A GNSS satellite phase bias correction information estimation method, device, equipment and storage medium

Abstract

The application discloses a GNSS satellite phase bias correction information estimation method, device and equipment and a storage medium. The method comprises the following steps: constructing a ground joint observation model based on ground observation data received by a ground reference station; constructing a satellite-borne observation model based on GNSS satellite observation data received by a low-orbit satellite; jointly solving the ground joint observation model and the satellite-borne observation model to obtain ground end ambiguity float solutions and variances of each GNSS satellite and satellite-borne ambiguity float solutions and variances; constructing a joint estimation equation set according to the ground end ambiguity float solutions and corresponding variances and the satellite-borne ambiguity float solutions and corresponding variances; and selecting one satellite from all GNSS satellites as a reference satellite, and solving the joint estimation equation set to obtain phase bias correction information of all other GNSS satellites relative to the reference satellite, so that fast convergence and high-precision estimation of satellite phase bias correction information are realized.

Description

Technical Field

[0001] This invention relates to the field of global navigation satellite system positioning enhancement technology, and in particular to a method, apparatus, device and storage medium for estimating phase deviation correction information of GNSS satellites. Background Technology

[0002] High-precision positioning using Global Navigation Satellite System (GNSS) typically relies on fixed carrier phase ambiguity. Phase deviation, including receiver-side and satellite-side phase deviation, is the core error source affecting the recovery of the integer characteristics of ambiguity. Accurately estimating GNSS satellite phase deviation and providing reliable correction information to users is a crucial step in achieving real-time high-precision GNSS positioning.

[0003] In existing technologies, the estimation of GNSS satellite phase deviation largely relies on single-station or network-based calculations from ground reference stations. While this method offers advantages such as known ground reference station coordinates and stable observations, it suffers from slow ambiguity convergence due to the slow changes in satellite perspective, resulting in poor timeliness of phase deviation estimation and difficulty in simultaneously achieving fast convergence and high-precision estimation. Some techniques attempt to introduce external observation sources for auxiliary estimation, but these typically utilize only single observations from either the ground or space-based sources, failing to achieve effective fusion of the two.

[0004] Therefore, improving the timeliness and high-precision estimation of GNSS satellite phase deviation is an urgent problem to be solved. Summary of the Invention

[0005] This invention provides a method, apparatus, device, and storage medium for estimating phase deviation correction information of GNSS satellites, in order to solve the problems of low timeliness and accuracy in the prior art for estimating phase deviation of GNSS satellites.

[0006] According to one aspect of the present invention, a method for estimating phase deviation correction information of a GNSS satellite is provided, the method comprising: A joint ground-based observation model is constructed based on ground observation data received from ground reference stations. The ground observation data includes GNSS satellite observation data and low-Earth orbit satellite observation data. Based on GNSS satellite observation data received from low-Earth orbit satellites, a satellite-borne observation model is constructed. The ground-side joint observation model and the satellite-side observation model are jointly solved to obtain the ground-side ambiguity floating-point solution and corresponding variance of each GNSS satellite, as well as the satellite-side ambiguity floating-point solution and corresponding variance. A joint estimation equation system is constructed based on the ground-side ambiguity floating-point solution and its corresponding variance, and the spaceborne-side ambiguity floating-point solution and its corresponding variance. One satellite is selected from all GNSS satellites as a reference satellite, and the joint estimation equations are solved to obtain the phase deviation correction information of all other GNSS satellites relative to the reference satellite.

[0007] According to another aspect of the present invention, a device for estimating phase deviation correction information of a GNSS satellite is provided, the device comprising: The first construction module is used to construct a ground-end joint observation model based on ground observation data received from ground reference stations. The ground observation data includes GNSS satellite observation data and low-orbit satellite observation data. The second building module is used to construct a spaceborne observation model based on GNSS satellite observation data received from low-orbit satellites. The first solution module is used to jointly solve the ground-side joint observation model and the satellite-side observation model to obtain the ground-side ambiguity floating-point solution and corresponding variance of each GNSS satellite, as well as the satellite-side ambiguity floating-point solution and corresponding variance. The third construction module is used to construct a joint estimation equation set based on the ground-side ambiguity floating-point solution and its corresponding variance, and the spaceborne-side ambiguity floating-point solution and its corresponding variance. The second solution module is used to select one satellite from all GNSS satellites as a reference satellite, solve the joint estimation equations, and obtain the phase deviation correction information of all other GNSS satellites relative to the reference satellite.

[0008] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: at least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the GNSS satellite phase deviation correction information estimation method according to any embodiment of the present invention.

[0009] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the GNSS satellite phase deviation correction information estimation method according to any embodiment of the present invention.

[0010] This invention discloses a method, apparatus, device, and storage medium for estimating phase deviation correction information of GNSS satellites. The method includes: constructing a ground-side joint observation model based on ground observation data received from a ground reference station, wherein the ground observation data includes GNSS satellite observation data and low-Earth orbit (LEO) satellite observation data; constructing a satellite-side observation model based on the GNSS satellite observation data received from LEO satellites; jointly solving the ground-side joint observation model and the satellite-side observation model to obtain the ground-side ambiguity floating-point solution and its corresponding variance, as well as the satellite-side ambiguity floating-point solution and its corresponding variance; constructing a joint estimation equation set based on the ground-side ambiguity floating-point solution and its corresponding variance, and the satellite-side ambiguity floating-point solution and its corresponding variance; selecting one satellite from all GNSS satellites as a reference satellite, solving the joint estimation equation set to obtain the phase deviation correction information of all other GNSS satellites relative to the reference satellite. This method integrates the dual observation and calculation results from ground reference stations and low-Earth orbit satellite receivers, fully combining the advantages of stable ground-based observations and rapid changes in the viewing angle of low-Earth orbit satellites. It can achieve rapid convergence and high-precision estimation of GNSS satellite phase deviation correction information, solving the problems of low timeliness and low accuracy in GNSS satellite phase deviation estimation in existing technologies.

[0011] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a flowchart illustrating a method for estimating phase deviation correction information of a GNSS satellite according to Embodiment 1 of the present invention. Figure 2 This is a comparison chart showing the convergence effect of the proposed method versus a single GNSS ambiguity floating-point solution, provided in an embodiment of the invention. Figure 3 This is a schematic diagram of the structure of a GNSS satellite phase deviation correction information estimation device provided in Embodiment 2 of the present invention; Figure 4 This is a schematic diagram of the electronic device used in the GNSS satellite phase deviation correction information estimation method according to an embodiment of the present invention. Detailed Implementation

[0014] To enable those skilled in the art to better understand the present invention, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention. It should be understood that the various steps described in the method embodiments of the present invention can be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0015] The term "comprising" and its variations as used herein are open-ended inclusions, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.

[0016] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, any variations of the terms "comprising" and "having," etc., are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0017] It should be noted that the terms "a" and "a plurality of" used in this invention are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0018] The names of the messages or information exchanged between the multiple devices in the embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of these messages or information.

[0019] Low Earth Orbit (LEO) satellites are characterized by their low orbital altitude, high speed, rapid changes in viewing angle, and fast updates in geometric configuration. Their onboard receivers can receive GNSS signals to form space-based observation results. Simultaneously, ground reference stations can observe both GNSS and LEO satellites, providing a new observational dimension for phase deviation estimation. However, currently, there is a lack of a method that fully utilizes the characteristic that the ambiguity floating-point solutions obtained from the same GNSS satellite at both the ground and LEO onboard ends have the same satellite-end phase deviation, and based on this, achieves joint estimation of phase deviation correction information by the ground and onboard ends.

[0020] Therefore, this invention proposes a phase deviation correction information estimation method that combines low-orbit satellites and GNSS to solve the problems of slow convergence, low accuracy, and insufficient integration of ground-end and space-end observation resources in the prior art.

[0021] Example 1 Figure 1 This is a flowchart illustrating a method for estimating phase deviation correction information of a GNSS satellite according to Embodiment 1 of the present invention. This method is applicable to situations where the phase deviation correction information of a GNSS satellite is estimated by combining ground reference sheets and observation data from low-orbit satellites. This method can be executed by a GNSS satellite phase deviation correction information estimation device, which can be implemented by software and / or hardware and is generally integrated into an electronic device. In this embodiment, the electronic device includes, but is not limited to, devices such as computers.

[0022] like Figure 1 As shown in Embodiment 1 of the present invention, a method for estimating phase deviation correction information of a GNSS satellite includes the following steps: S110. Construct a joint ground-end observation model based on ground observation data received from ground reference stations. The ground observation data includes GNSS satellite observation data and low-orbit satellite observation data.

[0023] In this context, a ground reference station is a ground-based site used to observe satellites and capable of receiving satellite signals. Ground observation data refers to the observation data received by the ground reference station, which may include GNSS satellite observation data and low Earth orbit (LEO) satellite observation data. A ground-based joint observation model is a model that combines LEO satellite observation data and GNSS satellite observation data. GNSS satellites can refer to satellites in orbit within the Global Navigation Satellite System. LEO satellites can refer to artificial satellites operating in Low Earth Orbit (LEO).

[0024] In this embodiment, observation data from GNSS satellites and low-Earth orbit (LEO) satellites can be received separately via ground reference stations. Based on the ground observation data received by the ground reference stations, a joint ground-based observation model can be constructed. For example, a system can be constructed that includes a ground reference station network, an LEO satellite-borne receiver, GNSS satellites, and a processing center. The ground reference stations can be used to receive observation data from GNSS satellites and LEO satellites, the onboard receivers on the LEO satellites can be used to receive GNSS satellite observation data, and the processing center can be used to jointly process the solution results from the ground and onboard sources to estimate the GNSS satellite phase offset correction information.

[0025] In one embodiment, the observation equation of the ground-based joint observation model is: ; Among them, superscript Represents GNSS satellites, superscript Represents low-Earth orbit satellites. s The designation of the GNSS satellite. p This is the designation for low-Earth orbit satellites. r Indicates a ground reference station. IF Indicates an assembly without an ionosphere; This represents the ionospheric pseudorange observations of GNSS satellites from a ground reference station. This represents the carrier phase observations of the GNSS satellite from the ground reference station. This represents the ionospheric pseudorange observations of low-Earth orbit satellites from a ground reference station. This represents the carrier phase observations of a low-Earth orbit satellite from a ground reference station. This refers to the distance from the GNSS satellite to the ground reference station. This represents the distance from the low-Earth orbit satellite to the ground reference station. It is the speed of light in a vacuum. For the receiver clock bias of the reparameterized ground reference station, For the receiver clock bias of the reparameterized low-Earth orbit satellite, For GNSS satellite clock bias, For low-Earth orbit satellite clock bias; For GNSS satellite tropospheric projection functions, For low-Earth orbit satellites, (This is the tropospheric projection function.) ground reference station r Zenith tropospheric time delay, For GNSS satellite carrier wavelengths without ionosphere, For carrier waves of low-Earth orbit satellites without ionospheric combination wavelengths; This is the ambiguity floating-point solution for the GNSS satellites after ionospheric reparameterization from a ground reference station. This is the ambiguity floating-point solution for the ionosphere-free combination reparameterization of low-Earth orbit satellites from a ground reference station. This represents the noise in the ionospheric-free combined pseudorange observations of GNSS satellites from a ground reference station. The noise in the carrier phase observations of GNSS satellites from the ground reference station. This represents the noise in the ionospheric-free combined pseudorange observations of low-Earth orbit satellites from a ground reference station. This represents the noise in the carrier phase observations of low-orbit satellites from the ground reference station.

[0026] In this embodiment, the GNSS satellite observation data received by the ground reference station includes at least the observation values ​​of the ionospheric-free combined pseudorange of the GNSS satellites, as well as carrier phase observation values. The low-Earth orbit (LEO) satellite observation data includes at least the observation values ​​of the ionospheric-free combined pseudorange of the LEO satellites, as well as carrier phase observation values. For the ground reference station, joint filtering can be performed on the GNSS satellites and the LEO satellites to obtain the narrow-lane ambiguity floating-point solution of the GNSS satellites.

[0027] In one embodiment, the parameter vector to be estimated for the ground-based joint observation model is: ; in, Let be the vector of parameters to be estimated. These are the three-dimensional coordinate parameters of the ground reference station.

[0028] In this embodiment, the parameter vector to be estimated may include the three-dimensional coordinate parameters of the ground reference station, the reparameterized receiver clock bias of the ground reference station, the reparameterized receiver clock bias of the low-Earth orbit satellite, and the ground reference station. r The zenith tropospheric delay, the ambiguity of the GNSS satellite after ionospheric reparameterization of the ground reference station, and the ambiguity of the low-orbit satellite after ionospheric reparameterization of the ground reference station, etc.

[0029] S120. Based on GNSS satellite observation data received from low-orbit satellites, a satellite-borne observation model is constructed.

[0030] Among them, the spaceborne observation model can be an observation model constructed by a low-orbit satellite based on the received GNSS satellite observation data.

[0031] In this embodiment, observation data from GNSS satellites can be received via low-Earth orbit satellites, and a spaceborne observation model can be constructed using the GNSS satellite observation data received via low-Earth orbit satellites.

[0032] In one embodiment, the observation equation of the spaceborne observation model is: ; Among them, subscriptl This refers to the onboard receiver of a low-Earth orbit satellite. This represents the observation value of the ionospheric-free combined pseudorange of GNSS satellites by the spaceborne receiver. This represents the carrier phase observation value of the GNSS satellite by the onboard receiver. This represents the distance from the GNSS satellite to the onboard receiver. The receiver clock bias of the reparameterized spaceborne receiver; This represents the noise in the ionospheric-free combined pseudorange observations of GNSS satellites by the spaceborne receiver. This refers to the noise in the carrier phase observations of the GNSS satellite by the onboard receiver. This is the floating-point solution of ambiguity for the GNSS satellite after ionospheric reparameterization by the spaceborne receiver.

[0033] In this embodiment, the GNSS satellite observation data received by the low-Earth orbit (LEO) satellite includes at least the observation values ​​of the ionospheric-free combined pseudorange and the carrier phase observation values ​​of the GNSS satellite. Similarly, the onboard receiver of the LEO satellite can also formulate GNSS observation equations on the received observation data to obtain the floating-point ambiguity solution of the GNSS satellite. .

[0034] S130. Jointly solve the ground-side joint observation model and the satellite-side observation model to obtain the ground-side ambiguity floating-point solution and corresponding variance of each GNSS satellite, as well as the satellite-side ambiguity floating-point solution and corresponding variance.

[0035] The ground-side ambiguity floating-point solution refers to the ambiguity floating-point solution obtained when a ground reference station observes a GNSS satellite. The satellite-side ambiguity floating-point solution refers to the ambiguity floating-point solution obtained when a low-Earth orbit satellite observes a GNSS satellite. The ambiguity floating-point solution can be a non-integer ambiguity estimate obtained from carrier phase observation calculations. Carrier phase observations can only directly measure the fractional part of the signal and cannot directly determine the integer cycle number. Furthermore, various biases are introduced during the observation process; therefore, the calculated ambiguity estimate is usually a non-integer form with decimals, i.e., the ambiguity floating-point solution. The ambiguity floating-point solution can be decomposed into an integer ambiguity part, receiver phase bias, and satellite phase bias.

[0036] In this embodiment, the ground-side joint observation model and the satellite-side observation model can be jointly solved to obtain the ground-side ambiguity floating-point solution and its corresponding variance for each GNSS satellite, as well as the satellite-side ambiguity floating-point solution and its corresponding variance.

[0037] For the same GNSS satellite, the obtained ambiguity floating-point solution and Since both models should have the same satellite fractional bias, they can be used simultaneously to separate the floating-point and integer solutions for ambiguity. For the satellite-based observation model, the data received by the satellite receiver on the low-Earth orbit (LEO) satellite changes rapidly in perspective, but the receiver's coordinates are unknown due to dynamic changes. Conversely, the coordinates of the data from the ground reference station are known, but the station's perspective relative to the satellite changes slowly. Integrating the ground observation data with the LEO observation data can accelerate ambiguity convergence to some extent. The fusion of the two models can improve the accuracy of fractional bias estimation. In solving both types of ambiguity, the variance of the corresponding floating-point solution can be obtained from the ambiguity parameters. Considering the differences in ambiguity accuracy introduced by different satellite and ground stations, the weights in the joint equations can be determined based on the variance when jointly solving for fractional bias.

[0038] S140. Construct a joint estimation equation set based on the ground-side ambiguity floating-point solution and its corresponding variance, and the spaceborne-side ambiguity floating-point solution and its corresponding variance.

[0039] In this embodiment, a joint estimation equation set can be constructed based on the ambiguity floating-point solution and its corresponding variance at the ground end, and the ambiguity floating-point solution and its corresponding variance at the spaceborne end.

[0040] In one embodiment, constructing a joint estimation equation set based on the ground-side ambiguity floating-point solution and its corresponding variance, and the satellite-side ambiguity floating-point solution and its corresponding variance, includes: decomposing the ground-side ambiguity floating-point solution and the satellite-side ambiguity floating-point solution into integer ambiguity components, receiver phase deviation, and satellite phase deviation, respectively; determining joint estimation weights based on the variances of the ground-side ambiguity floating-point solution and the satellite-side ambiguity floating-point solution; and constructing a joint estimation equation set by combining the joint estimation weights, the integer ambiguity components, the receiver phase deviation, and the satellite phase deviation.

[0041] Among them, the integer ambiguity part can refer to the integer part of the floating-point ambiguity solution, the receiver phase deviation can refer to the deviation generated by the receiver (ground reference station or low-orbit satellite) when receiving the signal, and the satellite phase deviation can refer to the deviation generated by the GNSS satellite when transmitting the signal.

[0042] In this embodiment, the ground-side ambiguity floating-point solution and the satellite-side ambiguity floating-point solution can be decomposed into integer ambiguity components, receiver phase deviation, and satellite phase deviation, respectively. The joint estimation weight is determined based on the variance of the ground-side ambiguity floating-point solution and the variance of the satellite-side ambiguity floating-point solution. By combining the joint estimation weight, the integer ambiguity components, the receiver phase deviation, and the satellite phase deviation, a joint estimation equation set can be constructed.

[0043] S150. Select one satellite from all GNSS satellites as a reference satellite, solve the joint estimation equations, and obtain the phase deviation correction information of all other GNSS satellites relative to the reference satellite.

[0044] In this embodiment, one satellite can be arbitrarily selected from all GNSS satellites as a reference satellite. The phase deviation of the reference satellite is used as a benchmark (considered as a known value). The joint estimation equations are rank-deficient and solved using the least squares method. This yields the phase deviation correction information of all other GNSS satellites relative to the reference satellite.

[0045] For example, if the rank deficiency of the joint estimation equation system is 1, in order to ensure that the full rank can be estimated, the phase deviation of a certain satellite can be selected as the reference and fixed to 0. Then, the phase deviation of the other satellites relative to the reference satellite can be estimated by the least squares method. Essentially, the phase deviation correction information obtained is the inter-satellite single-difference phase deviation.

[0046] This invention provides a method for estimating phase deviation correction information of GNSS satellites, comprising: constructing a ground-side joint observation model based on ground observation data received from a ground reference station, wherein the ground observation data includes GNSS satellite observation data and low-Earth orbit (LEO) satellite observation data; constructing a spaceborne observation model based on GNSS satellite observation data received from LEO satellites; jointly solving the ground-side joint observation model and the spaceborne observation model to obtain the ground-side ambiguity floating-point solution and its corresponding variance, as well as the spaceborne ambiguity floating-point solution and its corresponding variance for each GNSS satellite; constructing a joint estimation equation set based on the ground-side ambiguity floating-point solution and its corresponding variance, and the spaceborne ambiguity floating-point solution and its corresponding variance; selecting one satellite from all GNSS satellites as a reference satellite, solving the joint estimation equation set to obtain the phase deviation correction information of all other GNSS satellites relative to the reference satellite. This method integrates the dual observation and calculation results from ground reference stations and low-Earth orbit satellite receivers, fully combining the advantages of stable ground-based observations and rapid changes in the viewing angle of low-Earth orbit satellites. It can achieve rapid convergence and high-precision estimation of GNSS satellite phase deviation correction information, solving the problems of low timeliness and low accuracy in GNSS satellite phase deviation estimation in existing technologies.

[0047] Based on the above embodiments, modified embodiments of the above embodiments are proposed. It should be noted that, in order to keep the description brief, only the differences from the above embodiments are described in the modified embodiments.

[0048] In one embodiment, the equations expressing the ground-side ambiguity floating-point solution and the spaceborne ambiguity floating-point solution are as follows: ; in, This is the floating-point solution for the ambiguity at the satellite end, calculated by the receiving end. for The corresponding integer part can be obtained by rounding down. For the phase deviation at the receiving end, This refers to the phase deviation at the satellite end of a GNSS satellite. When the receiver is a ground observation station, the satellite end is either a GNSS satellite or a low-Earth orbit satellite. When the receiver is a low-Earth orbit satellite, the satellite end is a GNSS satellite.

[0049] In this embodiment, for arbitrary ambiguity floating-point solutions Both can be written as: .

[0050] In one embodiment, the joint estimation equations are: ; in, Indicates ground reference station j Corresponding GNSS satellites s The fuzzy floating-point solution, j From 1 to m integers, m The number of ground reference stations, s From 1 to n integers, n The number of GNSS satellites, for The integer part; Indicates low-orbit satellites p The GNSS satellite corresponding to the onboard receiver s The fuzzy floating-point solution, p From 1 to k integers, k For the number of low-Earth orbit satellites, for The integer part; ground reference station j The receiver's coefficient matrix, For low-orbit satellites p The coefficient matrix of the spaceborne receiver; GNSS satellites corresponding to ground reference stations s The coefficient matrix, GNSS satellites corresponding to low Earth orbit satellites s The coefficient matrix; ground reference station j The phase deviation at the receiving end, For low-orbit satellites p Phase deviation of the satellite-borne receiver's receiving end. GNSS satellites The phase deviation at the satellite end.

[0051] In this embodiment, for a given... m A network of reference stations consisting of several stations has k If a low-Earth orbit satellite-borne receiver simultaneously observes... n A single satellite can integrate the non-difference ambiguities of all station-satellite pairs to form a joint estimation equation system. The joint estimation equation system contains... Used to select the ground receiver j , of which j One element is 1, and the rest are 0. Used for selecting low-Earth orbit satellites p , of which p One element is 1, and the rest are 0. and Used to select GNSS satellites, where the first s One element is -1, and the rest are 0.

[0052] The method of this invention integrates ground-based and satellite-based observation resources. Ground reference stations offer advantages such as known coordinates and stable observations, while low-Earth orbit (LEO) satellite-based receivers offer advantages such as rapid viewpoint changes and fast geometric updates. Combining these two approaches helps to balance solution stability and convergence speed. Utilizing the characteristic that the floating-point ambiguity solutions of the same GNSS satellite at both the ground and satellite ends have the same satellite-end phase deviation, the two types of floating-point ambiguity solutions are jointly modeled, achieving unified separation and estimation of floating-point ambiguity, integer ambiguity, and receiver-end and satellite-end phase deviations. Determining the joint estimation weights by combining the variance of each ambiguity floating-point solution effectively reflects the difference in observation accuracy between the ground and satellite ends, thereby further improving the accuracy and reliability of phase deviation estimation. After eliminating rank deficiency by fixing the reference satellite, inter-satellite single-difference phase deviation correction information relative to the reference satellite can be obtained, providing reliable support for ambiguity fixation in high-precision GNSS positioning.

[0053] For example, Figure 2 This is a comparison chart showing the convergence effect of the proposed method versus single GNSS ambiguity floating-point deconvergence, as provided in an embodiment of the invention. Figure 2 As shown, compared with single GNSS solution, the method of this invention, which integrates GNSS observation data and low-orbit satellite observation data, exhibits faster convergence speed and better stability in the ambiguity floating-point solution deviation convergence process, indicating that this invention can effectively improve the timeliness and accuracy of phase deviation correction information.

[0054] The method of this invention first uses a ground reference station to jointly filter GNSS satellite and low-Earth orbit (LEO) satellite observation data to obtain ambiguity floating-point solutions for the same GNSS satellite. Then, it uses an onboard receiver on the LEO satellite to solve the received GNSS observation data, obtaining the corresponding ambiguity floating-point solutions for the GNSS satellite. Further, based on the characteristic that the solution results for the same GNSS satellite at the ground and onboard ends share a common satellite-end phase deviation, the two types of ambiguity floating-point solutions are jointly modeled, and weighted estimation is performed by combining the variance of each floating-point solution. Finally, by setting a reference satellite to eliminate rank deficiency, the phase deviation correction information of each GNSS satellite relative to the reference satellite is obtained. This method combines the advantages of stable ground-end observations and rapid changes in the viewing angle at the LEO onboard end, which is beneficial for improving the convergence speed and accuracy of phase deviation estimation. It can be used for ambiguity fixation and phase deviation correction in high-precision GNSS positioning.

[0055] Example 2 Figure 3 This is a schematic diagram of a GNSS satellite phase deviation correction information estimation device provided in Embodiment 2 of the present invention. The device is applicable to situations where the phase deviation correction information of a GNSS satellite is estimated by combining ground reference sheets and observation data from low-orbit satellites. The device can be implemented by software and / or hardware and is generally integrated into an electronic device.

[0056] like Figure 3 As shown, the device includes: The first construction module 210 is used to construct a ground-end joint observation model based on ground observation data received by the ground reference station. The ground observation data includes GNSS satellite observation data and low-orbit satellite observation data. The second building module 220 is used to build a spaceborne observation model based on GNSS satellite observation data received from low-orbit satellites. The first solution module 230 is used to jointly solve the ground-side joint observation model and the satellite-side observation model to obtain the ground-side ambiguity floating-point solution and the corresponding variance of each GNSS satellite, as well as the satellite-side ambiguity floating-point solution and the corresponding variance. The third construction module 240 is used to construct a joint estimation equation set based on the ground-side ambiguity floating-point solution and the corresponding variance, and the spaceborne-side ambiguity floating-point solution and the corresponding variance. The second solution module 250 is used to select one satellite from all GNSS satellites as a reference satellite, solve the joint estimation equations, and obtain the phase deviation correction information of all other GNSS satellites relative to the reference satellite.

[0057] This embodiment provides a device for estimating phase deviation correction information of GNSS satellites, comprising: a first construction module for constructing a ground-side joint observation model based on ground observation data received from a ground reference station, wherein the ground observation data includes GNSS satellite observation data and low-Earth orbit (LEO) satellite observation data; a second construction module for constructing a spaceborne observation model based on GNSS satellite observation data received from LEO satellites; a first solution module for jointly solving the ground-side joint observation model and the spaceborne observation model to obtain the ground-side ambiguity floating-point solution and its corresponding variance for each GNSS satellite, as well as the spaceborne ambiguity floating-point solution and its corresponding variance; a third construction module for constructing a joint estimation equation set based on the ground-side ambiguity floating-point solution and its corresponding variance, and the spaceborne ambiguity floating-point solution and its corresponding variance; and a second solution module for selecting one satellite from all GNSS satellites as a reference satellite, solving the joint estimation equation set to obtain the phase deviation correction information of all other GNSS satellites relative to the reference satellite. This device integrates the dual observation and calculation results from ground reference stations and low-Earth orbit satellite-borne receivers, fully combining the advantages of stable ground-end observations and rapid changes in the viewing angle of low-Earth orbit satellite-borne receivers. It can achieve rapid convergence and high-precision estimation of GNSS satellite phase deviation correction information, solving the problems of low timeliness and low accuracy in GNSS satellite phase deviation estimation in existing technologies.

[0058] Furthermore, the observation equation of the ground-based joint observation model is: ; Among them, superscript Represents GNSS satellites, superscript Represents low-Earth orbit satellites. s The designation of the GNSS satellite. p This is the designation for low-Earth orbit satellites. r Indicates a ground reference station. IF Indicates an assembly without an ionosphere; This represents the ionospheric pseudorange observations of GNSS satellites from a ground reference station. This represents the carrier phase observations of the GNSS satellite from the ground reference station. This represents the ionospheric pseudorange observations of low-Earth orbit satellites from a ground reference station. This represents the carrier phase observations of a low-Earth orbit satellite from a ground reference station. This refers to the distance from the GNSS satellite to the ground reference station. This represents the distance from the low-Earth orbit satellite to the ground reference station. It is the speed of light in a vacuum. For the receiver clock bias of the reparameterized ground reference station, For the receiver clock bias of the reparameterized low-Earth orbit satellite, For GNSS satellite clock bias, For low-Earth orbit satellite clock bias; For GNSS satellite tropospheric projection functions, For low-Earth orbit satellites, (This is the tropospheric projection function.) ground reference station r Zenith tropospheric time delay, For GNSS satellite carrier wavelengths without ionosphere, For carrier waves of low-Earth orbit satellites without ionospheric combination wavelengths; This is the ambiguity floating-point solution for the GNSS satellites after ionospheric reparameterization from a ground reference station. This is the ambiguity floating-point solution for the ionosphere-free combination reparameterization of low-Earth orbit satellites from a ground reference station. This represents the noise in the ionospheric-free combined pseudorange observations of GNSS satellites from a ground reference station. The noise in the carrier phase observations of GNSS satellites from the ground reference station. This represents the noise in the ionospheric-free combined pseudorange observations of low-Earth orbit satellites from a ground reference station. This represents the noise in the carrier phase observations of low-orbit satellites from the ground reference station.

[0059] Furthermore, the parameter vector to be estimated for the ground-based joint observation model is: ; in, Let be the vector of parameters to be estimated. These are the three-dimensional coordinate parameters of the ground reference station.

[0060] Furthermore, the observation equation of the spaceborne observation model is: ; Among them, subscript l This refers to the onboard receiver of a low-Earth orbit satellite. This represents the observation value of the ionospheric-free combined pseudorange of GNSS satellites by the spaceborne receiver. This represents the carrier phase observation value of the GNSS satellite by the onboard receiver. This represents the distance from the GNSS satellite to the onboard receiver. The receiver clock bias of the reparameterized spaceborne receiver; This represents the noise in the ionospheric-free combined pseudorange observations of GNSS satellites by the spaceborne receiver. This refers to the noise in the carrier phase observations of the GNSS satellite by the onboard receiver. This is the floating-point solution of ambiguity for the GNSS satellite after ionospheric reparameterization by the spaceborne receiver.

[0061] Furthermore, the third building block 240 specifically includes: The decomposition unit is used to decompose the ground-side ambiguity floating-point solution and the satellite-side ambiguity floating-point solution into integer ambiguity components, receiver phase deviation, and satellite phase deviation, respectively. The determining unit is used to determine the joint estimation weights based on the variance of the ambiguity floating-point solution at the ground end and the variance of the ambiguity floating-point solution at the spaceborne end. The construction unit is used to combine the joint estimation weights, the integer ambiguity part, the receiver phase deviation, and the satellite phase deviation to construct a joint estimation equation set.

[0062] Furthermore, the expression equations for the ground-side ambiguity floating-point solution and the spaceborne ambiguity floating-point solution are as follows: ; in, This is the floating-point solution for the ambiguity at the satellite end, calculated by the receiving end. for The corresponding integer part, For the phase deviation at the receiving end, This refers to the phase deviation at the satellite end of a GNSS satellite. When the receiver is a ground observation station, the satellite end is either a GNSS satellite or a low-Earth orbit satellite. When the receiver is a low-Earth orbit satellite, the satellite end is a GNSS satellite.

[0063] Furthermore, the joint estimation equation set is as follows: ; in, Indicates ground reference station j Corresponding GNSS satellites s The fuzzy floating-point solution, j From 1 to m integers, m The number of ground reference stations, s From 1 to n integers, n The number of GNSS satellites, for The integer part; Indicates low-orbit satellites p The GNSS satellite corresponding to the onboard receiver s The fuzzy floating-point solution, p From 1 to k integers, k For the number of low-Earth orbit satellites, for The integer part; ground reference station j The receiver's coefficient matrix, For low-orbit satellites p The coefficient matrix of the spaceborne receiver; GNSS satellites corresponding to ground reference stations s The coefficient matrix, GNSS satellites corresponding to low Earth orbit satellites s The coefficient matrix; ground reference station j The phase deviation at the receiving end, For low-orbit satellites p Phase deviation of the satellite-borne receiver's receiving end. GNSS satellite s The phase deviation at the satellite end.

[0064] The aforementioned GNSS satellite phase deviation correction information estimation device can execute the GNSS satellite phase deviation correction information estimation method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method.

[0065] Example 3 Figure 4 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0066] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0067] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0068] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the phase deviation correction information estimation method for GNSS satellites.

[0069] In some embodiments, the GNSS satellite phase offset correction information estimation method can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the GNSS satellite phase offset correction information estimation method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the GNSS satellite phase offset correction information estimation method by any other suitable means (e.g., by means of firmware).

[0070] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0071] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0072] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM) or flash memory, optical fibers, compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0073] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device for displaying information to the user, such as a cathode ray tube (CRT) or liquid crystal display (LCD) monitor; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0074] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0075] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system. It addresses the shortcomings of traditional physical hosts and Virtual Private Server (VPS) services, such as high management difficulty and weak business scalability.

[0076] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0077] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for estimating phase deviation correction information of GNSS satellites, characterized in that, The method includes: A joint ground-based observation model is constructed based on ground observation data received from ground reference stations. The ground observation data includes GNSS satellite observation data and low-Earth orbit satellite observation data. Based on GNSS satellite observation data received from low-Earth orbit satellites, a satellite-borne observation model is constructed. The ground-side joint observation model and the satellite-side observation model are jointly solved to obtain the ground-side ambiguity floating-point solution and corresponding variance of each GNSS satellite, as well as the satellite-side ambiguity floating-point solution and corresponding variance. A joint estimation equation system is constructed based on the ground-side ambiguity floating-point solution and its corresponding variance, and the spaceborne-side ambiguity floating-point solution and its corresponding variance. One satellite is selected from all GNSS satellites as a reference satellite, and the joint estimation equations are solved to obtain the phase deviation correction information of all other GNSS satellites relative to the reference satellite.

2. The method according to claim 1, characterized in that, The observation equations of the ground-based joint observation model are as follows: ； Among them, superscript Represents GNSS satellites, superscript Represents low-Earth orbit satellites. s The designation of the GNSS satellite. p This is the designation for low-Earth orbit satellites. r Indicates a ground reference station. IF Indicates an assembly without an ionosphere; This represents the ionospheric pseudorange observations of GNSS satellites from a ground reference station. This represents the carrier phase observations of the GNSS satellite from the ground reference station. This represents the ionospheric pseudorange observations of low-Earth orbit satellites from a ground reference station. This represents the carrier phase observations of a low-Earth orbit satellite from a ground reference station. This refers to the distance from the GNSS satellite to the ground reference station. This represents the distance from the low-Earth orbit satellite to the ground reference station. It is the speed of light in a vacuum. For the receiver clock bias of the reparameterized ground reference station, For the receiver clock bias of the reparameterized low-Earth orbit satellite, For GNSS satellite clock bias, For low-Earth orbit satellite clock bias; For GNSS satellite tropospheric projection functions, For low-Earth orbit satellites, (This is the tropospheric projection function.) ground reference station r Zenith tropospheric time delay, For GNSS satellite carrier wavelengths without ionosphere, For carrier waves of low-Earth orbit satellites without ionospheric combination wavelengths; This is the ambiguity floating-point solution for the GNSS satellites after ionospheric reparameterization from a ground reference station. This is the ambiguity floating-point solution for the ionosphere-free combination reparameterization of low-Earth orbit satellites from a ground reference station. This represents the noise in the ionospheric-free combined pseudorange observations of GNSS satellites from a ground reference station. The noise in the carrier phase observations of GNSS satellites from the ground reference station. This represents the noise in the ionospheric-free combined pseudorange observations of low-Earth orbit satellites from a ground reference station. This represents the noise in the carrier phase observations of low-orbit satellites from the ground reference station.

3. The method according to claim 2, characterized in that, The parameter vector to be estimated for the ground-based joint observation model is: ； in, Let be the vector of parameters to be estimated. These are the three-dimensional coordinate parameters of the ground reference station.

4. The method according to claim 1, characterized in that, The observation equations of the satellite-borne observation model are as follows: ； Among them, subscript l This refers to the onboard receiver of a low-Earth orbit satellite. This represents the observation value of the ionospheric-free combined pseudorange of GNSS satellites by the spaceborne receiver. This represents the carrier phase observation value of the GNSS satellite by the onboard receiver. This represents the distance from the GNSS satellite to the onboard receiver. The receiver clock bias of the reparameterized spaceborne receiver; This represents the noise in the ionospheric-free combined pseudorange observations of GNSS satellites by the spaceborne receiver. This refers to the noise in the carrier phase observations of the GNSS satellite by the onboard receiver. This is the floating-point solution of ambiguity for the GNSS satellite after ionospheric reparameterization by the spaceborne receiver.

5. The method according to claim 1, characterized in that, The step of constructing a joint estimation equation set based on the ground-side ambiguity floating-point solution and its corresponding variance, and the spaceborne-side ambiguity floating-point solution and its corresponding variance, includes: The ground-side ambiguity floating-point solution and the satellite-side ambiguity floating-point solution are respectively decomposed into integer ambiguity components, receiver phase deviation, and satellite phase deviation; The joint estimation weights are determined based on the variance of the ambiguity floating-point solution at the ground end and the variance of the ambiguity floating-point solution at the spaceborne end. By combining the joint estimation weights, the integer ambiguity portion, the receiver phase deviation, and the satellite phase deviation, a joint estimation equation set is constructed.

6. The method according to claim 1 or 5, characterized in that, The equations expressing the ambiguity floating-point solution at the ground end and the ambiguity floating-point solution at the spaceborne end are as follows: ； in, This is the floating-point solution for the ambiguity at the satellite end, calculated by the receiving end. for The corresponding integer part, For the phase deviation at the receiving end, This refers to the phase deviation at the satellite end of a GNSS satellite. When the receiver is a ground observation station, the satellite end is either a GNSS satellite or a low-Earth orbit satellite. When the receiver is a low-Earth orbit satellite, the satellite end is a GNSS satellite.

7. The method according to claim 1 or 5, characterized in that, The joint estimation equation set is as follows: ； in, Indicates ground reference station j Corresponding GNSS satellites s The fuzzy floating-point solution, j From 1 to m integers, m The number of ground reference stations, s From 1 to n integers, n The number of GNSS satellites, for The integer part; Indicates low-orbit satellites p The GNSS satellite corresponding to the onboard receiver s The fuzzy floating-point solution, p From 1 to k integers, k For the number of low-Earth orbit satellites, for The integer part; ground reference station j The receiver's coefficient matrix, For low-orbit satellites p The coefficient matrix of the spaceborne receiver; GNSS satellites corresponding to ground reference stations s The coefficient matrix, GNSS satellites corresponding to low Earth orbit satellites s The coefficient matrix; ground reference station j The phase deviation at the receiving end, For low-orbit satellites p Phase deviation of the satellite-borne receiver's receiving end. GNSS satellite s The phase deviation at the satellite end.

8. A device for estimating phase deviation correction information for GNSS satellites, characterized in that, The device includes: The first construction module is used to construct a ground-end joint observation model based on ground observation data received from ground reference stations. The ground observation data includes GNSS satellite observation data and low-orbit satellite observation data. The second building module is used to construct a spaceborne observation model based on GNSS satellite observation data received from low-orbit satellites. The first solution module is used to jointly solve the ground-side joint observation model and the satellite-side observation model to obtain the ground-side ambiguity floating-point solution and corresponding variance of each GNSS satellite, as well as the satellite-side ambiguity floating-point solution and corresponding variance. The third construction module is used to construct a joint estimation equation set based on the ground-side ambiguity floating-point solution and its corresponding variance, and the spaceborne-side ambiguity floating-point solution and its corresponding variance. The second solution module is used to select one satellite from all GNSS satellites as a reference satellite, solve the joint estimation equations, and obtain the phase deviation correction information of all other GNSS satellites relative to the reference satellite.

9. An electronic device, characterized in that, The device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the GNSS satellite phase deviation correction information estimation method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the method for estimating phase deviation correction information of a GNSS satellite as described in any one of claims 1-7.

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