through the ground receiver clock error obtained by S200. Assuming that there are two systems such as BDS and GPS, and the receiver clock error of BDS is used as the benchmark, the receiver clock error after adding the deviation is the receiver clock error of GPS.

[0054] For a more realistic reflection of the true characteristics of the observation, please continue to refer to Figure 3 , Figure 4, this embodiment also adds other errors based on the simulation of satellite-borne low-orbit observations and ground-based low-orbit observations. Other errors include adaptive noise and cycle slips. Specifically, the nature and characteristics of the noise depend on many factors, such as receiver type, environmental conditions, satellite geometry, etc. This embodiment mainly adds noise according to the type of low-orbit satellite receiver. Different types of receivers have different performances, and the corresponding added noise levels are also different. In practical applications, they can be adjusted according to demand. In one embodiment, the simulated pseudorange observations add a noise level of 1~3m, and the simulated carrier phase observations add a noise level of 6mm~12mm. Generally, the observations of one day are simulated, and the noise of different epochs is different, so a constant cannot be added. In order to increase the authenticity of the simulation data, a random number generator can be used to generate Gaussian distributed random numbers as the added noise level, where the probability density function of the Gaussian distribution can be expressed as: (7) in: is the probability density value at x, is the mean of the distribution, which is taken as 0, is the standard deviation of the distribution and is set according to the receiver type.

[0055] Because receiver performance and observation environments are different, the probability of a cycle slip is also different. In this embodiment, a cycle slip is added to the carrier phase observation value (including the satellite-borne low-orbit carrier phase observation value and the ground low-orbit phase observation value) according to the probability of a cycle slip. The probability of a cycle slip refers to the possibility of a cycle slip occurring on the satellite at the epoch. The probability of a cycle slip can be set in advance according to the environment, for example, it can be set to 0.1% in an open environment. In other embodiments, a cycle slip can also be added to the carrier phase observation value of a specific satellite at a specific epoch according to actual needs.

[0056] In order to meet the requirements of low-orbit satellite ground observation data simulation in complex environments, S400 is included on the basis of the above-mentioned observation value simulation, and the environmental error is grafted on the simulated ground low-orbit observation value to obtain the ground low-orbit observation data in complex environments. Please refer to Figure 5 First, various errors are extracted using precise single-point positioning, and then the environmental errors of the satellite are further solved. The semi-celestial model is used to model the environmental errors. Finally, the environmental errors are grafted and the environmental error effects are added to the simulated low-orbit satellite observation data.

[0057] Specifically, the embodiment of the present application first uses a non-differenced non-combined precise single point positioning model to calculate various errors in the transmission path such as the troposphere, ionosphere, and ground receiver clock error, and then deducts various errors from the GNSS satellite observation data to obtain the environmental error. The various errors are deducted as follows: (8) in, are other errors that can be corrected, pseudorange environmental errors It also includes receiver hardware delay, pseudorange measurement noise, carrier environment error, etc. It includes carrier phase hardware delay, carrier observation value noise, etc. represents pseudorange observation data, represents the phase observation data, Represents the geometric distance from the GNSS satellite to the ground receiver, represents the ground receiver clock error, represents the GNSS satellite clock error, represents the ionospheric delay, represents the tropospheric delay, Indicates the GNSS satellite pseudorange hardware delay, Indicates the GNSS satellite phase hardware delay, represents the fuzziness parameter, represents the frequency-dependent ionospheric delay amplification factor, Indicates frequency The corresponding carrier wavelength.

[0058] While obtaining the environmental error, the altitude and azimuth of each GNSS satellite are calculated based on the GNSS satellite position and the coordinates of the ground monitoring station for subsequent error grafting.

[0059] After obtaining the environmental error, it is necessary to perform environmental error modeling and generate an environmental error correction table. In this embodiment, environmental error modeling is performed based on a semi-celestial model. Specifically, the azimuth Range 0°~360° and altitude angle The celestial sphere area ranging from 0° to 90° is divided into multiple grids. For each grid, the GNSS satellite environmental error passing through the grid is solved by the bilinear interpolation method to solve the parameters of each grid point, and finally the environmental error correction tables of pseudorange and carrier phase are established respectively, as follows: (9) in, To establish the environmental error correction table, represents the altitude angle, represents the azimuth, , , and Both represent the values ​​of the endpoints of the grid. Indicates that the altitude angle is The azimuth is The environmental error.

[0060] At this time, the obtained environmental error correction table can be used to graft the ground low-orbit observation values ​​obtained by S300. The ground low-orbit observation data under complex environment after grafting is expressed as follows: (10) in, is the ground low-orbit pseudorange observation value in complex environment, is the ground low-orbit carrier phase observation value in a complex environment, and Altitude angle , azimuth The environmental errors of pseudorange and carrier phase.

[0061] The low-orbit observation data obtained by the simulation method proposed in this application can better reflect the actual situation. At the same time, cycle slips can be added according to different scenarios, and corresponding noise can be added according to the performance of the low-orbit satellite receiver. Using the real ground receiver clock error instead of the fitted low-orbit satellite receiver clock error can better reflect the performance of the low-orbit satellite receiver clock. The observation data is also processed by environmental error grafting to obtain low-orbit ground observation data in complex environments.

[0062] The embodiment of the present application also provides a system, including: a position information acquisition module, which is used to obtain the orbit and position information of the low-orbit satellite; an error solution module, which performs precise single-point positioning solution on the low-orbit satellite based on historical data and determines the error in the transmission path; an observation value simulation module, which performs satellite-borne low-orbit observation value simulation and ground-based low-orbit observation value simulation based on the low-orbit satellite orbit and position information and the error in the transmission path; wherein custom noise and cycle slips are added to the satellite-borne low-orbit observation value and the ground-based low-orbit observation value. The specific functions implemented by each module can be found in the aforementioned description of the low-orbit satellite observation data simulation method, which will not be repeated here.

[0063] Reference Figure 6 As shown, an electronic device 500 according to an embodiment of the present application includes: a memory 501 and a processor 502, wherein the memory 501 stores a computer program corresponding to the aforementioned low-orbit satellite observation data simulation method that can be loaded and executed by the processor 502.

[0064] Figure 7 A schematic diagram of the structure of a computer system suitable for implementing a receiving system of an embodiment of the present application is shown.

[0065] It should be noted that Figure 7 The computer system 600 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0066] like Figure 7As shown, the computer system 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 602 or the program loaded from the storage part 608 to the random access memory (RAM) 603, such as executing the method described in the above embodiment. In the RAM 603, various programs and data required for system operation are also stored. The CPU 601, the ROM 602 and the RAM 603 are connected to each other through the bus 604. The input / output (I / O) interface 605 is also connected to the bus 604.

[0067] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, etc.; an output section 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed so that a computer program read therefrom is installed into the storage section 608 as needed.

[0068] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication part 609, and / or installed from a removable medium 611. When the computer program is executed by a central processing unit (CPU) 601, various functions defined in the system of the present application are executed.

[0069] It should be noted that the computer-readable medium shown in the embodiment of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate, or transmit programs for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0070] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. Among them, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the above-mentioned module, a program segment or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0071] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0072] As another aspect, the present application also provides a computer program product or a computer program, which includes a computer instruction stored in a computer-readable storage medium. A processor of a computer device reads the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the computer device executes the communication-based method described in the above embodiment.

[0073] As another aspect, the present application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements the communication method described in the above embodiment.

[0074] It should be noted that, although several modules or units of the equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0075] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software, or by combining software with necessary hardware. Therefore, the technical solution according to the implementation method of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes a number of instructions to enable a computing device (which can be a personal computer, a server, a touch terminal or a network device, etc.) to execute the method according to the implementation method of the present application.

[0076] For those skilled in the art, the specific meanings of the above terms in the present invention can be understood in specific situations; the drawings in the embodiments are used to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0077] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for simulating low-orbit satellite observation data, characterized in that: include: Obtain low-orbit satellite orbit and position information; Perform precise point positioning calculations on GNSS satellites based on historical data to determine errors in the transmission path; Based on the LEO satellite orbit and position information and the error in the transmission path, a simulation of onboard LEO observation values ​​and a simulation of ground-based LEO observation values ​​are performed; Wherein, noise and cycle slips are added to the satellite-borne low-orbit observation values ​​and the ground-based low-orbit observation values.

2. The low-orbit satellite observation data simulation method according to claim 1, characterized in that: Also includes: The environmental errors are grafted onto the ground low-orbit observation values ​​obtained by simulation to obtain the ground low-orbit observation data in complex environments.

3. The low-orbit satellite observation data simulation method according to claim 1 or 2, characterized in that: The obtaining of low-orbit satellite orbit and position information specifically includes: Based on the initial parameters and dynamic model of the low-orbit satellite constellation, the orbit and position information of the low-orbit satellite are obtained.

4. The low-orbit satellite observation data simulation method according to claim 1, characterized in that: The historical data includes GNSS satellite observation data during a low-orbit satellite observation period.

5. The low-orbit satellite observation data simulation method according to claim 1, characterized in that: The errors in the transmission path include tropospheric delay and ground receiver clock error.

6. The low-orbit satellite observation data simulation method according to claim 1, characterized in that: The satellite-borne low-orbit observation value simulation includes: Determine the GNSS satellite position at the time of information transmission based on the low-orbit satellite position information and corresponding clock error, the GNSS satellite orbit and corresponding clock error; Calculate the geometric distance between GNSS satellites and low-orbit satellites; The GNSS satellite error, the first propagation error and the low-orbit satellite error are superimposed on the geometric distance between the GNSS satellite and the low-orbit satellite to obtain the satellite-borne low-orbit observation value; wherein the satellite-borne low-orbit observation value includes the satellite-borne low-orbit pseudorange observation value and the satellite-borne low-orbit carrier phase observation value.

7. The method for simulating low-orbit satellite observation data according to claim 6, characterized in that: After calculating the geometric distance between the GNSS satellite and the low-orbit satellite, it also includes judging the line of sight between the GNSS satellite and the low-orbit satellite.

8. The low-orbit satellite observation data simulation method according to claim 1, characterized in that: The ground low orbit observation value simulation includes: Based on the LEO satellite orbit and corresponding clock error, the ground monitoring station location information and the ground receiver clock error, determine the LEO satellite position at the time of information transmission; Calculate the geometric distance between low-orbit satellites and ground monitoring stations; The low-orbit satellite error, the second propagation error and the ground receiver error are superimposed on the geometric distance between the low-orbit satellite and the ground monitoring station to obtain the ground low-orbit observation value; among which, the ground low-orbit observation value includes the ground low-orbit pseudorange observation value and the ground low-orbit carrier phase observation value.

9. The method for simulating low-orbit satellite observation data according to claim 8, characterized in that: The second propagation error includes ionospheric delay and tropospheric delay.

10. The low-orbit satellite observation data simulation method according to claim 8 or 9, characterized in that: After calculating the geometric distance between the low-orbit satellite and the ground monitoring station, it also includes judging the line of sight between the low-orbit satellite and the ground monitoring station.

11. The low-orbit satellite observation data simulation method according to claim 6 or 8, characterized in that: The clock error of the low-orbit satellite is represented by the pre-estimated clock error of the ground receiver.

12. The method for simulating low-orbit satellite observation data according to claim 1, characterized in that: Also includes: Noise is added to the satellite-borne LEO observations and ground-based LEO observations according to the LEO receiver type.

13. The method for simulating low-orbit satellite observation data according to claim 1, characterized in that: The noise is determined by a Gaussian distributed random number generated by a random number generator.

14. The method for simulating low-orbit satellite observation data according to claim 1, characterized in that: The method also includes adding a cycle slip to a satellite-borne low-orbit carrier phase observation value and a ground-based low-orbit phase observation value according to a probability of a cycle slip occurring; the probability of a cycle slip occurring is pre-set according to the environment.

15. The method for simulating low-orbit satellite observation data according to claim 2, characterized in that: The step of grafting environmental errors on the basis of the simulated ground low-orbit observation values ​​to obtain ground low-orbit observation data in a complex environment specifically includes: Extract environmental errors; Environmental error modeling is performed based on the semi-spherical model to generate an environmental error correction table; The corresponding environmental errors are grafted onto the ground-based low-orbit observation values ​​through the environmental error correction table to obtain the ground-based low-orbit observation data in complex environments.

16. The method for simulating low-orbit satellite observation data according to claim 15, characterized in that: The environmental error is obtained by solving the GNSS satellite observation data.

17. A system, characterized in that: include: Position information acquisition module, used to obtain low-orbit satellite orbit and position information; The error calculation module performs precise single-point positioning calculations on GNSS satellites based on historical data to determine the errors in the transmission path; The observation value simulation module performs on-board low-orbit observation value simulation and ground-based low-orbit observation value simulation based on the low-orbit satellite orbit and position information and the error in the transmission path; wherein noise and cycle slips are added to the on-board low-orbit observation value and the ground-based low-orbit observation value.

18. An electronic device, characterized in that: It includes a memory and a processor, wherein the memory stores a computer program corresponding to the low-orbit satellite observation data simulation method as described in any one of claims 1 to 16, which can be loaded and executed by the processor.

19. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the program instructions are executed by the processor, they are used to implement the process corresponding to the low-orbit satellite observation data simulation method described in any one of claims 1 to 16.

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