Enhanced information generation method and system fusing SBAS and PPP

Abstract

The invention discloses an enhanced information generation method and system fusing SBAS and PPP, and relates to a satellite navigation enhancement technology, and the method comprises the steps: receiving observation data of an SBAS and a global real-time monitoring station, and carrying out the file storage according to a standard format; carrying out precise orbit determination and forecasting by utilizing a stored standard format file and adopting a simplified dynamics method, and carrying out continuous calculation by taking one hour as a sliding window to generate a real-time precise orbit of the satellite; based on a satellite real-time precision orbit and real-time monitoring station data, a non-difference observation model and a sequential least square method are adopted for parameter solving, and a satellite real-time precision clock error is generated; solving an ephemeris and star clock differential correction number based on the broadcast ephemeris by using a satellite real-time precise orbit and a precise clock difference; and solving a covariance matrix and an integrity parameter by using the differential correction of the star calendar and the star clock. According to the method, two navigation enhancement technical means are fused, and the high-precision and high-integrity navigation positioning requirements are met.

Description

Technical Field

[0001] The present application relates to the field of satellite navigation enhancement technology, and in particular to a method and system for generating enhancement information integrating SBAS and PPP. Background Art

[0002] Since the birth of satellite navigation systems, due to different usage scenarios, precision enhancement and integrity enhancement technologies have been developed to meet users' needs for higher precision and integrity. Among them, precision enhancement mainly meets users' needs for high precision at the decimeter, centimeter or even millimeter level on the basis of basic services, such as the wide-area high-precision positioning system (PPP); integrity enhancement mainly warns users in a timely manner when the system fails or is abnormal, such as the satellite-based augmentation system (SBAS). There is still a lack of navigation enhancement service information that meets both precision enhancement and integrity enhancement.

[0003] The current precision enhancement technology cannot provide integrity services. Integrity enhancement technology can only provide meter-level positioning accuracy, and cannot solve the high-security and high-precision service needs of key national economic infrastructure and important industries such as high life safety, public safety, emergency areas, smart cities, etc. under the background of the new generation of information infrastructure. Summary of the invention

[0004] The embodiments of the present application provide a method and system for generating enhanced information integrating SBAS and PPP, so as to integrate the two navigation enhancement technical means, provide users with integrated enhanced information with high precision and high integrity, and meet the needs of high precision and high integrity navigation and positioning.

[0005] The embodiment of the present application provides a method for generating enhanced information integrating SBAS and PPP, including:

[0006] Receive SBAS and global real-time monitoring station observation data and store them in standard formats;

[0007] Using the stored standard format files, the simplified dynamics method is used for precise orbit determination and prediction, with a 1-hour sliding window for continuous calculation to generate the satellite's real-time precise orbit;

[0008] Based on the satellite's real-time precise orbit and real-time monitoring station data, the non-difference observation model and sequential least squares method are used to solve the parameters and generate the satellite's real-time precise clock error.

[0009] Using the satellite's real-time precise orbit and precise clock error, the ephemeris and clock error corrections based on the broadcast ephemeris are solved;

[0010] The covariance matrix and integrity parameters are solved using the ephemeris and clock differential corrections.

[0011] Optionally, receive SBAS and global real-time monitoring station observation data and store them in standard file formats including:

[0012] Receive SBAS monitoring station observation data in real time and store the data in files according to the RINEX standard format; receive global monitoring station data provided by the International Global Navigation Satellite System Service (IGS), the Global Continuous Monitoring and Assessment System (iGMAS) and other institutions in real time, and store the data in files according to the RINEX standard format.

[0013] Optionally, the standard format files are stored, and the simplified dynamics method is used for precise orbit determination and prediction. The calculation is performed continuously with a sliding window of 1 hour to generate the satellite real-time precise orbit, including:

[0014] Based on the standard format file of the stored observation data, the simplified dynamic method is used for precise orbit determination and prediction. Based on the orbit integration method, the satellite position of each epoch is [X j ,Y j ,Z j ] is expressed by the dynamic parameters at the initial time. The dynamic parameters at the initial time are first solved using formula (1), and the final position of the satellite at other times is derived. The 1-hour sliding window is used for continuous calculation, and the 3-hour arc segment of the forecast is selected as the real-time precise orbit output to generate the satellite real-time precise orbit.

[0015]

[0016] In the formula, and is the ionospheric-free combined pseudorange and carrier phase observation value from BeiDou satellite j to monitoring station i; is the geometric distance between monitoring station i and BeiDou satellite j, δt i ,δt j They represent the monitoring station clock error and BeiDou satellite real-time high-precision clock error, d error is the error that can be modeled and corrected, ε P and ε L represents the noise of pseudorange and carrier phase measurements, N j represents the integer ambiguity; λ represents the wavelength, [x i ,y i ,z i ] is the location information of monitoring station i; [X j ,Y j ,Z j ] is the real-time high-precision orbit of Beidou satellite j, c is the speed of light, and t is the epoch time.

[0017] Optionally, based on the satellite real-time precise orbit and real-time monitoring station data, the non-difference observation model and sequential least squares method are used to solve the parameters and generate the satellite real-time precise clock error, including:

[0018] Based on the satellite's real-time precise orbit and the known coordinates of the monitoring station, as well as the real-time observation data in a unified format, the non-difference observation model is adopted and the sequential least squares method is used to solve the satellite's precise clock error. The solution results are shown in equations (2) and (3):

[0019]

[0020] In the formula, δt j represents the satellite clock error, δt i Indicates the receiver clock error, N j represents the ambiguity parameter, t-1 and t are the two epochs before and after, L is the matrix of all observations in the same epoch, P is the weight matrix corresponding to the observations, are the estimated unknown parameters, is the cofactor matrix of the estimated unknown parameters, A is The corresponding coefficient matrix.

[0021] Optionally, using the satellite's real-time precise orbit and precise clock error, solving the ephemeris and clock error corrections based on the broadcast ephemeris includes:

[0022] Using the satellite's high-precision orbit and broadcast ephemeris, the satellite orbit differential correction number based on the broadcast ephemeris within an update period D is calculated.

[0023]

[0024] In the formula, O j Real-time high-precision orbit of Beidou satellite, is the satellite orbit calculated by broadcast ephemeris, are the unit vectors of the orbit in the X, Y, and Z directions respectively, t is the epoch time, t 0 The reference time for orbit differential corrections within the update period D;

[0025] Using the satellite high-precision clock error and broadcast ephemeris, the satellite clock error correction number based on the broadcast ephemeris within an update period D is calculated.

[0026]

[0027] Where, T j is the real-time high-precision clock error of Beidou satellite j, is the satellite clock error calculated by broadcast ephemeris, t is the epoch time, t 0 It is the reference time of the clock differential correction within the update period D.

[0028] Optionally, using the ephemeris and clock differential corrections to solve the covariance matrix and integrity parameters includes:

[0029] Using the ephemeris correction ΔO j , clock correction ΔT j and the low-orbit satellite clock error δt i , calculate the residuals of all pseudorange observations of GNSS satellite j observed by monitoring station i at epoch time t

[0030]

[0031] In the formula, is the original pseudorange observation value, is the pseudorange observation value calculated using the differential correction number;

[0032] Count all residual errors ΔP of monitoring station i observing GNSS satellite j within an update period D i j Variance of (t) Calculate the covariance matrix of the ephemeris and clock differential corrections

[0033]

[0034] in, is the unit direction vector from monitoring station i to GNSS satellite j, and M is the number of monitoring stations that can effectively observe GNSS satellite j.

[0035] Count all pseudorange residuals within an update period D The mean and variance satisfy:

[0036]

[0037] The integrity parameter dual frequency ranging error DFRE j satisfy:

[0038]

[0039] The embodiment of the present application further proposes an enhanced information generation system integrating SBAS and PPP, including a processor and a memory, wherein a computer program is stored on the memory, and when the computer program is executed by the processor, the steps of the enhanced information generation method integrating SBAS and PPP as described above are implemented.

[0040] The method of the embodiment of the present application integrates two navigation enhancement technical means to provide users with integrated enhanced information with high precision and high integrity, meeting the needs of high precision and high integrity navigation and positioning.

[0041] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present application. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0043] Figure 1 The following is a schematic diagram of the basic process of the enhanced information generation method integrating SBAS and PPP in this application. DETAILED DESCRIPTION

[0044] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0045] The method exemplified in this application integrates the wide-area high-precision positioning system and the satellite-based augmentation system technology, and uses the ground monitoring station data to generate navigation augmentation information with high precision and high integrity, so as to realize the processing and generation of augmentation information in the fusion mode. The specific embodiment of this application provides a method for generating augmentation information integrating SBAS and PPP, such as Figure 1 As shown, the following steps are included:

[0046] In step S101, SBAS and global real-time monitoring station observation data are received and stored in a file in a standard format. In some embodiments, SBAS monitoring station observation data is received in real time and the data is stored in a file in a RINEX standard format; global monitoring station data provided by the International Global Navigation Satellite System Service (IGS), the Global Continuous Monitoring and Assessment System (iGMAS) and other institutions are received in real time and the data is stored in a file in a RINEX standard format.

[0047] In step S102, the simplified dynamics method is used to perform precise orbit determination and prediction based on the stored standard format file, and the real-time precise orbit of the satellite is generated by continuously solving the problem with a sliding window of 1 hour. In some embodiments, based on the stored standard format file of observation data, the simplified dynamics method is used to perform precise orbit determination and prediction, and the satellite position [X] of each epoch is calculated based on the orbit integration method. j ,Y j ,Z j ] is expressed by the dynamic parameters at the initial time. The dynamic parameters at the initial time are first solved using formula (1), and the final position of the satellite at other times is derived. The 1-hour sliding window is used for continuous calculation, and the 3-hour arc segment of the forecast is selected as the real-time precise orbit output to generate the satellite real-time precise orbit.

[0048]

[0049] In the formula, and is the ionospheric-free combined pseudorange and carrier phase observation value from BeiDou satellite j to monitoring station i; is the geometric distance between monitoring station i and BeiDou satellite j, δt i ,δt j They represent the monitoring station clock error and BeiDou satellite real-time high-precision clock error, d error is the error that can be modeled and corrected, ε P and ε L represents the noise of pseudorange and carrier phase measurements, N j represents the integer ambiguity; λ represents the wavelength, [x i ,y i ,z i ] is the location information of monitoring station i; [X j ,Y j ,Z j ] is the real-time high-precision orbit of Beidou satellite j, c is the speed of light, and t is the epoch time.

[0050] In step S103, based on the satellite real-time precise orbit and real-time monitoring station data, the non-difference observation model and sequential least squares method are used to solve the parameters and generate the satellite real-time precise clock error. In some embodiments, based on the satellite real-time precise orbit and the known coordinates of the monitoring station, and the real-time observation data in a unified format, the non-difference observation model is used to solve the satellite precise clock error using the sequential least squares method, and the solution results are as shown in equations (2) and (3):

[0051]

[0052] In the formula, δt j represents the satellite clock error, δt i Indicates the receiver clock error, Nj represents the ambiguity parameter, t-1 and t are the two epochs before and after, L is the matrix of all observations in the same epoch, P is the weight matrix corresponding to the observations, are the estimated unknown parameters, is the cofactor matrix of the estimated unknown parameters, A is The corresponding coefficient matrix.

[0053] In step S104, the satellite real-time precise orbit and precise clock error are used to solve the satellite ephemeris and clock differential correction number based on the broadcast ephemeris. In some embodiments, the satellite high-precision orbit and broadcast ephemeris are used to solve and obtain the satellite orbit differential correction number based on the broadcast ephemeris within an update period D.

[0054]

[0055] In the formula, O j Real-time high-precision orbit of Beidou satellite, is the satellite orbit calculated by broadcast ephemeris, are the unit vectors of the orbit in the X, Y, and Z directions respectively, t is the epoch time, t 0 The reference time for orbit differential corrections within the update period D;

[0056] Using the satellite high-precision clock error and broadcast ephemeris, the satellite clock error correction number based on the broadcast ephemeris within an update period D is calculated.

[0057]

[0058] Where, T j is the real-time high-precision clock error of Beidou satellite j, is the satellite clock error calculated by broadcast ephemeris, t is the epoch time, t 0 It is the reference time of the clock differential correction within the update period D.

[0059] In step S105, the covariance matrix and integrity parameters are solved using the ephemeris and clock differential corrections. j , clock correction ΔT j and the low-orbit satellite clock error δt i , calculate the residual ΔP of all pseudorange observations of GNSS satellite j observed by monitoring station i at epoch time t i j (t):

[0060]

[0061] Where P ij (t) is the original pseudorange observation value, is the pseudorange observation value calculated using the differential correction number;

[0062] Count all residual errors ΔP of monitoring station i observing GNSS satellite j within an update period D i j Variance of (t) Calculate the covariance matrix of the ephemeris and clock differential corrections

[0063]

[0064] in, is the unit direction vector from monitoring station i to GNSS satellite j, and M is the number of monitoring stations that can effectively observe GNSS satellite j.

[0065] Count all pseudo-range residuals ΔP within an update period D i j The mean of (t) and variance satisfy:

[0066]

[0067] The integrity parameter dual frequency ranging error DFRE j satisfy:

[0068]

[0069] The enhanced information generated by the present application can be used for both high-precision positioning and satellite-based enhanced positioning. Compared with the traditional satellite-based augmentation system, the method of the present application has better accuracy in the ephemeris and clock differential corrections. Compared with the traditional wide-area high-precision positioning system, it can use integrity information to assist in judging the reliability of the positioning results, and provide users with integrated enhanced information with high precision and high integrity, meeting the needs of high-precision and high-integrity navigation and positioning.

[0070] The embodiment of the present application further proposes an enhanced information generation system integrating SBAS and PPP, including a processor and a memory, wherein a computer program is stored on the memory, and when the computer program is executed by the processor, the steps of the enhanced information generation method integrating SBAS and PPP as described above are implemented.

[0071] It should be noted that in the various embodiments of the present application, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0072] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0073] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0074] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A method for generating enhanced information integrating SBAS and PPP, characterized in that: include: Receive SBAS and global real-time monitoring station observation data and store them in standard formats; Using the stored standard format files, the simplified dynamics method is used for precise orbit determination and prediction, with a 1-hour sliding window for continuous calculation to generate the satellite's real-time precise orbit; Based on the satellite's real-time precise orbit and real-time monitoring station data, the non-difference observation model and sequential least squares method are used to solve the parameters and generate the satellite's real-time precise clock error. Using the satellite's real-time precise orbit and precise clock error, the ephemeris and clock error corrections based on the broadcast ephemeris are solved; The covariance matrix and integrity parameters are solved using the ephemeris and clock differential corrections.

2. The method for generating enhanced information integrating SBAS and PPP according to claim 1, characterized in that: Receive SBAS and global real-time monitoring station observation data and store them in standard formats including: Receive SBAS monitoring station observation data in real time and store the data in files according to the RINEX standard format; receive global monitoring station data provided by the International Global Navigation Satellite System Service (IGS), the Global Continuous Monitoring and Assessment System (iGMAS) and other institutions in real time, and store the data in files according to the RINEX standard format.

3. The method for generating enhanced information integrating SBAS and PPP as claimed in claim 2, characterized in that: Using the stored standard format files, the simplified dynamics method is used for precise orbit determination and prediction, with a 1-hour sliding window for continuous calculation, to generate the satellite's real-time precise orbit, including: Based on the standard format file of the stored observation data, the simplified dynamic method is used for precise orbit determination and prediction. Based on the orbit integration method, the satellite position of each epoch is [X j ,Y j ,Z j ] is expressed by the dynamic parameters at the initial time. The dynamic parameters at the initial time are first solved using formula (1), and the final position of the satellite at other times is derived. The 1-hour sliding window is used for continuous calculation, and the 3-hour arc segment of the forecast is selected as the real-time precise orbit output to generate the satellite real-time precise orbit. In the formula, and is the ionospheric-free combined pseudorange and carrier phase observation value from BeiDou satellite j to monitoring station i; is the geometric distance between monitoring station i and BeiDou satellite j, δt i ,δt j They represent the monitoring station clock error and BeiDou satellite real-time high-precision clock error, d error is the error that can be modeled and corrected, ε P and ε L represents the noise of pseudorange and carrier phase measurements, N j represents the integer ambiguity; λ represents the wavelength, [x i ,y i ,z i ] is the location information of monitoring station i; [X j ,Y j ,Z j ] is the real-time high-precision orbit of Beidou satellite j, c is the speed of light, and t is the epoch time.

4. The method for generating enhanced information integrating SBAS and PPP as claimed in claim 3, characterized in that: Based on the satellite real-time precise orbit and real-time monitoring station data, the non-difference observation model and sequential least squares method are used to solve the parameters and generate the satellite real-time precise clock error, including: Based on the satellite's real-time precise orbit and the known coordinates of the monitoring station, as well as the real-time observation data in a unified format, the non-difference observation model is adopted and the sequential least squares method is used to solve the satellite's precise clock error. The solution results are shown in equations (2) and (3): In the formula, δt j represents the satellite clock error, δt i Indicates the receiver clock error, N j represents the ambiguity parameter, t-1 and t are the two epochs before and after, L is the matrix of all observations in the same epoch, P is the weight matrix corresponding to the observations, are the estimated unknown parameters, is the cofactor matrix of the estimated unknown parameters, A is The corresponding coefficient matrix.

5. The method for generating enhanced information integrating SBAS and PPP as claimed in claim 4, characterized in that: Using the satellite's real-time precise orbit and precise clock error, the ephemeris and clock corrections based on the broadcast ephemeris are solved, including: Using the satellite precise orbit and broadcast ephemeris, the satellite orbit differential correction number based on the broadcast ephemeris within an update period D is calculated. In the formula, O j Real-time high-precision orbit of Beidou satellite j, is the satellite orbit calculated by broadcast ephemeris, are the unit vectors of the orbit in the X, Y, and Z directions respectively, t is the epoch time, and t0 is the reference time of the orbit differential correction number within the update period D; Using the satellite precise clock error and broadcast ephemeris, the satellite clock error differential correction number based on the broadcast ephemeris within an update period D is calculated. Where, T j is the real-time high-precision clock error of Beidou satellite j, is the satellite clock error calculated from the broadcast ephemeris, t is the epoch time, and t0 is the reference time of the clock error correction number within the update period D.

6. The method for generating enhanced information integrating SBAS and PPP as claimed in claim 5, characterized in that: Solving the covariance matrix and integrity parameters using the ephemeris and clock differential corrections includes: Using the ephemeris correction ΔO j , clock correction ΔT j and the low-orbit satellite clock error δt i , calculate the residuals of all pseudorange observations of GNSS satellite j observed by monitoring station i at epoch time t In the formula, is the original pseudorange observation value, is the pseudorange observation value calculated using the differential correction number; Count all residuals of monitoring station i observing GNSS satellite j within an update period D Variance Calculate the covariance matrix of the ephemeris and clock differential corrections in, is the unit direction vector from monitoring station i to GNSS satellite j, and M is the number of monitoring stations that can effectively observe GNSS satellite j. Count all pseudorange residuals within an update period D The mean and variance satisfy: Integrity parameters Dual frequency ranging error DFRE j satisfy:

7. An enhanced information generation system integrating SBAS and PPP, characterized in that: The method comprises a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the steps of the method for generating enhanced information by integrating SBAS and PPP as claimed in any one of claims 1 to 6 are implemented.

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