Observed value simulation and positioning method of low earth orbit satellite fused GNSS multi-error model

Abstract

The invention relates to the technical field of satellite navigation and positioning, in particular to an observed value simulation and positioning method for a low-orbit satellite fused with a GNSS (Global Navigation Satellite System) multi-error model, which comprises the following steps of: establishing a low-orbit satellite by utilizing STK, establishing a Walker constellation by taking the satellite as a seed satellite, adding satellites in a TLE data format, and establishing a GNSS (Global Navigation Satellite System) (GPS / BDS) constellation; outputting the position and the speed of each satellite through an STK report function, and taking the position and the speed as an orbit file; adding a required GNSS precision product file and each error model, calculating a satellite-ground distance and each error information, and establishing a pseudo-range and carrier phase simulation observation value; and finally, iteration and positioning are carried out through least square and Kalman filtering, and ionosphere-free combination rapid convergence high-precision positioning is realized. According to the method, the convergence time is shortened to be within 1 minute from traditional 30 minutes, and the positioning availability is improved to be more than 90% in a complex environment.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of satellite navigation and positioning, and particularly relates to a low-orbit satellite fusion GNSS multi-error model observation value simulation and positioning method. BACKGROUND

[0002] The main function of a global navigation satellite system (GNSS) is to provide continuous, stable and reliable positioning, navigation and timing functions for various users. Precise point positioning (PPP) technology uses carrier phase and pseudorange observations of a global navigation satellite system through a single receiver, combined with high-precision satellite orbit and clock error products, to achieve centimeter-level positioning accuracy.

[0003] However, the traditional PPP technology has always been faced with the problem of long convergence time, which is mainly limited by the difficulty in ambiguity parameter estimation and the slow convergence of various error parameters, and it takes more than 30 minutes to achieve stable high precision. Moreover, in the bridge, city and canyon environments that are easy to block, effective positioning cannot even be completed, which is difficult to meet the real-time application requirements. With the development of low-orbit satellites, their application potential in precise point positioning has been increasingly concerned. The low-orbit satellite has a fast rate of geometric configuration change, and its orbit period is generally 90-120 minutes. Its high-speed movement significantly speeds up the ambiguity fixing and convergence process. In addition, the low-orbit satellite is relatively close to the ground, and the signal transmission distance is short, so the signal strength is stronger than that of the medium-orbit GNSS satellite, which can improve the signal availability in complex environments such as cities and canyons. SUMMARY

[0004] The purpose of the application is to provide a low-orbit satellite fusion GNSS multi-error model observation value simulation and positioning method. Based on the LEO constellation orbit data simulated by STK and the real GNSS precise products, a platform for multi-error simulation and positioning accuracy analysis is constructed to assist the GNSS system in positioning, so as to improve the convergence time and positioning accuracy.

[0005] To achieve the above purpose, the application provides a low-orbit satellite fusion GNSS multi-error model observation value simulation and positioning method, which comprises the following steps:

[0006] Step 1: using STK software to set a low-orbit satellite constellation with an orbital height of 500-1200 kilometers, setting a seed satellite through six orbital elements, and generating a complete low-orbit satellite constellation based on Walker constellation parameters T / P / F, and then exporting the orbital data of each low-orbit satellite by using the STK orbital parameter report generation function;

[0007] Step 2: Download and import GNSS precise products required for positioning from IGS data center, including satellite clock error files, antenna phase center offset and phase center variation files, systematic phase bias products, and import low-orbit satellite orbit data simulated in step 1, including 30-second interval satellite position and velocity;

[0008] Step 3: Calculate the real satellite-geodetic distance, including the geometric distance from satellite center of mass coordinates to the reference point of the receiver antenna, antenna phase center correction, and displacement correction caused by the earth's solid tide, to obtain the corrected real satellite-geodetic distance;

[0009] Step 4: Calculate the error in the propagation process, including satellite clock delay, receiver clock delay, ionospheric delay, tropospheric delay, and relativistic effect delay, wherein the ionospheric delay is calculated using a spherical harmonic function model, the tropospheric delay is realized by a dry-wet component mapping function, and the relativistic effect adopts a Shapiro delay model;

[0010] Step 5: Combine the real satellite-geodetic distance with the error calculated in step 4 to generate dual-frequency pseudo-range and carrier phase simulation observations through a non-difference non-combination model, wherein the integer part of the ambiguity is generated as a random integer, the decimal part is obtained through the systematic phase bias product, and the observation noise adopts a normal distribution model;

[0011] Step 6: Use the simulation observations to perform positioning solution using ionosphere-free combination;

[0012] Step 7: Use MW combination method to detect and repair cycle slip, then use least squares method to obtain initial position estimate, and combine Kalman filter to perform low-orbit satellite enhanced GNSS positioning solution for high-precision positioning solution.

[0013] Optionally, download satellite TLE data in the satellite data website, and import all satellites of the GNSS system into STK through TLE data.

[0014] Optionally, in the process of exporting low-orbit satellite orbit data, use the report function in STK software to output the "X", "Y", "Z" coordinate positions and corresponding velocities of each satellite in the Earth-Centered Earth-Fixed coordinate system at 30-second intervals, a total of 2880 epochs, i.e. 24 hours.

[0015] Optionally, the real satellite-geodetic distance is calculated from the satellite center of mass coordinates to the reference point of the receiver antenna, the unit vector in the receiver-to-satellite line-of-sight direction, the corresponding antenna phase center offset and phase center variation files at the satellite end and the receiver end, and the earth tide displacement correction.

[0016] Optionally, the positioning solution process uses an ionosphere-free combination model to calculate each item of raw data observations.

[0017] The application provides a low-orbit satellite fusion GNSS multi-error model observation value simulation and positioning method, a low-orbit satellite is established by using STK, a Walker constellation is established by taking the satellite as a seed satellite, and the GNSS (GPS / BDS) constellation is created by adding satellites in TLE data format; the position and speed of each satellite are output as orbit files by using the STK report function; the required GNSS precise product files and error models are added, the satellite-Earth distance and error information are calculated, and the pseudo-range and carrier phase simulation observation values are established; finally, the least square and Kalman filtering are used for iteration and positioning, so that the fast convergence high-precision positioning of the ionosphere-free combination is realized. The method shortens the convergence time from 30 minutes of the traditional method to less than 1 minute, and improves the positioning availability to more than 90% in a complex environment. The low-orbit constellation data generated by STK is combined with the real GNSS precise product for the first time, and a comprehensive multi-error simulation and positioning precision analysis platform is constructed. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, a brief introduction will be given to the drawings needed in the embodiments or prior art description. Obviously, the drawings in the following description only show some embodiments of the present application.

[0019] Figure 1 FIG. 1 is a flowchart of a low-orbit satellite fusion GNSS multi-error model observation value simulation and positioning method according to the present application.

[0020] Figure 2 FIG. 2 is a positioning result comparison diagram of simulation observation values and real observation values in a specific embodiment of the present application. DETAILED DESCRIPTION

[0021] The embodiments of the present application will be described in detail below, and examples of the embodiments are shown in the drawings, wherein the same or similar reference signs represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and are intended to explain the present application, and cannot be understood as a limitation of the present application.

[0022] The application provides a low-orbit satellite fusion GNSS multi-error model observation value simulation and positioning method, which comprises the following steps:

[0023] Step 1: a low-orbit satellite constellation with an orbital height of 500-1200 kilometers is set by using the STK software, a seed satellite is set by using the orbital six-element, and a complete low-orbit constellation is generated based on the Walker constellation parameters T / P / F, and then the orbit data of each low-orbit satellite is exported by using the STK orbit parameter report generation function;

[0024] Step 2: Download and import GNSS precise products required for positioning from IGS data center, including satellite clock error file, antenna phase center offset and phase center variation file, systematic phase bias product, and import low earth orbit satellite orbit data simulated in step 1, including 30-second interval satellite position and velocity;

[0025] Step 3: Calculate the real satellite-geodetic distance, including the geometric distance from the satellite center of mass coordinates to the station receiver antenna reference point, antenna phase center correction, and displacement correction caused by the earth solid tide, to obtain the corrected real satellite-geodetic distance;

[0026] Step 4: Calculate the error in the propagation process, including satellite clock delay, receiver clock delay, ionospheric delay, tropospheric delay, and relativistic effect delay, wherein the ionospheric delay is calculated using a spherical harmonic function model, the tropospheric delay is achieved by a wet and dry component mapping function, and the relativistic effect adopts a Shapiro delay model;

[0027] Step 5: Combine the real satellite-geodetic distance with the error calculated in step 4 to generate dual-frequency pseudo-range and carrier phase simulation observations through a non-difference non-combination model, wherein the integer part of the ambiguity is generated as a random integer, the decimal part is obtained through the systematic phase bias product, and the observation noise adopts a normal distribution model;

[0028] Step 6: Use the simulation observation values to perform positioning solution using ionosphere-free combination;

[0029] Step 7: Use MW combination method to detect and repair cycle slip, and then use least squares method to obtain initial position estimate, and combine Kalman filter to perform low earth orbit satellite enhanced GNSS positioning solution for high-precision positioning solution.

[0030] As Figure 1 The flowchart of the low earth orbit satellite integrated GNSS multi-error model observation simulation and positioning method is shown, and the specific idea is to calculate the low earth orbit satellite simulation observation value, and to perform GNSS enhanced positioning analysis, which will be further described in combination with specific embodiments and execution steps:

[0031] Step 1: Use STK software to simulate low earth orbit satellite constellation and low earth orbit satellite orbit data.

[0032] In the STK software, the seed satellite of the required simulation low earth orbit satellite constellation is established by setting six orbit parameters of orbit semi-major axis, orbit eccentricity, orbit inclination, ascending node longitude, perigee amplitude and mean anomaly, and the Walker low earth orbit satellite constellation is generated by setting three parameters T / P / F.

[0033] Where, T is the total number of satellites in the constellation, P is the number of orbital planes, F is the phase factor of adjacent orbital plane satellites, according to The included angle of satellites on adjacent orbits can be determined.

[0034] The "X", "Y", "Z" coordinates of each satellite in the constellation in the Earth-Centered Earth-Fixed coordinate system and the corresponding time in year, month, day, hour, minute and second are exported by using the report generation function of the STK software at a time interval of 30s.

[0035] Step 2: Import the GNSS precise products required for positioning and simulated low-orbit satellite orbit data.

[0036] Wherein, the satellite clock error files and antenna correction files of GPS and BDS are real files; the low-orbit satellite clock error uses the GPS satellite clock error file, and an additional noise term related to the orbital height is added; the receiver clock error is obtained according to the GPS positioning result.

[0037] Table 1 GNSS precise products

[0038] Real data Data files Satellite antenna PCO and PCV data ANTEX files (.atx) Satellite clock error data IGS precise clock error files (.clk) Systematic phase bias data UPD products (.bias)

[0039] PCO: antenna phase center offset; PCV: file phase center variation; UPD: systematic phase bias product.

[0040] Step 3: Calculate the real distance between the low-orbit satellite center-of-mass coordinates generated by the report and the receiver position coordinates:

[0041]

[0042] Wherein, ρ represents the real distance between the satellite and the earth; is the unit vector in the direction of the line of sight from the receiver to the satellite; o s and o r respectively represent the coordinates of the satellite center-of-mass and the coordinates of the antenna reference point of the station receiver; and are the satellite end antenna PCO and PCV; d r,pco and d r,pcv are the receiver end PCO and PCV; d r,disp is the correction for the displacement of the earth's solid tide delay.

[0043] The ranging path error caused by the solid tide can be expressed as:

[0044]

[0045] Wherein, Δr tide is the crust displacement vector caused by the solid tide.

[0046] Step 4: Calculate the error in the propagation process, including satellite clock delay, receiver clock delay, ionospheric delay, tropospheric delay and relativistic effect delay, etc.

[0047] (1) Satellite clock delay t s and receiver clock delay t r : Directly obtained from the imported clock difference file;

[0048] (2) Ionospheric error The spherical harmonic function model is used to establish the ionospheric delay error model, and the specific expression is as follows:

[0049]

[0050] θ = λ - λ0 (4)

[0051]

[0052] In the formula, m max is the maximum expansion order; m represents the expansion order; is the Legendre function of m order k times after complete normalization; θ is the fixed longitude of the puncture point; λ0 is the solar longitude; A mk , B mk are the model parameters to be solved; λ, is the longitude and latitude of the puncture point; R E is the radius of the earth; H ion is the height of the ionospheric single-layer model; E is the satellite elevation angle (unit: radian);

[0053] (3) Tropospheric delay The total tropospheric delay when the elevation angle is E is obtained by multiplying the dry delay by the dry delay projection function and adding the wet delay by the wet delay projection function:

[0054]

[0055] Wherein, is the total tropospheric delay when the elevation angle is E; m h , m w are the dry and wet component mapping functions; ZHD is the zenith dry delay; ZWD is the zenith wet delay.

[0056] (4) Relativistic effect model δt: Shapiro delay model is adopted:

[0057]

[0058] Wherein, G is the gravitational constant; M is the mass of the earth; c is the speed of light; r s is the distance from the satellite to the center of the earth; r r is the distance from the receiver to the center of the earth; R srEuclidean distance from satellite to receiver.

[0059] (5) The integer part of ambiguity is generated by random integer, and the decimal part is simulated by UPD.

[0060] (6) The phase and pseudorange noise are both Gaussian noise.

[0061] Step 5: Combine the calculated real satellite-geodetic distance with the relevant errors to generate simulated pseudorange observations and carrier phase observations:

[0062]

[0063] In the formula, P and L are respectively the pseudorange observation and carrier phase observation of the simulated low-orbit satellite, and λ is the wavelength; N is the ambiguity; are respectively the pseudorange observation noise and carrier phase observation noise; is the ionospheric delay coefficient, and f is the frequency of the satellite signal.

[0064] Step 6: Use the simulated low-orbit satellite observations to perform positioning calculation using the ionosphere-free combination.

[0065]

[0066] In the formula, P IF and L IF are respectively the pseudorange and carrier phase observations of the ionosphere-free combination; f1 and f2 are two carrier frequencies; P1 and P2 are respectively the pseudorange observations at the two frequencies; and L1 and L2 are respectively the carrier phase observations at the two frequencies. This combination eliminates the first-order ionospheric delay effect.

[0067] Step 7: Use the Melbourne-Wübbena (MW) combination method to detect and repair cycle slips:

[0068]

[0069] Then use the least squares method to determine the initial iteration value of the station, and linearize the observation equation as:

[0070]

[0071] The positioning is completed by iteration through the Kalman filter method. The state quantity of the Kalman filter is set as:

[0072] X = [x, y, z, t r , N1, N2,..., N n ] T (15)

[0073] In the formula, x, y, and z are the three-dimensional coordinates of the receiver, and N1 to N nthe ambiguity parameters of each satellite.

[0074] The dynamic model is set as:

[0075] X k = Φ k,k-1 · X k-1 + w k (16)

[0076] wherein Φ k,k-1 is a state transition matrix, w k is a process noise, and the covariance matrix is Q k .

[0077] The measurement model is set as:

[0078] Z k = H k · X k + v k (17)

[0079] wherein H k is a design matrix, v k is an observation noise, and the covariance matrix is R k .

[0080] The following time update and measurement update iterations are used for solving:

[0081] Time update:

[0082]

[0083] Measurement update:

[0084]

[0085] wherein K k is a Kalman gain matrix, and P k is a state covariance matrix.

[0086] To analyze the accuracy of the present application, the GPS satellite constellation is simulated by using the STK software, and the pseudorange observation value and the carrier phase observation value are simulated according to the implementation steps of the method of the present application, and the positioning is solved by using the ionosphere-free combination. The solving result is compared with the positioning result of the real pseudorange observation value and the carrier phase observation value of the GPS system. As shown in Figure 2 , the result shows that the PPP convergence time is shortened from 30 minutes of the traditional GNSS to 1 minute, and the positioning availability is improved to more than 90% under complex environment.

[0087] The above disclosure only shows one or more preferred embodiments of the present application, of course, cannot limit the scope of the present application, those skilled in the art can understand that the implementation of all or part of the above processes, and the equivalent changes made by the present application claims, still belong to the scope covered by the present application.

Claims

1. A method for simulating and locating observations from a low-Earth orbit satellite fusion GNSS multi-error model, characterized in that, Includes the following steps: Step 1: Use STK software to set up a low Earth orbit (LEO) satellite constellation with an orbital altitude of 500-1200 km, set up seed satellites using the six orbital elements, and generate a complete LEO constellation based on Walker constellation parameters T / P / F. Then, use the STK orbital parameter report generation function to export the orbital data of each LEO satellite. Step 2: Download and import the GNSS precision products required for positioning from the IGS data center, including satellite clock bias files, antenna phase center offset and phase center change files, systematic phase deviation products, and import the low-Earth orbit satellite orbit data simulated in Step 1, including satellite position and velocity at 30-second intervals. Step 3: Calculate the true satellite-to-Earth distance, including the geometric distance from the satellite's centroid coordinates to the station's receiver antenna reference point, antenna phase center correction, and displacement correction caused by Earth's solid tides, to obtain the corrected true satellite-to-Earth distance; Step 4: Calculate the errors in the propagation process, including satellite clock delay, receiver clock delay, ionospheric delay, tropospheric delay, and relativistic delay. The ionospheric delay is calculated using the spherical harmonic function model, the tropospheric delay is realized through the dry and wet component mapping function, and the relativistic delay is calculated using the Shapiro delay model. Step 5: Combine the actual satellite-to-ground distance with the error calculated in Step 4, and generate simulated observations of dual-frequency pseudorange and carrier phase using a non-difference, non-combination model. The integer part of the ambiguity is generated as a random integer, and the fractional part is obtained through a systematic phase deviation product. The observation noise adopts a normal distribution model. Step 6: Using the simulated observations, perform location calculations using an ionosphere-free combination; Step 7: Use the MW combination method to detect and repair cycle slips, then use the least squares method to obtain the initial position estimate, and combine it with Kalman filtering to perform high-precision positioning calculation for low-orbit satellite-enhanced GNSS positioning.

2. The observation simulation and positioning method of the low-orbit satellite fusion GNSS multi-error model as described in claim 1, characterized in that, Download satellite TLE data from the satellite data website, and import all satellites of the GNSS system into STK using the TLE data.

3. The observation simulation and positioning method of the low-orbit satellite fusion GNSS multi-error model as described in claim 1, characterized in that, During the export of low-Earth orbit satellite orbit data, the report function in STK software is used to output the "X", "Y", and "Z" coordinate positions and corresponding velocities of each satellite in the geocentric-geostatic coordinate system at 30-second intervals for a total of 2880 epochs, or 24 hours.

4. The observation simulation and positioning method of the low-orbit satellite fusion GNSS multi-error model as described in claim 1, characterized in that, The true distance between the satellite and the Earth is calculated from the spatial geometric distance from the satellite's centroid coordinates to the reference point of the receiver antenna at the station, the unit vector of the line of sight from the receiver to the satellite, the corresponding antenna phase center offset and phase center change files at the satellite and receiver ends, and the Earth's tidal displacement correction.

5. The observation simulation and positioning method for the low-orbit satellite fusion GNSS multi-error model as described in claim 1, characterized in that, The location calculation process uses an ionosphere-free combined model to calculate various raw data observations.

Images