A GNSS elastic code deviation calculation method and system applicable to all scenarios

Abstract

The present invention relates to the field of satellite navigation technology, and specifically discloses a GNSS elastic code bias calculation method and system applicable to all scenarios, wherein the method comprises: based on the satellite signal power change amount of the GNSS monitoring station, analyzing the signal power change amplitude of the monitoring station to determine the state of the satellite signal power; constructing a high-time-resolution code bias state equation and an observation equation, and realizing high-time-resolution code bias estimation of the GNSS based on epoch-by-epoch code bias estimation using Kalman filtering, an improved phase-smoothing pseudorange method, and ionospheric spherical harmonic functions; calculating the elastic code bias elasticity factor of the GNSS based on the GNSS signal power state and the code bias change amplitude of the GNSS, product accuracy, and time series stability; and determining the elastic code bias value of the GNSS according to the satellite signal power state, the high-time-resolution code bias estimation of the GNSS, and the elastic code bias elasticity factor of the GNSS.

Description

Technical Field

[0001] The present invention relates to the field of satellite navigation technology, and in particular to a GNSS elastic code deviation calculation method and system applicable to all scenarios. Background Art

[0002] Satellite radio navigation systems are inherently vulnerable to obstruction, interference, and spoofing. The risk of service denial and degradation for space-based positioning, navigation, and timing (PNT) systems is increasing, posing significant potential risks to the operation and development of critical societal infrastructure. Satellite power boosting technology, a primary method for enhancing Global Navigation Satellite System (GNSS) signals, impacts the robustness and availability of PNT services, also known as resilient power. GPS satellites possess robust radio reconfiguration capabilities. Currently, 31 second- and third-generation GPS satellites provide services, 19 of which have power boosting capabilities. The Beidou Navigation Satellite System (BDS) is currently provided by a combined service of BDS-2 and BDS-3. Both BDS-2 and BDS-3 have the ability to boost the power of the B3 center frequency signal. While maintaining long-term civilian signal broadcasting, the B3 signal also incorporates modern military signals. This solves the problem of medium-power combining of civilian and military frequencies, meeting the requirements for medium-power combining of multiple onboard transmitters and smooth B3 signal transitions.

[0003] Code bias, as the time delay of navigation signals between the satellite and the receiver, is one of the main sources of error in GNSS PNT services. During the elastic power period, the magnitude of changes in BDS and GPS code bias ranges from sub-nanoseconds to hundreds of nanoseconds. The low-time-resolution code bias products provided by existing institutions cannot guarantee a rapid response to code bias changes. The hourly broadcast ephemeris code bias parameters and the daily or even monthly post-processing code bias products will inevitably affect the satellite availability and the overall performance of the PNT service during the satellite elastic power period. Traditional code bias products are difficult to meet the user's full-time PNT service needs. Combined with the existing elastic power judgment method, the present invention provides a GNSS elastic code bias calculation method and system suitable for all scenarios. Summary of the Invention

[0004] To achieve the purpose of the present invention, this application provides a GNSS elastic code deviation calculation method applicable to all scenarios, including:

[0005] Step S1: Analyzing the amplitude of the signal power change of the GNSS monitoring station based on the satellite signal power change of the GNSS monitoring station to determine the state of the satellite signal power;

[0006] Step S2: Construct high-time-resolution code bias state equations and observation equations, and estimate code biases epoch by epoch based on Kalman filtering, an improved phase-smoothed pseudorange method, and ionospheric spherical harmonics to achieve high-time-resolution code bias estimation for GNSS.

[0007] Step S3: Calculating the GNSS elastic code bias elasticity factor based on the GNSS signal power status and the GNSS code bias variation amplitude, product accuracy, and time series stability;

[0008] Step S4: determining a GNSS elastic code bias value according to the state of the satellite signal power, the high time resolution code bias estimate of the GNSS, and the elastic code bias elasticity factor of the GNSS.

[0009] In some specific embodiments, step S1 includes:

[0010] Step S11: obtaining a time series of the ratio of the GNSS signal carrier power at each frequency point to the noise in a 1 Hz bandwidth;

[0011] Step S12: establishing a functional relationship between the ratio of the carrier power of the fitted GNSS signal to the noise in a 1 Hz bandwidth and the satellite elevation angle;

[0012] Step S13: Calculate the mathematical expectation of the ratio of the GNSS signal carrier power to the noise in a 1 Hz bandwidth, and determine whether the ratio of the measured GNSS signal carrier power to the noise in a 1 Hz bandwidth exceeds a certain range of the mathematical expectation;

[0013] Step S14: determining whether the satellite signal power is in a normal power state or an elastic power state by setting a threshold.

[0014] In some specific embodiments, in step S12, the functional relationship between the ratio of the carrier power of the fitted GNSS signal to the noise in a 1 Hz bandwidth and the satellite elevation angle is determined according to the following formula:

[0015] ;

[0016] Where, SW r,j It represents the ratio of the GNSS signal carrier power at the jth frequency point of the monitoring station to the noise in the 1 Hz bandwidth. r Represents the receiver, represents the satellite altitude angle, 、 、 、 and represents the model coefficient, Noise represents the ratio of the GNSS signal carrier power to the noise in a 1 Hz bandwidth.

[0017] In some specific embodiments, step S13 includes: when the satellite power is stable, the measured value of the ratio of the GNSS signal carrier power to the noise in the 1 Hz bandwidth is close to the mathematical expectation, and when the satellite power is elastic, the measured value will exceed the mathematical expectation by a certain range, which is determined according to the following formula:

[0018] ;

[0019] in, is the expected range gap value, H 0 is normal power, H 1 is the elastic power.

[0020] In some specific embodiments, the elastic code deviation elasticity factor is determined according to the following formula:

[0021] ;

[0022] Where, H Indicates the GNSS signal power status, Represents epoch t Time code deviation variance, Represents epoch t The standard deviation of daily code deviation within the continuous arc segment of the time history, Δ t Represents epoch t The absolute difference between the time code deviation value and the average value within the historical continuous arc segment.

[0023] To achieve the same invention purpose, the present application also provides a GNSS elastic code deviation calculation system applicable to all scenarios, including:

[0024] GNSS elastic power judgment module: used to analyze the amplitude of the signal power change of the monitoring station based on the satellite signal power change of the GNSS monitoring station to determine the status of the satellite signal power;

[0025] High time resolution code bias estimation module: used to construct high time resolution code bias state equations and observation equations, and to achieve high time resolution code bias estimation for GNSS based on epoch-by-epoch Kalman filtering, an improved phase-smoothed pseudorange method, and ionospheric spherical harmonics.

[0026] Elastic code bias elasticity factor generation module: used to calculate the elastic code bias elasticity factor of GNSS based on the GNSS signal power status and the GNSS code bias change amplitude, product accuracy and time series stability;

[0027] The elastic code deviation value calculation module is used to determine the elastic code deviation value of the GNSS according to the state of the satellite signal power, the high time resolution code deviation estimation of the GNSS and the elastic code deviation elasticity factor of the GNSS.

[0028] In some specific embodiments, the GNSS elastic power determination module is configured to perform the following steps:

[0029] Step S11: obtaining a time series of the ratio of the GNSS signal carrier power at each frequency point to the noise in a 1 Hz bandwidth;

[0030] Step S12: establishing a functional relationship between the ratio of the carrier power of the fitted GNSS signal to the noise in a 1 Hz bandwidth and the satellite elevation angle;

[0031] Step S13: Calculate the mathematical expectation of the ratio of the GNSS signal carrier power to the noise in a 1 Hz bandwidth, and determine whether the ratio of the measured GNSS signal carrier power to the noise in a 1 Hz bandwidth exceeds a certain range of the mathematical expectation;

[0032] Step S14: determining whether the satellite signal power is in a normal power state or an elastic power state by setting a threshold.

[0033] In some specific embodiments, in step S12, the functional relationship between the ratio of the carrier power of the fitted GNSS signal to the noise in a 1 Hz bandwidth and the satellite elevation angle is determined according to the following formula:

[0034] ;

[0035] Where, SW r,j It represents the ratio of the GNSS signal carrier power at the jth frequency point of the monitoring station to the noise in the 1 Hz bandwidth. r Represents the receiver, represents the satellite altitude angle, 、 、 、 and represents the model coefficient, Noise represents the ratio of the GNSS signal carrier power to the noise in a 1 Hz bandwidth.

[0036] In some specific embodiments, step S13 includes: when the satellite power is stable, the measured value of the ratio of the GNSS signal carrier power to the noise in the 1 Hz bandwidth is close to the mathematical expectation, and when the satellite power is elastic, the measured value will exceed the mathematical expectation by a certain range, which is determined according to the following formula:

[0037] ;

[0038] in, is the expected range gap value, H 0 is normal power, H 1 is the elastic power.

[0039] In some specific embodiments, the elastic code deviation elasticity factor is determined according to the following formula:

[0040] ;

[0041] Where, H Indicates the GNSS signal power status, Represents epoch t Time code deviation variance, Represents epoch t The standard deviation of daily code deviation within the continuous arc segment of the time history, Δ t Represents epoch t The absolute difference between the time code deviation value and the average value within the historical continuous arc segment.

[0042] Beneficial effects of the above technical solution:

[0043] The present invention provides a GNSS elastic code deviation calculation method and system applicable to all scenarios. By using filtered epoch-by-epoch estimation to analyze the code deviation state changes, and with reference to the characteristics of traditional code deviation products, the adaptability of the code deviation is improved, and the code deviation product is developed from a single low time resolution mode to a self-adjusting and self-improving mode with dynamic adaptive time resolution adjustment. It has the characteristics of high efficiency, high precision, high integrity, high continuity and high availability, and has the ability to cope with different scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0045] Figure 1 A flowchart of a GNSS elastic code deviation calculation method applicable to all scenarios provided by an embodiment of the present invention;

[0046] Figure 2 A schematic diagram of the basic framework of a GNSS elastic code deviation calculation method applicable to all scenarios provided by an embodiment of the present invention;

[0047] Figure 3 A calculation flow chart of a GNSS elastic code deviation calculation method applicable to all scenarios provided by an embodiment of the present invention;

[0048] Figure 4 A flowchart of elastic power determination for a GNSS elastic code deviation calculation method applicable to all scenarios provided by an embodiment of the present invention;

[0049] Figure 5 A schematic diagram of the structure of a GNSS elastic code deviation calculation system applicable to all scenarios is provided in accordance with an embodiment of the present invention. DETAILED DESCRIPTION

[0050] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0051] Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar symbols throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0052] Example 1

[0053] An embodiment of the present invention provides a GNSS elastic code deviation calculation method applicable to all scenarios, referring to Figure 1 、 2 Shown, including:

[0054] Step S1: Based on the satellite signal power change of the GNSS monitoring station, the amplitude of the signal power change of the monitoring station is analyzed to determine the state of the satellite signal power.

[0055] In a specific embodiment of the present invention, step S1 includes:

[0056] Step S11: obtaining a time series of the ratio of the GNSS signal carrier power at each frequency point to the noise in a 1 Hz bandwidth;

[0057] Step S12: establishing a functional relationship between the ratio of the carrier power of the fitted GNSS signal to the noise in a 1 Hz bandwidth and the satellite elevation angle;

[0058] Step S13: Calculate the mathematical expectation of the ratio of the GNSS signal carrier power to the noise in a 1 Hz bandwidth, and determine whether the ratio of the measured GNSS signal carrier power to the noise in a 1 Hz bandwidth exceeds a certain range of the mathematical expectation;

[0059] Step S14: determining whether the satellite signal power is in a normal power state or an elastic power state by setting a threshold.

[0060] In a specific embodiment of the present invention, in step S12, the daily repetition characteristic of GNSS satellite observation values ​​is utilized, and based on the real-time streaming observation data provided by the IGS monitoring station, a time series of the ratio of the GNSS signal carrier power to the noise in a 1 Hz bandwidth at each frequency point is obtained. Then, combined with the satellite elevation angle of the corresponding monitoring station calculated using the broadcast ephemeris, the functional relationship between the ratio of the GNSS signal carrier power to the noise in a 1 Hz bandwidth and the satellite elevation angle is determined according to the following formula:

[0061] ;

[0062] Where, SW r,j It represents the ratio of the GNSS signal carrier power at the jth frequency point of the monitoring station to the noise in the 1 Hz bandwidth. r Represents the receiver, represents the satellite altitude angle, 、 、 、 and represents the model coefficient, Noise represents the ratio of the GNSS signal carrier power to the noise in a 1 Hz bandwidth.

[0063] In a specific embodiment of the present invention, step S13 includes: when the satellite power is stable, the measured value of the ratio of the GNSS signal carrier power to the noise in the 1 Hz bandwidth is close to the mathematical expectation, and when the satellite power is elastic, the measured value will exceed the mathematical expectation by a certain range, which is determined according to the following formula:

[0064] ;

[0065] in, is the expected range gap value, H 0 is normal power, H 1 is the elastic power.

[0066] Specifically, when the satellite power is stable, the C / N0 observation value changes relatively steadily, and the measured value is close to the mathematical expectation. However, when the satellite power is elastic, the measured value will exceed the mathematical expectation by a certain range, which can be expressed as:

[0067] ;

[0068] in, is the expected range difference value. The C / N0 observation value is the ratio of the GNSS signal carrier power to the noise in a 1 Hz bandwidth. It can be used as an important parameter to measure signal quality. The change in the C / N0 value of a single receiver can be used as an indicator to monitor power changes.

[0069] The elastic power probability statistics can be formed by grouping and counting the actual results of n groups of receiver monitoring stations in the IGS monitoring station ,Right now:

[0070] ;

[0071] Furthermore, by setting the threshold (significance level) to judge the elastic power, that is:

[0072] ;

[0073] By solving the corresponding parameters based on the long-term characteristics of GNSS monitoring stations and combining them with satellite elastic power examples, a satellite elastic power judgment model can be established based on each monitoring station. On this basis, a real-time satellite elastic power monitoring system based on a threshold detection mechanism can be constructed by selecting a certain number of evenly distributed global monitoring stations. When a certain number of selected monitoring stations simultaneously observe a jump in the C / N0 observed value of the same type of satellite signal, it can be considered that the system has experienced elastic power.

[0074] Step S2: Construct high time resolution code bias state equation and observation equation, estimate code bias by epoch based on Kalman filter and improved phase smoothing pseudorange method and ionospheric spherical harmonic function to achieve high time resolution code bias estimation of GNSS.

[0075] Specifically, the Kalman filter estimates the code bias on an epoch-by-epoch basis, including the code bias value and the code bias variance.

[0076] See also Figure 3 As shown, the code bias calculation engine constructs a mathematical model and utilizes Kalman filtering to generate high-time-resolution code bias products, including code bias values ​​and code bias variances, on an epoch-by-epoch basis. The generation of the flexible code bias product involves the integration of flexible optimization of the calculation engine, flexible adjustment of the function model, and flexible optimization of the stochastic model. It provides the code bias RI and code bias values. The code bias calculation engine uses filtering to estimate code bias state changes on an epoch-by-epoch basis. Using the characteristics of traditional code bias products as a reference, it improves the adaptability of the code bias, evolving the code bias product from a single low-time-resolution model to a self-adjusting and self-improving model with dynamic adaptive time resolution adjustment. The code bias RI parameter is set to reflect characteristics such as availability, continuity, integrity, robustness, and accuracy. To enhance efficiency, the self-adjusting code bias includes two different time resolution states: normal code bias and flexible code bias. Therefore, the flexible code bias product can meet the minimum requirements for accuracy, integrity, and continuity of PNT services, even in complex scenarios such as elastic power.

[0077] Figure 4This is the generation process for flexible code deviation products. Based on the traditional code deviation product framework, the flexible code deviation solution uses a high-time-resolution filtered code deviation solution as the calculation engine, employs elastic adjustment of function models and elastic optimization of random models, and incorporates background field information such as elastic power and other complex external environments or uncertainties. This enables the code deviation product to achieve high efficiency, high accuracy, high integrity, high continuity, and high availability. The flexible code deviation product is capable of handling diverse scenarios.

[0078] The mathematical model of high time resolution code bias is the basis of the elastic code bias product engine. Based on this, different state products of elastic code bias products are generated. The high time resolution code bias of any observation channel is t The moment can be expressed as:

[0079] ;

[0080] The elastic code deviation (RI) is calculated based on indicators such as the GNSS signal power status, the variation of the code deviation, product accuracy, and time series stability, and is expressed as follows:

[0081] ;

[0082] Where, H 0 and H 1 indicates code deviation elasticity and normal state, 、 、 and represent coefficient scaling factors, which are generated by linear regression calculations of observation data under normal conditions for one year. Represents epoch t Time code deviation variance, Represents epoch t The standard deviation (STD) of the daily code deviation within the continuous arc end of the time history, Represents epoch t The absolute difference between the code deviation value at the moment and the historical average value within the continuous arc end. A code deviation RI between 0-0.5 indicates a normal state, between 0.5-1.0 indicates a flexible state, 1.0 indicates a warning state, and N / A indicates an abnormal state.

[0083] It should be noted that the GNSS elastic code deviation products applicable to the present invention in all scenarios are usually in normal and elastic states, and their time resolutions are different. When the code deviation RI value is in the normal state, it is consistent with the time resolution of the code deviation products of each analysis agency, and provides a code deviation product of Tianjie. When the code deviation product status is elastic or warning, it is in the elastic code deviation state and provides high time resolution code deviation products on an epoch-by-epoch basis. In the abnormal state, the code deviation is set to be unavailable to downstream users, indicating that an abnormality has occurred in the code deviation engine.

[0084] Step S3: Calculate the GNSS elastic code deviation elasticity factor based on the GNSS signal power status and the GNSS code deviation change amplitude, product accuracy and time series stability.

[0085] In a specific embodiment of the present invention, the elastic code deviation elasticity factor is determined according to the following formula:

[0086] ;

[0087] Where, H Indicates the GNSS signal power status, Represents epoch t Time code deviation variance, Represents epoch t The standard deviation of daily code deviation within the continuous arc segment of the time history, Δ t Represents epoch t The absolute difference between the time code deviation value and the average value within the historical continuous arc segment.

[0088] To reflect the availability, continuity, integrity, robustness, and accuracy of code deviation, the elastic code deviation (RI) incorporates background field information such as elastic power and other external complex environments or uncertainties, and is calculated based on indicators such as GNSS signal power status, code deviation variation, product accuracy, and time series stability.

[0089] Step S4: determining a GNSS elastic code bias value according to the state of the satellite signal power, the high time resolution code bias estimate of the GNSS, and the elastic code bias elasticity factor of the GNSS.

[0090] The elastic code deviation value uses the elastic adjustment of function models and the elastic optimization of random models as means, is based on the traditional code deviation product framework, and uses the high-time-resolution filtered code deviation solution as the calculation engine. It has the ability to cope with different scenarios and includes four states: elastic, normal, warning, and abnormal.

[0091] The elastic code deviation product can solve the problems of fault prevention and system recovery in complex external environments or uncertain factors, and can still meet the minimum requirements of users for accuracy, integrity and continuity of PNT services even in complex scenarios such as elastic power.

[0092] Example 2

[0093] An embodiment of the present invention provides a GNSS elastic code deviation calculation system applicable to all scenarios, referring to Figure 5 Shown, including:

[0094] GNSS flexible power judgment module 10: used to analyze the amplitude of the signal power change of the monitoring station based on the satellite signal power change of the GNSS monitoring station to determine the state of the satellite signal power;

[0095] High time resolution code bias estimation module 20: used to construct high time resolution code bias state equation and observation equation, and to achieve high time resolution code bias estimation of GNSS based on epoch-by-epoch code bias estimation by Kalman filtering, an improved phase smoothing pseudorange method, and ionospheric spherical harmonics.

[0096] The elastic code deviation elasticity factor generating module 30 is used to calculate the elastic code deviation elasticity factor of the GNSS based on the GNSS signal power state and the GNSS code deviation change amplitude, product accuracy and time series stability;

[0097] The elastic code bias value calculation module 40 is configured to determine the elastic code bias value of the GNSS according to the state of the satellite signal power, the high time resolution code bias estimation of the GNSS, and the elastic code bias elasticity factor of the GNSS.

[0098] In some specific embodiments, the GNSS elastic power determination module 10 is configured to perform the following steps:

[0099] Step S11: obtaining a time series of the ratio of the GNSS signal carrier power at each frequency point to the noise in a 1 Hz bandwidth;

[0100] Step S12: establishing a functional relationship between the ratio of the carrier power of the fitted GNSS signal to the noise in a 1 Hz bandwidth and the satellite elevation angle;

[0101] Step S13: Calculate the mathematical expectation of the ratio of the GNSS signal carrier power to the noise in a 1 Hz bandwidth, and determine whether the ratio of the measured GNSS signal carrier power to the noise in a 1 Hz bandwidth exceeds a certain range of the mathematical expectation;

[0102] Step S14: determining whether the satellite signal power is in a normal power state or an elastic power state by setting a threshold.

[0103] In some specific embodiments, in step S12, the functional relationship between the ratio of the carrier power of the fitted GNSS signal to the noise in a 1 Hz bandwidth and the satellite elevation angle is determined according to the following formula:

[0104] ;

[0105] Where, SW r,j It represents the ratio of the GNSS signal carrier power at the jth frequency point of the monitoring station to the noise in the 1 Hz bandwidth. r Represents the receiver, represents the satellite altitude angle, 、 、 、 and represents the model coefficient, Noise represents the ratio of the GNSS signal carrier power to the noise in a 1 Hz bandwidth.

[0106] In some specific embodiments, step S13 includes: when the satellite power is stable, the measured value of the ratio of the GNSS signal carrier power to the noise in the 1 Hz bandwidth is close to the mathematical expectation, and when the satellite power is elastic, the measured value will exceed the mathematical expectation by a certain range, which is determined according to the following formula:

[0107] ;

[0108] in, is the expected range gap value, H 0 is normal power, H 1 is the elastic power.

[0109] In some specific embodiments, the elastic code deviation elasticity factor is determined according to the following formula:

[0110] ;

[0111] Where, H Indicates the GNSS signal power status, Represents epoch t Time code deviation variance, Represents epoch t The standard deviation of daily code deviation within the continuous arc segment of the time history, Δ t Represents epoch t The absolute difference between the time code deviation value and the average value within the historical continuous arc segment.

[0112] The present invention provides a GNSS elastic code deviation calculation system suitable for all scenarios. By using filtered epoch-by-epoch estimation to analyze the code deviation state changes, and with reference to the characteristics of traditional code deviation products, the adaptability of the code deviation is improved, so that the code deviation product is developed from a single low time resolution mode to a self-adjusting and self-improving mode with dynamic adaptive time resolution adjustment. It has the characteristics of high efficiency, high precision, high integrity, high continuity and high availability, and has the ability to cope with different scenarios.

[0113] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

[0114] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same and similar parts between the various embodiments can be referred to each other. The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing terminal device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the functions in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing terminal device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device, so that a series of operation steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for implementing the process in the process. Figure 1 a process or multiple processes and / or boxes Figure 1The steps of the functions specified in one or more blocks. Although preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they are aware of the basic inventive concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention. Finally, it should be noted that, in this document, relational terms such as first and second, etc. are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or terminal device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article, or terminal device. Without further limitation, an element defined by the phrase "comprising a..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes the element.

[0115] The method and apparatus provided by the present invention are introduced in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method and core ideas of the present invention. At the same time, for those skilled in the art, according to the ideas of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the contents of this specification should not be understood as limiting the present invention.

[0116] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "example," "specific example," "a specific embodiment," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, schematic representations of terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0117] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A GNSS elastic code deviation calculation method applicable to all scenarios, characterized by: include: Step S1: Analyzing the amplitude of the signal power change of the GNSS monitoring station based on the satellite signal power change of the GNSS monitoring station to determine the state of the satellite signal power; Step S2: Construct high-time-resolution code bias state equations and observation equations, and estimate code biases epoch by epoch based on Kalman filtering, an improved phase-smoothed pseudorange method, and ionospheric spherical harmonics to achieve high-time-resolution code bias estimation for GNSS. Step S3: Calculating the GNSS elastic code bias elasticity factor based on the GNSS signal power status and the GNSS code bias variation amplitude, product accuracy, and time series stability; Step S4: determining a GNSS elastic code bias value according to the state of the satellite signal power, the high time resolution code bias estimate of the GNSS, and the elastic code bias elasticity factor of the GNSS.

2. The GNSS elastic code deviation calculation method applicable to all scenarios according to claim 1 is characterized in that: Step S1 includes: Step S11: obtaining a time series of the ratio of the GNSS signal carrier power at each frequency point to the noise in a 1 Hz bandwidth; Step S12: establishing a functional relationship between the ratio of the carrier power of the fitted GNSS signal to the noise in a 1 Hz bandwidth and the satellite elevation angle; Step S13: Calculate the mathematical expectation of the ratio of the GNSS signal carrier power to the noise in a 1 Hz bandwidth, and determine whether the ratio of the measured GNSS signal carrier power to the noise in a 1 Hz bandwidth exceeds a certain range of the mathematical expectation; Step S14: determining whether the satellite signal power is in a normal power state or an elastic power state by setting a threshold.

3. The GNSS elastic code deviation calculation method applicable to all scenarios according to claim 2 is characterized in that: In step S12, the functional relationship between the ratio of the carrier power of the fitted GNSS signal to the noise in a 1 Hz bandwidth and the satellite elevation angle is determined according to the following formula: ； Where, SW r,j It represents the ratio of the GNSS signal carrier power at the jth frequency point of the monitoring station to the noise in the 1 Hz bandwidth. r Represents the receiver, represents the satellite altitude angle, 、 、 、 and represents the model coefficient, Noise is the ratio of the GNSS signal carrier power to the noise in a 1 Hz bandwidth.

4. The GNSS elastic code deviation calculation method applicable to all scenarios according to claim 3 is characterized in that: Step S13 includes: when the satellite power is stable, the measured value of the ratio of the GNSS signal carrier power to the noise in the 1 Hz bandwidth is close to the mathematical expectation, while when the satellite power is elastic, the measured value will exceed the mathematical expectation by a certain range, which is determined according to the following formula: ； in, is the expected range gap value, H 0 is normal power, H 1 is the elastic power.

5. The GNSS elastic code deviation calculation method applicable to all scenarios according to claim 1 is characterized in that: The elastic code deviation elasticity factor is determined according to the following formula: ； Where, H Indicates the GNSS signal power status, Represents epoch t Time code deviation variance, Represents epoch t The standard deviation of daily code deviation within the continuous arc segment of the time history, Δ t Represents epoch t The absolute difference between the time code deviation value and the average value within the historical continuous arc segment.

6. A GNSS elastic code deviation calculation system applicable to all scenarios, characterized by: include: GNSS elastic power judgment module: used to analyze the amplitude of the signal power change of the monitoring station based on the satellite signal power change of the GNSS monitoring station to determine the status of the satellite signal power; High time resolution code bias estimation module: used to construct high time resolution code bias state equations and observation equations, and to achieve high time resolution code bias estimation for GNSS based on epoch-by-epoch Kalman filtering, an improved phase-smoothed pseudorange method, and ionospheric spherical harmonics. Elastic code bias elasticity factor generation module: used to calculate the elastic code bias elasticity factor of GNSS based on the GNSS signal power status and the GNSS code bias change amplitude, product accuracy and time series stability; The elastic code deviation value calculation module is used to determine the elastic code deviation value of the GNSS according to the state of the satellite signal power, the high time resolution code deviation estimation of the GNSS and the elastic code deviation elasticity factor of the GNSS.

7. The GNSS elastic code deviation calculation system applicable to all scenarios according to claim 6 is characterized in that: The GNSS elastic power judgment module is used to perform the following steps: Step S11: obtaining a time series of the ratio of the GNSS signal carrier power at each frequency point to the noise in a 1 Hz bandwidth; Step S12: establishing a functional relationship between the ratio of the carrier power of the fitted GNSS signal to the noise in a 1 Hz bandwidth and the satellite elevation angle; Step S13: Calculate the mathematical expectation of the ratio of the GNSS signal carrier power to the noise in a 1 Hz bandwidth, and determine whether the ratio of the measured GNSS signal carrier power to the noise in a 1 Hz bandwidth exceeds a certain range of the mathematical expectation; Step S14: determining whether the satellite signal power is in a normal power state or an elastic power state by setting a threshold.

8. The GNSS elastic code deviation calculation system applicable to all scenarios according to claim 7 is characterized in that: In step S12, the functional relationship between the ratio of the carrier power of the fitted GNSS signal to the noise in a 1 Hz bandwidth and the satellite elevation angle is determined according to the following formula: ； Where, SW r,j It represents the ratio of the GNSS signal carrier power at the jth frequency point of the monitoring station to the noise in the 1 Hz bandwidth. r Represents the receiver, represents the satellite altitude angle, 、 、 、 and represents the model coefficient, Noise represents the ratio of the GNSS signal carrier power to the noise in a 1 Hz bandwidth.

9. The GNSS elastic code deviation calculation system applicable to all scenarios according to claim 8, characterized in that: Step S13 includes: when the satellite power is stable, the measured value of the ratio of the GNSS signal carrier power to the noise in the 1 Hz bandwidth is close to the mathematical expectation, while when the satellite power is elastic, the measured value will exceed the mathematical expectation by a certain range, which is determined according to the following formula: ； in, is the expected range gap value, H 0 is normal power, H 1 is the elastic power.

10. The GNSS elastic code deviation calculation system applicable to all scenarios according to claim 6, characterized in that: The elastic code deviation elasticity factor is determined according to the following formula: ； Where, H Indicates the GNSS signal power status, Represents epoch t Time code deviation variance, Represents epoch t The standard deviation of daily code deviation within the continuous arc segment of the time history, Δ t Represents epoch t The absolute difference between the time code deviation value and the average value within the historical continuous arc segment.

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