Method and device for acquiring state parameters of high-orbit and low-orbit constellation combined precise point positioning

Abstract

The invention provides a method and a device for acquiring state parameters of high-orbit and low-orbit constellation joint precision point positioning, and relates to the technical field of satellite navigation. Obtaining observation data based on high and low orbit combined satellite constellation parameters, receiver position parameters and epoch moments; preprocessing the observation data to obtain target observation data generated after preprocessing, and carrying out high and low orbit constellation joint standard single-point positioning solution based on the target observation data to obtain a single-point positioning solution; and performing state estimation and ambiguity fixation by taking the single-point positioning solution as an iterative initial value of Kalman filtering to obtain state parameters.

Description

Technical Field

[0001] The present application relates to the field of satellite navigation technology, and in particular to a method and device for acquiring state parameters of high-orbit and low-orbit constellation joint precise single-point positioning. Background Art

[0002] Joint positioning of high-orbit and low-orbit constellations refers to the integration of the high-orbit Global Navigation Satellite System (GNSS) constellation and the low-orbit satellite constellation, combining the large amount of observations brought by the advantage of the number of low-orbit satellites and the advantage of the wide airspace coverage of high-orbit satellites to provide enhanced positioning services. This method has gradually become a new development direction of ground terminal positioning technology.

[0003] In the related technology, the focus is on the error values ​​on the satellite side and the propagation path, and the differences in different scenarios are reflected by the size and weighting of the error values. However, the characteristics of low-orbit constellations and the actual scenarios of user receivers are not fully considered, and there is a lack of methods for obtaining the state parameters of low-orbit constellation enhanced GNSS precise single-point positioning. Summary of the invention

[0004] The present application aims to solve one of the technical problems in the related art at least to some extent.

[0005] To this end, one purpose of the present application is to propose a method for obtaining state parameters of high- and low-orbit constellation joint precise single-point positioning, by obtaining high- and low-orbit joint satellite constellation parameters, receiver position parameters and epoch time, and obtaining observation data based on the high- and low-orbit joint satellite constellation parameters, receiver position parameters and epoch time; preprocessing the observation data to obtain target observation data generated after preprocessing, and performing high- and low-orbit constellation joint standard single-point positioning solution based on the target observation data to obtain a single-point positioning solution; using the single-point positioning solution as the iterative initial value of the Kalman filter to perform state estimation and ambiguity fixation to obtain state parameters.

[0006] The second objective of the present application is to propose a device for acquiring state parameters of high-orbit and low-orbit constellation joint precise point positioning.

[0007] The third objective of the present application is to provide an electronic device.

[0008] A fourth object of the present application is to provide a non-transitory computer-readable storage medium.

[0009] A fifth object of the present application is to provide a computer program product.

[0010] To achieve the above-mentioned purpose, the first aspect embodiment of the present application proposes a method for obtaining state parameters of high- and low-orbit constellation joint precise single-point positioning, by obtaining high- and low-orbit joint satellite constellation parameters, receiver position parameters and epoch time, and obtaining observation data based on the high- and low-orbit joint satellite constellation parameters, receiver position parameters and epoch time; preprocessing the observation data to obtain the target observation data generated after the preprocessing, and performing high- and low-orbit constellation joint standard single-point positioning solution based on the target observation data to obtain a single-point positioning solution; using the single-point positioning solution as the iterative initial value of the Kalman filter to perform state estimation and ambiguity fixation to obtain state parameters.

[0011] According to one embodiment of the present application, obtaining observation data includes: obtaining the satellite positions of each satellite constellation and determining the satellite orbit based on the satellite positions; obtaining the earth rotation effect error and the relativistic effect error, and performing data correction based on the earth rotation effect error and the relativistic effect error; calculating the geometric distance from the satellite to the receiver, calculating the satellite error, and correcting the geometric distance; obtaining pseudorange measurement noise, and combining the result of the error calculation and the corrected geometric distance to generate a pseudorange observation value according to the pseudorange observation equation; obtaining carrier phase measurement noise, and performing carrier phase integer ambiguity calculation and carrier phase cycle slip calculation, and combining the result of the error calculation and the corrected geometric distance to generate a carrier phase observation value according to the carrier phase observation equation; generating observation data based on the pseudorange observation value and the carrier phase observation value.

[0012] According to one embodiment of the present application, the calculation formula of the carrier phase integer ambiguity is:

[0013] N i =-m*L i +S t

[0014] Where N i is the integer ambiguity, m = 10 8 , S t is the cycle slip, S t is an integer, L i is a frequency-dependent integer constant.

[0015] According to one embodiment of the present application, in the calculation of satellite errors, the satellite errors include: clock error, ionospheric delay error, tropospheric delay error, antenna phase center error, antenna phase winding error, earth solid tide error and ocean tide error.

[0016] According to one embodiment of the present application, a single-point positioning solution is used as an iterative initial value of a Kalman filter to perform state estimation and fix the ambiguity to obtain state parameters, including: using the single-point positioning solution as an iterative initial value of a Kalman filter to perform state estimation to obtain a real positioning solution; based on the real positioning solution, fixing the positioning ambiguity to obtain an integer ambiguity solution; substituting the integer ambiguity solution into the observation equation to obtain a solution for related parameters.

[0017] According to one embodiment of the present application, the observation data is preprocessed to obtain target observation data generated after the preprocessing, including: performing clock jump detection and repair on the observation data; performing gross error detection and cycle slip detection on the observation data after the clock jump detection and repair to obtain the target observation data generated after the preprocessing.

[0018] According to an embodiment of the present application, a high-orbit combined standard single-point positioning solution is performed based on the target observation data to obtain a single-point positioning solution, including: performing a standard single-point positioning solution based on the pseudo-range observation value in the target observation data combined with the pseudo-range observation equation group, and the pseudo-range observation equation corresponding to each satellite is as follows:

[0019] P=ρ+cδt s -cδt r +I+T+ε p

[0020] Where P is the pseudorange observation value, ρ is the geometric distance between the satellite and the receiver, c is the speed of light, and δt s is the satellite clock error, δt r is the receiver clock error, I is the ionospheric delay error, T is the tropospheric delay error, ε p is the pseudorange observation noise.

[0021] According to one embodiment of the present application, after obtaining the state parameters, it also includes: performing performance evaluation of high-orbit and low-orbit constellation joint precise single-point positioning based on the state parameters.

[0022] To achieve the above-mentioned purpose, the second embodiment of the present application proposes a device for acquiring state parameters of high- and low-orbit constellation joint precise single-point positioning, including: a data acquisition module, used to acquire high- and low-orbit joint satellite constellation parameters, receiver position parameters and epoch time, and acquire observation data based on the high- and low-orbit joint satellite constellation parameters, receiver position parameters and epoch time; a positioning solution module, used to preprocess the observation data, obtain the target observation data generated after the preprocessing, and perform high- and low-orbit constellation joint standard single-point positioning solution based on the target observation data to obtain a single-point positioning solution; a state estimation module, used to use the single-point positioning solution as the iterative initial value of the Kalman filter to perform state estimation and fix the ambiguity, and obtain state parameters.

[0023] To achieve the above-mentioned purpose, the third aspect embodiment of the present application proposes an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to implement the method for obtaining state parameters of joint precise single-point positioning of high-orbit and low-orbit constellations as described in the first aspect embodiment of the present application.

[0024] To achieve the above-mentioned purpose, the fourth aspect embodiment of the present application proposes a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to implement the method for obtaining state parameters of the joint precise single-point positioning of high- and low-orbit constellations as described in the first aspect embodiment of the present application.

[0025] To achieve the above-mentioned objectives, the fifth aspect embodiment of the present application proposes a computer program product, including a computer program, which, when executed by a processor, implements the method for obtaining state parameters of the joint precise single-point positioning of high- and low-orbit constellations as described in the first aspect embodiment of the present application.

[0026] The present application achieves at least the following beneficial effects: The embodiment of the present application comprehensively considers the satellite side, propagation path, and multiple errors on the user receiver side as well as the characteristics of the low-orbit constellation to obtain observation data, and then combines the low-orbit / high-orbit observation data for precise single-point positioning. When obtaining the observation data, the influence of the orbit error on the satellite side and different scenarios on the receiver side are taken into account, while the influence of the characteristics of the low-orbit constellation such as configuration and quantity is taken into account, so that the state parameters of the low-orbit constellation combined with GNSS precise single-point positioning in different user receiver scenarios can be accurately obtained. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0028] Figure 1 It is a schematic diagram of an exemplary implementation of a method for acquiring state parameters of high-orbit and low-orbit constellation joint precise single-point positioning, shown in an embodiment of the present application.

[0029] Figure 2 It is a schematic diagram of an exemplary implementation of a method for acquiring state parameters of high-orbit and low-orbit constellation joint precise single-point positioning, shown in an embodiment of the present application.

[0030] Figure 3 It is a schematic diagram of a device for acquiring state parameters of high-orbit and low-orbit constellation joint precise single-point positioning shown in an embodiment of the present application.

[0031] Figure 4 It is a schematic diagram of an electronic device shown in one embodiment of the present application. DETAILED DESCRIPTION

[0032] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0033] Figure 1 is a schematic diagram of an exemplary implementation of a method for obtaining state parameters of high-orbit and low-orbit constellation joint precise point positioning shown in the present application, such as Figure 1 As shown, the method for obtaining the state parameters of the high-orbit and low-orbit constellation combined precise single-point positioning includes the following steps:

[0034] S101, obtaining high-orbit joint satellite constellation parameters, receiver position parameters and epoch time, and obtaining observation data based on the high-orbit joint satellite constellation parameters, receiver position parameters and epoch time.

[0035] The high-orbit and low-orbit combined satellite constellation includes the Global Navigation Satellite System (GNSS) constellation and the Low Earth Orbit (LEO) constellation. The constellation parameters include the constellation configuration and the number of constellations of the LEO constellation.

[0036] The receiver position parameters may include position parameters of one or more receivers, and the position parameter of each receiver may be expressed as a static position or a dynamic motion trajectory.

[0037] Determine the epoch time, which is the reference time point for the constellation parameters and receiver position parameters.

[0038] The satellite will send navigation signals to the receiver, and the receiver will receive and process these signals. In this process, it is necessary to calculate the satellite errors (clock error, ionospheric delay error, tropospheric delay error, antenna phase center error, antenna phase winding error, earth solid tide error and ocean tide error) and the geometric distance from the satellite to the receiver, calculate and obtain pseudorange observations and carrier phase observations, and generate observation data based on the pseudorange observations and the carrier phase observations.

[0039] S102, preprocessing the observation data to obtain target observation data generated after the preprocessing, and performing a joint standard single-point positioning solution of the high-orbit and low-orbit constellations based on the target observation data to obtain a single-point positioning solution.

[0040] Verify the received observation data to eliminate possible errors or abnormal data, and edit and correct the observation data as needed, such as removing unavailable data and completing missing data, to obtain the target observation data generated after preprocessing, and perform standard single-point positioning based on the pseudo-range observation values ​​in the target observation data combined with the pseudo-range observation equations. The pseudo-range observation equations corresponding to each satellite are as follows:

[0041] P=ρ+cδt s -cδt r +I+T+ε p

[0042] Where P is the pseudorange observation value, ρ is the geometric distance between the satellite and the receiver, c is the speed of light, and δt s is the satellite clock error, δt r is the receiver clock error, I is the ionospheric delay error, T is the tropospheric delay error, ε p is the pseudorange observation noise.

[0043] After constructing the observation equations of multiple satellites, the single-point positioning solution can be obtained by using the weighted least squares method. The single-point positioning solution includes the approximate position of the receiver, which serves as the iterative initial value of the Kalman filter for the subsequent precise single-point positioning solution.

[0044] S103, using the single point positioning solution as the iterative initial value of the Kalman filter to perform state estimation and ambiguity fixation to obtain state parameters.

[0045] The single point positioning solution is used as the initial state parameter to initialize the state vector and covariance matrix of the Kalman filter. The Kalman filter algorithm is used to estimate the state based on the observed data and the state model of the Kalman filter. In this process, the Kalman filter will update and adjust the state parameters of the high- and low-orbit constellation joint precise single point positioning according to the weight of the observed data and the accuracy of the system model.

[0046] In satellite navigation, ambiguity is an important parameter that affects precise positioning and navigation results. By using multi-frequency or multi-path observation data and combining ambiguity fixation technology, the ambiguity can be estimated and fixed, the state parameters can be obtained, and the accuracy of the positioning results can be improved.

[0047] After obtaining the state parameters, the state parameters can be used, for example, to perform positioning error analysis: comparing the difference between the precise single-point positioning solution and the true position, and analyzing the size and distribution of the positioning error.

[0048] After obtaining the state parameters, the state parameters can be used, for example, for accuracy assessment: according to the error characteristics of the precise single-point positioning solution, its accuracy indicators, such as horizontal accuracy, vertical accuracy, time accuracy, etc., are calculated.

[0049] After obtaining the state parameters, for example, the state parameters can be used to perform performance evaluation: evaluating the performance of high-orbit and low-orbit joint precise single-point positioning, including indicators such as positioning accuracy, positioning stability, and convergence speed.

[0050] The embodiment of the present application proposes a method for obtaining state parameters of high- and low-orbit constellation joint precise single-point positioning, by obtaining high- and low-orbit joint satellite constellation parameters, receiver position parameters and epoch time, and obtaining observation data based on the high- and low-orbit joint satellite constellation parameters, the receiver position parameters and the epoch time; preprocessing the observation data to obtain the target observation data generated after the preprocessing, and performing high- and low-orbit constellation joint standard single-point positioning solution based on the target observation data to obtain a single-point positioning solution; using the single-point positioning solution as the iterative initial value of the Kalman filter to perform state estimation and fix the ambiguity to obtain state parameters. The embodiment of the present application comprehensively considers the satellite side, the propagation path, and the user receiver side of the multiple errors and the low-orbit constellation characteristics to obtain observation data, and then combines the low-orbit / high-orbit observation data for precise single-point positioning solution. When obtaining the observation data, the orbit error on the satellite side and the influence of different scenarios on the receiver side are considered, and the influence of the low-orbit constellation characteristics such as configuration and quantity are considered, so that the state parameters of the low-orbit constellation joint GNSS precise single-point positioning in different user receiver scenarios can be accurately obtained.

[0051] Figure 2 is a schematic diagram of an exemplary implementation of a method for obtaining state parameters of high-orbit and low-orbit constellation joint precise point positioning shown in the present application, such as Figure 2 As shown, the method for obtaining the state parameters of the high-orbit and low-orbit constellation combined precise single-point positioning includes the following steps:

[0052] S201, obtaining high-orbit and low-orbit joint satellite constellation parameters, receiver position parameters and epoch time.

[0053] The high-orbit and low-orbit combined satellite constellation includes the Global Navigation Satellite System (GNSS) constellation and the Low Earth Orbit (LEO) constellation. The constellation parameters include the constellation configuration and the number of constellations of the LEO constellation.

[0054] The receiver position parameters may include position parameters of one or more receivers, and the position parameter of each receiver may be expressed as a static position or a dynamic motion trajectory.

[0055] Determine the epoch time, which is the reference time point for the constellation parameters and receiver position parameters.

[0056] S202: Acquire the satellite positions of each satellite constellation and determine the satellite orbits based on the satellite positions.

[0057] The position of GNSS constellation satellites can be obtained by interpolation through orbital dynamics model extrapolation, precise ephemeris, broadcast ephemeris, TLE files, etc., and the satellite orbit error is simulated by adding a random walk noise model to the actual position to determine the satellite orbit.

[0058] The known orbital position of the low-orbit satellite can be obtained through orbital dynamics model extrapolation or TLE two-line root number file. On this basis, random noise is artificially added to simulate the corresponding orbital error to determine the satellite orbit.

[0059] S203, obtaining an earth rotation effect error and a relativistic effect error, and performing data correction based on the earth rotation effect error and the relativistic effect error.

[0060] Since the Earth-fixed system is a non-inertial coordinate system, it changes with the rotation of the Earth, and the Earth-fixed system corresponding to the satellite signal transmission time and the receiver signal reception time is different. Therefore, when calculating the geometric distance from the satellite to the receiver in the Earth-fixed system, this effect must be considered.

[0061]

[0062] In the formula, α=ω*τ is the angle that the earth rotates during signal propagation, τ is the satellite signal propagation time, and ω is the angular velocity of the earth's rotation.

[0063] The relativistic effect in GPS measurement is caused by the different speeds of the satellite clock and the receiver clock in inertial space and the different gravitational positions of the two clocks. The following formula can be used to express the relativistic effect:

[0064]

[0065] Where C is the speed of light, X is the position vector of the satellite, is the velocity vector of the satellite, and Δρ is the equivalent distance value of the observation value caused by the relativistic effect.

[0066] In this application, data correction is performed based on the earth rotation effect error and the relativistic effect error to correct the effects of the earth rotation effect and the relativistic effect. Among them, the earth rotation corrects the receiver coordinates, the relativistic effect corrects the deviation of the satellite clock, and finally corrects the distance between the satellite and the receiver.

[0067] S204, calculating the geometric distance from the satellite to the receiver, calculating the satellite error, and correcting the geometric distance.

[0068] After data correction based on the earth's rotation effect error and relativistic effect error, the geometric distance from the satellite to the receiver is calculated, and the satellite error is calculated.

[0069] Among them, in the calculation of satellite errors, satellite errors include clock error, ionospheric delay error, tropospheric delay error, antenna phase center error, antenna phase winding error, earth solid tide error and ocean tide error.

[0070] The following is a detailed description of each satellite error:

[0071] 1. Clock error

[0072] According to the characteristics of satellite clock error, a quadratic polynomial is used for simulation calculation, and the formula is as follows:

[0073] Δt=a0+a1(t-t0)+a2(t-t0) 2

[0074] Where Δt is the satellite clock error at time t, a0 is the clock error of the clock at reference time t0; a 11 is the clock speed (frequency deviation) of the clock at time t0; a2 is the frequency drift of the clock at time t0.

[0075] 2. Ionospheric delay error

[0076] The ionospheric delay can be obtained from the global gridded ionospheric delay file published by IGS.

[0077] 3. Tropospheric delay error

[0078] The tropospheric delay can be divided into dry delay and wet delay components, expressed as follows:

[0079] Trop=ZPD dry ×M dry +ZWD wet ×M wet

[0080] Where M dry , M wet They are dry component projection function and wet component projection function, ZPD dry , ZWD wet They are dry delay and wet delay in the zenith direction respectively. The projection function can be Niell projection function NMF, Vienna projection function VMF1, global projection function GMF, etc.

[0081] 4. Antenna phase center error

[0082] The antenna phase center error can be obtained by obtaining the satellite phase center deviation value according to the antenna phase center correction value file, simulating the phase center value of the corresponding receiver model, and then superimposing the random error term to obtain the antenna phase center error.

[0083] 5. Antenna phase winding error

[0084] The antenna phase winding error can be expressed as:

[0085]

[0086]

[0087]

[0088] in, represents the antenna phase winding error, The unit vector representing the direction from the satellite to the receiver; represents the satellite unit vector in the satellite-fixed coordinate system; represents the receiver antenna unit vector in the station horizontal coordinate system, D' and D are the dipole vectors calculated from the satellite unit vector and the receiver antenna unit vector, respectively.

[0089] 6. Earth solid tide error and ocean tide error

[0090] The earth solid tide errors and ocean tide errors are calculated using the IERS standard error model and added to the observation data.

[0091] S205, obtaining pseudorange measurement noise, and generating pseudorange observation values ​​according to the pseudorange observation equation by combining the error calculation result and the corrected geometric distance.

[0092] S206, obtaining carrier phase measurement noise, and performing carrier phase integer ambiguity calculation and carrier phase cycle slip calculation, combining the error calculation result and the corrected geometric distance, and generating a carrier phase observation value according to the carrier phase observation equation.

[0093] The calculation formula of carrier phase integer ambiguity is:

[0094] N i =-m*L i +S t

[0095] Where N i is the integer ambiguity, m = 10 8 , S t is the cycle slip, S t is an integer, L i is a frequency-dependent integer constant.

[0096] S207, generating observation data based on the pseudorange observation value and the carrier phase observation value.

[0097] Among them, the observation data mainly includes pseudorange and carrier phase observation values.

[0098] S208, preprocessing the observation data to obtain target observation data generated after the preprocessing.

[0099] In the data preprocessing stage, the observation data is firstly detected and repaired for clock jumps to avoid misjudging the observed value jumps caused by the receiver clock jumps as cycle slips.

[0100] The observation data after clock slip detection and repair are jointly detected by GF (Geometry-Free) and MW (Melbourne-Wübben) methods for gross error detection and cycle slip detection to obtain the target observation data generated after preprocessing.

[0101] Among them, the GF combination and MW combination cycle slip detection methods are as follows.

[0102] The simplified observation equations of GNSS dual-frequency phase and pseudorange can be expressed as follows:

[0103]

[0104] In the above formula, L is the phase carrier phase observation value, P is the pseudorange observation value, subscripts 1 and 2 represent different frequencies, ρ is the geometric distance from the satellite to the receiver, c is the speed of light, dt is the receiver clock error, dT is the satellite clock error, I is the ionospheric delay, T is the tropospheric delay, λ is the corresponding frequency wavelength, and N is the integer ambiguity.

[0105] The observed values ​​of the MW combination are:

[0106]

[0107] Where f is the frequency, N MW = N1-N2 is the wide lane ambiguity, and its wavelength λ MW =c / (f1-f2). According to the above formula, N MW It can be expressed as:

[0108] N MW =(L MW -P MW ) / λ MW

[0109] The cycle slip test quantity is:

[0110] D MW =|N MW,i - <N MW > i-1 |≥4σ i

[0111] Where σ is the standard deviation, <N MW > and σ are generally calculated using the following recursive formula:

[0112]

[0113]

[0114] The GF combined observation value can be expressed as:

[0115] L GF =L1-L2=(γ-1)I+(λ1N1-λ2N2)

[0116] in, It is the ratio of the square of the frequency of the dual-frequency signal. The traditional cycle slip test quantity is:

[0117] D GF =L GF,i -L GF,i-1

[0118] This verification quantity is obtained based on the premise that the ionosphere changes relatively smoothly between epochs. GF The series still has a large trend term, so D GF The difference sequence, that is, the GF quadratic difference, is used as the cycle slip test quantity:

[0119] D' GF =D GF,i -D GF,i-1

[0120] S209, performing a joint standard single-point positioning solution of the high-orbit and low-orbit constellations based on the target observation data to obtain a single-point positioning solution.

[0121] Based on the pseudo-range observation values ​​in the target observation data combined with the pseudo-range observation equation group, the standard single-point positioning solution is performed. The pseudo-range observation equation corresponding to each satellite is as follows:

[0122] P=ρ+cδt s -cδt r +I+T+ε p

[0123] Where P is the pseudorange observation value, ρ is the geometric distance between the satellite and the receiver, c is the speed of light, and δt s is the satellite clock error, δt r is the receiver clock error, I is the ionospheric delay error, T is the tropospheric delay error, ε p is the pseudorange observation noise.

[0124] After constructing the observation equations of multiple satellites, the single-point positioning solution can be obtained by using the weighted least squares method. The single-point positioning solution includes the approximate position of the receiver, which serves as the iterative initial value of the Kalman filter for the subsequent precise single-point positioning solution.

[0125] S210, using the single point positioning solution as the iterative initial value of the Kalman filter to perform state estimation and ambiguity fixation to obtain state parameters.

[0126] The single-point positioning solution (receiver 3D position coordinates and receiver clock difference) is used as the iterative initial value of the Kalman filter to perform state estimation to obtain the real positioning solution. Based on the real positioning solution, the positioning ambiguity is fixed to obtain the ambiguity integer solution. The ambiguity integer solution is substituted into the observation equation to obtain the relevant parameter solution.

[0127] Specifically, the low-orbit / high-orbit joint precise point positioning solution adopts a non-difference non-combination function model, the basic state parameters of which include the receiver's 3D position coordinates r r , receiver clock error δt r , Zenith Tropospheric Wet Delay ZPD r , ionospheric delay in the station-satellite line of sight Fuzziness parameter Right now:

[0128]

[0129] Wherein, the superscript s represents the satellite, the subscript r represents the receiver, and j is the frequency identifier.

[0130] In the above formula, the zenith tropospheric wet delay ZPD r , ionospheric delay in the station-satellite line of sight Fuzziness parameter An initial value can be obtained through the model or set directly.

[0131] The receiver's 3D position coordinates and the receiver's clock error and its variance P0 in the initial value of the system state are obtained from the single point positioning solution mentioned above. The state estimate at time t(k) can be calculated recursively by the extended Kalman filter:

[0132] (1) One-step state prediction

[0133]

[0134] (2) Covariance one-step prediction

[0135]

[0136] (3) Filter gain

[0137]

[0138] (4) State estimation

[0139]

[0140] (5) State covariance estimation

[0141] P k =(IK k H k ) k,k-1

[0142] In the formula, I is the unit matrix, X k,k-1 , P k,k-1 are the one-step prediction value and its variance-covariance matrix, K k is the gain matrix, P k are the filter estimates and their variance-covariance matrices, Φ k,k-1 is the state transfer matrix, Q k-1 is the dynamic noise covariance matrix, H k is the coefficient matrix, L k is the observation vector, R k is the observed noise covariance matrix. In actual calculation, in order to reduce the sensitivity of the filtering algorithm to the calculation rounding error, it is necessary to ensure that P k Symmetric positive definiteness is generally written as follows:

[0143]

[0144] The Kalman filter is used to calculate the precise point positioning real number solution, and then the ambiguity is fixed. The square of the distance between them is the objective function, and the integer ambiguity N is searched by the least square ambiguity reduction adjustment (LAMBDA) algorithm to minimize the objective function:

[0145]

[0146] The LAMBDA algorithm consists of two main parts: (1) a multidimensional integer transformation to reduce the correlation between ambiguity parameters; and (2) an ambiguity search in the transformed space and then the result is transformed back into the ambiguity space to obtain the ambiguity integer solution.

[0147] The optimal integer solution of the integer ambiguity is substituted N times back into the original observation equation to solve the receiver coordinates, ZPD, ionospheric delay, receiver clock error and other parameters.

[0148] S211, performing performance evaluation of high-orbit and low-orbit constellation joint precise point positioning based on the state parameters.

[0149] The embodiment of the present application comprehensively considers the satellite side, propagation path, and multiple errors on the user receiver side as well as the characteristics of the low-orbit constellation to obtain observation data, and then combines the low-orbit / high-orbit observation data for precise single-point positioning. When obtaining the observation data, the influence of the orbit error on the satellite side and different scenarios on the receiver side are taken into account, while the influence of the characteristics of the low-orbit constellation such as configuration and quantity is taken into account. The state parameters of the low-orbit constellation combined with GNSS precise single-point positioning in different user receiver scenarios can be accurately obtained.

[0150] Figure 3 is a schematic diagram of a device for acquiring state parameters of high-orbit and low-orbit constellation joint precise point positioning shown in the present application, such as Figure 3 As shown, the high-orbit and low-orbit constellation combined precise single-point positioning performance evaluation device 300 includes a data acquisition module 301, a positioning solution module 302, and a state estimation module 303, wherein:

[0151] The data acquisition module 301 is used to obtain the high-low orbit joint satellite constellation parameters, receiver position parameters and epoch time, and obtain observation data based on the high-low orbit joint satellite constellation parameters, the receiver position parameters and the epoch time.

[0152] The positioning solution module 302 is used to preprocess the observation data to obtain the target observation data generated after the preprocessing, and perform a joint standard single-point positioning solution of the high-orbit and low-orbit constellations based on the target observation data to obtain a single-point positioning solution.

[0153] The state estimation module 303 is used to use the single point positioning solution as the iterative initial value of the Kalman filter to perform state estimation and ambiguity fixation to obtain state parameters.

[0154] This device comprehensively considers the satellite side, propagation path, and multiple errors on the user receiver side as well as the characteristics of the low-orbit constellation to obtain observation data, and then combines the low-orbit / high-orbit observation data for precise point positioning. When obtaining the observation data, the orbit error on the satellite side and the influence of different scenarios on the receiver side are taken into account, while the influence of the low-orbit constellation characteristics such as configuration and number are taken into account. The state parameters of the low-orbit constellation combined with GNSS precise point positioning in different user receiver scenarios can be accurately obtained.

[0155] Furthermore, the data acquisition module 301 is also used to: obtain the satellite position of each satellite constellation and determine the satellite orbit based on the satellite position; obtain the earth rotation effect error and the relativistic effect error, and perform data correction based on the earth rotation effect error and the relativistic effect error; calculate the geometric distance from the satellite to the receiver, calculate the satellite error, and correct the geometric distance; obtain the pseudorange measurement noise, and combine the result of the error calculation and the corrected geometric distance to generate the pseudorange observation value according to the pseudorange observation equation; obtain the carrier phase measurement noise, and perform the carrier phase integer ambiguity calculation and the carrier phase cycle slip calculation, and combine the result of the error calculation and the corrected geometric distance to generate the carrier phase observation value according to the carrier phase observation equation; generate observation data based on the pseudorange observation value and the carrier phase observation value.

[0156] Furthermore, the calculation formula of the carrier phase integer ambiguity used in the data acquisition module 301 is:

[0157] N i =-m*L i +S t

[0158] Where N i is the integer ambiguity, m = 10 8 , S t is the cycle slip, S t is an integer, L i is a frequency-dependent integer constant.

[0159] Furthermore, the satellite errors involved in the data acquisition module 301 include: clock error, ionospheric delay error, tropospheric delay error, antenna phase center error, antenna phase winding error, earth solid tide error and ocean tide error.

[0160] Furthermore, the state estimation module 303 is also used to: use the single-point positioning solution as the iterative initial value of the Kalman filter to perform state estimation to obtain a real positioning solution; based on the real positioning solution, fix the positioning ambiguity to obtain an ambiguity integer solution; substitute the ambiguity integer solution into the observation equation to obtain the relevant parameter solution.

[0161] Furthermore, the positioning solution module 302 is also used to: perform clock jump detection and repair on the observation data; perform gross error detection and cycle slip detection on the observation data after clock jump detection and repair, and obtain the target observation data generated after preprocessing.

[0162] Furthermore, the positioning solution module 302 is also used to perform standard single-point positioning solution based on the pseudo-range observation values ​​in the target observation data combined with the pseudo-range observation equation group. The pseudo-range observation equation corresponding to each satellite is as follows:

[0163] P=ρ+cδt s -cδt r +I+T+ε p

[0164] Where P is the pseudorange observation value, ρ is the geometric distance between the satellite and the receiver, c is the speed of light, and δt s is the satellite clock error, δt r is the receiver clock error, I is the ionospheric delay error, T is the tropospheric delay error, ε p is the pseudorange observation noise.

[0165] Furthermore, the device also includes a performance evaluation module, which is used to perform performance evaluation of high-orbit and low-orbit constellation joint precise single-point positioning based on the state parameters.

[0166] In order to implement the above embodiment, the present application embodiment also proposes an electronic device 400, such as Figure 4 As shown, the electronic device 400 includes: a processor 401 and a memory 402 that is communicatively connected to the processor, the memory 402 stores instructions that can be executed by at least one processor, and the instructions are executed by at least one processor 401 to implement the method for obtaining state parameters of high-orbit and low-orbit constellation joint precise single-point positioning as shown in the above embodiment.

[0167] In order to implement the above embodiments, the embodiments of the present application also propose a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable the computer to implement the method for obtaining state parameters of the joint precise single-point positioning of the high- and low-orbit constellations as shown in the above embodiments.

[0168] In order to implement the above embodiments, the embodiments of the present application also propose a computer program product, including a computer program. When the computer program is executed by a processor, it implements the method for obtaining state parameters of the high-orbit and low-orbit constellation joint precise single-point positioning as shown in the above embodiments.

[0169] In the description of the present application, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0170] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0171] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0172] 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 obtaining state parameters of high-orbit and low-orbit constellation joint precise point positioning, characterized in that: include: Acquire high-orbit joint satellite constellation parameters, receiver position parameters and epoch time, and acquire observation data based on the high-orbit joint satellite constellation parameters, the receiver position parameters and the epoch time; Preprocessing the observation data to obtain target observation data generated after the preprocessing, and performing high-orbit and low-orbit constellation joint standard single-point positioning solution based on the target observation data to obtain a single-point positioning solution; The single point positioning solution is used as the iterative initial value of the Kalman filter to perform state estimation and ambiguity fixation to obtain state parameters.

2. The method according to claim 1, characterized in that: The obtaining of observation data comprises: Obtaining satellite positions of each satellite constellation and determining satellite orbits based on the satellite positions; Obtaining an earth rotation effect error and a relativistic effect error, and performing data correction based on the earth rotation effect error and the relativistic effect error; Calculating the geometric distance from the satellite to the receiver, calculating the satellite error, and correcting the geometric distance; Obtain pseudorange measurement noise, and generate pseudorange observation values ​​according to pseudorange observation equations by combining the error calculation results and the corrected geometric distance; Obtain carrier phase measurement noise, perform carrier phase integer ambiguity calculation and carrier phase cycle slip calculation, combine the error calculation results and the corrected geometric distance, and generate carrier phase observation values ​​according to the carrier phase observation equation; Observation data is generated based on the pseudorange observations and the carrier phase observations.

3. The method according to claim 2, characterized in that The calculation formula of the carrier phase integer ambiguity is: N i =-m*L i +S t Where N i is the integer ambiguity, m = 10 8 , S t is the cycle slip, S t is an integer, L i is a frequency-dependent integer constant.

4. The method according to claim 2, characterized in that: In the calculation of satellite error, the satellite error includes: Clock error, ionospheric delay error, tropospheric delay error, antenna phase center error, antenna phase winding error, earth solid tide error and ocean tide error.

5. The method according to claim 4, characterized in that The single point positioning solution is used as the iterative initial value of the Kalman filter to perform state estimation and ambiguity fixation to obtain state parameters, including: Using the single point positioning solution as the iterative initial value of the Kalman filter to perform state estimation to obtain a real number positioning solution; Based on the real number solution of positioning, the positioning ambiguity is fixed to obtain the ambiguity integer solution; Substitute the ambiguity integer solution into the observation equation to obtain the relevant parameter solution.

6. The method according to claim 5, characterized in that The preprocessing of the observation data to obtain target observation data generated after the preprocessing includes: Performing clock jump detection and repair on the observation data; The observation data after clock jump detection and repair are subjected to gross error detection and cycle slip detection to obtain the target observation data generated after preprocessing.

7. The method according to claim 6, characterized in that The method of performing high-orbit and low-orbit combined standard single-point positioning solution based on target observation data to obtain a single-point positioning solution includes: Based on the pseudo-range observation values ​​in the target observation data combined with the pseudo-range observation equation group, the standard single-point positioning solution is performed. The pseudo-range observation equation corresponding to each satellite is as follows: P=ρ+cδt s -cδt r +I+T+e p Where P is the pseudorange observation value, ρ is the geometric distance between the satellite and the receiver, c is the speed of light, and δt s is the satellite clock error, δt r is the receiver clock error, I is the ionospheric delay error, T is the tropospheric delay error, ε p is the pseudorange observation noise.

8. The method according to any one of claims 1 to 7, characterized in that After obtaining the state parameters, the method further includes: The performance of high-orbit and low-orbit constellation joint precise point positioning is evaluated based on the state parameters.

9. A device for acquiring state parameters of high-orbit and low-orbit constellation joint precise point positioning performance, characterized in that: include: A data acquisition module, used to acquire high-orbit joint satellite constellation parameters, receiver position parameters and epoch time, and acquire observation data based on the high-orbit joint satellite constellation parameters, the receiver position parameters and the epoch time; A positioning solution module is used to preprocess the observation data to obtain target observation data generated after the preprocessing, and perform a joint standard single-point positioning solution of the high-orbit and low-orbit constellations based on the target observation data to obtain a single-point positioning solution; The state estimation module is used to use the single point positioning solution as the iterative initial value of the Kalman filter to perform state estimation and ambiguity fixation to obtain state parameters.

10. An electronic device comprising: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 8.

11. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-8.

12. A computer program product comprising a computer program, which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 8.

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