A method and system for monitoring accuracy of data differential post-processing in a navigation system

Abstract

The present invention discloses a method and system for monitoring the accuracy of data differential post-processing in a navigation system. The method comprises: acquiring data in the navigation system, performing differential processing on the data, generating differentially processed data, wherein the differentially processed data comprises: a pseudorange value measured at a first observation frequency, a pseudorange value measured at a second observation frequency, tropospheric delay, ambient air pressure, ambient temperature, ambient humidity, a measured pseudorange and a theoretical pseudorange; setting a pseudorange change evaluation model, and calculating a pseudorange change evaluation value according to the differentially processed data, wherein the pseudorange change evaluation model comprises a nonlinear function of ionospheric delay, a nonlinear estimation function of tropospheric delay and a nonlinear estimation function of receiver noise and multipath effect; performing accuracy evaluation on the differentially processed data according to the pseudorange change evaluation value, and correcting the differentially processed data according to the evaluation result.

Description

Technical Field

[0001] The present invention belongs to the technical field of navigation data processing, and more specifically, relates to a method and system for monitoring the accuracy of data differential post-processing in a navigation system. Background Art

[0002] Navigation data generally refers to data received from the Global Navigation Satellite System (GNSS) or other location service systems (such as BeiDou, GLONASS, Galileo, etc.). This data includes the satellite's position, speed, time information, and the position and clock error of the receiving device. Navigation data plays a key role in various applications, including but not limited to:

[0003] Positioning and navigation: Use navigation data for real-time positioning and navigation, such as vehicle navigation, aviation navigation, ship navigation, etc.

[0004] Time synchronization: Time synchronization using precise time information provided by satellites, such as precise time standards and synchronized communication equipment.

[0005] Scientific research: In scientific research, navigation data is used for research and experiments in the fields of geophysics, atmospheric science, space astronomy, etc.

[0006] Intelligent Transportation: In intelligent transportation systems, navigation data is used for traffic management, route planning, and traffic flow analysis.

[0007] However, the accuracy of monitoring navigation data in the prior art is low and inefficient. Summary of the invention

[0008] In order to solve the above technical problems, the present invention proposes a method for monitoring the accuracy of data differential post-processing in a navigation system, comprising:

[0009] Acquire data in the navigation system, and perform differential processing on the data to generate differentially processed data, wherein the differentially processed data includes: speed of light, satellite clock error, receiver clock error, ionospheric delay, first observation frequency, second observation frequency, pseudorange value measured at the first observation frequency, pseudorange value measured at the second observation frequency, tropospheric delay, ambient air pressure, ambient temperature, ambient humidity, measured pseudorange and theoretical pseudorange;

[0010] Setting a pseudorange change evaluation model, and calculating a pseudorange change evaluation value according to the differentially processed data, wherein the pseudorange change evaluation model includes a nonlinear function of ionospheric delay, a nonlinear estimation function of tropospheric delay, and a nonlinear estimation function of receiver noise and multipath effect;

[0011] According to the pseudorange change evaluation value, the accuracy of the data after the difference processing is evaluated, and according to the evaluation result, the data after the difference processing is corrected.

[0012] Furthermore, the pseudorange change assessment model includes:

[0013] ,

[0014] in, is the pseudorange change evaluation value, is the speed of light, is the satellite clock error, is the receiver clock error, is the ionospheric delay, is a nonlinear function of ionospheric delay, which is used to describe the complex ionospheric nonlinear effects. is the first observation frequency, is the second observation frequency, is the pseudorange value measured at the first observation frequency, is the pseudorange value measured at the second observation frequency, is the tropospheric delay, is the nonlinear estimation function of tropospheric delay, which is used to describe the nonlinear response of tropospheric delay under different air pressures. is the ambient air pressure, is the ambient temperature, is the ambient humidity, is the receiver noise value, is the nonlinear estimation function of receiver noise and multipath effect, which is used to describe the nonlinear characteristics of receiver noise and multipath effect under different pseudorange conditions. is the measured pseudorange, is the theoretical pseudorange.

[0015] Furthermore, the nonlinear function of the ionospheric delay is include:

[0016] ,

[0017] in, is the first adjustment factor for ionospheric delay, is the second adjustment factor for ionospheric delay, is the fourth adjustment factor for ionospheric delay, is the fifth adjustment factor for ionospheric delay, is the third adjustment factor for ionospheric delay.

[0018] Furthermore, the nonlinear estimation function of the tropospheric delay is include:

[0019] ,

[0020] in, is the first adjustment factor for tropospheric delay, is the second adjustment factor for tropospheric delay, is the third adjustment factor for tropospheric delay, is the fourth adjustment factor for tropospheric delay, is the fifth adjustment factor for tropospheric delay, is the sixth adjustment factor for tropospheric delay, is the seventh adjustment factor for tropospheric delay.

[0021] Furthermore, the nonlinear evaluation function of the receiver noise and multipath effect is include:

[0022] ,

[0023] in, is the first adjustment factor for receiver noise and multipath effects, is the second adjustment factor for receiver noise and multipath effects, is the third adjustment factor for receiver noise and multipath effects, is the fourth adjustment factor for receiver noise and multipath effects.

[0024] Furthermore, generating the differentially processed data also includes: performing format conversion and screening on the differentially processed data to remove abnormal values.

[0025] Furthermore, an interpolation method is used to fill in the missing data points in the differentially processed data to ensure the integrity of the data.

[0026] Furthermore, an accuracy threshold is set, and when the pseudorange change evaluation value is less than or equal to the accuracy threshold, the data after the difference processing meets the accuracy requirement.

[0027] Furthermore, each adjustment factor is fitted by the gradient descent method.

[0028] The present invention also proposes an accuracy monitoring system for data differential post-processing in a navigation system, comprising:

[0029] A data acquisition module is used to acquire data in the navigation system and perform differential processing on the data to generate differentially processed data, wherein the differentially processed data includes: light speed, satellite clock error, receiver clock error, ionospheric delay, first observation frequency, second observation frequency, pseudorange value measured at the first observation frequency, pseudorange value measured at the second observation frequency, tropospheric delay, ambient air pressure, ambient temperature, ambient humidity, measured pseudorange and theoretical pseudorange;

[0030] Setting a model module, used for setting a pseudorange change evaluation model, and calculating a pseudorange change evaluation value according to the differentially processed data, wherein the pseudorange change evaluation model includes a nonlinear function of ionospheric delay, a nonlinear estimation function of tropospheric delay, and a nonlinear estimation function of receiver noise and multipath effect;

[0031] The accuracy evaluation module is used to perform accuracy evaluation on the differentially processed data according to the pseudorange change evaluation value, and to correct the differentially processed data according to the evaluation result.

[0032] Compared with the prior art, the above technical solution conceived by the present invention has the following beneficial effects:

[0033] The present invention sets a pseudorange change evaluation model, and calculates a pseudorange change evaluation value based on the differentially processed data, wherein the pseudorange change evaluation model includes a nonlinear function of ionospheric delay, a nonlinear estimation function of tropospheric delay, and a nonlinear estimation function of receiver noise and multipath effect; according to the pseudorange change evaluation value, the accuracy of the differentially processed data is evaluated, and according to the evaluation result, the differentially processed data is corrected. Through the above technical solution, the present invention comprehensively considers the influence of various factors on the accuracy of navigation data, and can more comprehensively understand the complexity of navigation data, thereby more effectively processing navigation data and improving accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 is a flow chart of the method of embodiment 1 of the present invention;

[0035] Figure 2 It is a system structure diagram of embodiment 2 of the present invention. DETAILED DESCRIPTION

[0036] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0037] The method provided by the present invention can be implemented in the following terminal environment, and the terminal may include one or more of the following components: a processor, a storage medium, and a display screen. The storage medium stores at least one instruction, and the instruction is loaded and executed by the processor to implement the method described in the following embodiment.

[0038] The processor may include one or more processing cores. The processor uses various interfaces and lines to connect various parts in the entire terminal, and executes various functions of the terminal and processes data by running or executing instructions, programs, code sets or instruction sets stored in the storage medium, and calling data stored in the storage medium.

[0039] The storage medium may include a random access memory (RAM) or a read-only memory (ROM). The storage medium may be used to store instructions, programs, codes, code sets or instructions.

[0040] The display is used to show the interactive cross-section of each application.

[0041] All subscripts in the formulas of the present invention are only used to distinguish parameters and have no actual meaning.

[0042] In addition, those skilled in the art can understand that the structure of the above terminal does not constitute a limitation on the terminal, and the terminal may include more or fewer components, or combine certain components, or arrange the components differently. For example, the terminal also includes components such as a radio frequency circuit, an input unit, a sensor, an audio circuit, and a power supply, which will not be described in detail here.

[0043] Example 1

[0044] like Figure 1 As shown, the present invention proposes a method for monitoring the accuracy of data differential post-processing in a navigation system, comprising:

[0045] Step 101, acquiring data in a navigation system, and performing differential processing on the data to generate differentially processed data, wherein the differentially processed data includes: light speed, satellite clock error, receiver clock error, ionospheric delay, first observation frequency, second observation frequency, pseudorange value measured at the first observation frequency, pseudorange value measured at the second observation frequency, tropospheric delay, ambient air pressure, ambient temperature, ambient humidity, measured pseudorange and theoretical pseudorange;

[0046] Specifically, generating the data after differential processing also includes: performing format conversion and screening on the data after differential processing to remove abnormal values.

[0047] Specifically, an interpolation method is used to fill in the missing data points in the differentially processed data to ensure the integrity of the data.

[0048] Step 102, setting a pseudorange change evaluation model, and calculating a pseudorange change evaluation value according to the differentially processed data, wherein the pseudorange change evaluation model includes a nonlinear function of ionospheric delay, a nonlinear estimation function of tropospheric delay, and a nonlinear estimation function of receiver noise and multipath effect;

[0049] Specifically, the pseudorange change evaluation model includes:

[0050] ,

[0051] in, is the pseudorange change evaluation value, is the speed of light, is the satellite clock error, is the receiver clock error, is the ionospheric delay, is a nonlinear function of ionospheric delay, which is used to describe the complex ionospheric nonlinear effects. is the first observation frequency, is the second observation frequency, is the pseudorange value measured at the first observation frequency (for example, is The pseudorange value measured at the frequency (usually 1575.42MHz) is the pseudorange value measured at the second observation frequency (for example, is The pseudorange value measured at the frequency (usually 1227.60MHz) is the tropospheric delay, is the nonlinear estimation function of tropospheric delay, which is used to describe the nonlinear response of tropospheric delay under different air pressures. is the ambient air pressure, is the ambient temperature, is the ambient humidity, is the receiver noise value, is the nonlinear estimation function of receiver noise and multipath effect, which is used to describe the nonlinear characteristics of receiver noise and multipath effect under different pseudorange conditions. is the measured pseudorange, is the theoretical pseudorange.

[0052] Ionospheric delay is one of the main sources of error in satellite signal propagation. The ionosphere has different refraction effects on electromagnetic waves of different frequencies. This effect depends not only on the frequency, but also on the density of the ionosphere, solar activity, geographical location and time. Therefore, this embodiment proposes a nonlinear function of ionospheric delay: , which is used to describe the complex ionospheric nonlinear effects, as follows:

[0053] Specifically, the nonlinear function of the ionospheric delay is include:

[0054] ,

[0055] in, is the first adjustment factor for ionospheric delay, is the second adjustment factor for ionospheric delay, is the fourth adjustment factor for ionospheric delay, is the fifth adjustment factor for ionospheric delay, is the third adjustment factor for ionospheric delay.

[0056] The nonlinear function of the ionospheric delay Has the following effects:

[0057] Inter-frequency interaction effect: By introducing the parameter , , The model can capture the complex interaction effects between different frequencies. frequency (1575.42 MHz) and The effect of frequency (1227.60 MHz) is different, and a simple linear model cannot accurately describe this difference. After introducing the nonlinear factor, the model can better reflect the nonlinear effect of frequency change on ionospheric delay and improve the accuracy of pseudorange calculation.

[0058] Adaptability to spatiotemporal variation: Parameters The introduction of takes into account the changes of ionospheric delay with spatial position and time. In particular, the ionospheric characteristics vary significantly at different latitudes of the earth, in different seasons, or during the day and night. The model describes these changes in detail through nonlinear terms, allowing the positioning system to maintain high accuracy in various environments.

[0059] Tropospheric delay is mainly related to meteorological factors such as atmospheric pressure, temperature and humidity. Tropospheric delay varies significantly with altitude and weather conditions. Therefore, this embodiment proposes a nonlinear estimation function for tropospheric delay: , which is used to describe the nonlinear response of the tropospheric delay at different air pressures, is as follows:

[0060] Specifically, the nonlinear estimation function of the tropospheric delay is include:

[0061] ,

[0062] in, is the first adjustment factor for tropospheric delay, is the second adjustment factor for tropospheric delay, is the third adjustment factor for tropospheric delay, is the fourth adjustment factor for tropospheric delay, is the fifth adjustment factor for tropospheric delay, is the sixth adjustment factor for tropospheric delay, is the seventh adjustment factor for tropospheric delay.

[0063] The nonlinear estimation function of the tropospheric delay is Has the following effects:

[0064] Complex meteorological conditions affect: parameters , , , , The introduction of enables the model to capture the complex nonlinear response of tropospheric delay under different meteorological conditions. For example, in weather conditions with significant changes in air pressure, such as storms and sudden heavy rains, traditional models may have difficulty accurately estimating tropospheric delay. By introducing these parameters, the model can provide more accurate tropospheric delay corrections under various meteorological conditions.

[0065] Altitude dependence: The model also considers the effect of altitude on tropospheric delay. Especially in mountainous areas and aviation flight scenarios, the effect of altitude on delay is very significant. By introducing the parameter and ,The model can adapt to the altitude changes, provide more precise delay correction,and improve the positioning accuracy in these scenarios.

[0066] Receiver noise and multipath effects are another major factor affecting the accuracy of pseudorange measurements, especially in urban environments or other scenarios with more signal reflections. Therefore, this embodiment proposes a nonlinear evaluation function for receiver noise and multipath effects: , as shown below:

[0067] Specifically, the nonlinear evaluation function of the receiver noise and multipath effect is include:

[0068] ,

[0069] in, is the first adjustment factor for receiver noise and multipath effects, is the second adjustment factor for receiver noise and multipath effects, is the third adjustment factor for receiver noise and multipath effects, is the fourth adjustment factor for receiver noise and multipath effects.

[0070] The nonlinear evaluation function of the receiver noise and multipath effect Has the following effects:

[0071] Dynamic Noise Adaptation: By introducing , , , The model can more accurately describe the changes of noise under different pseudorange conditions. The noise level often changes dynamically with the strength of the received signal and the pseudorange measurement. Traditional models are difficult to capture this dynamic characteristic. After introducing complex nonlinear terms, the model can adapt to various noise levels and reduce pseudorange errors.

[0072] Nonlinear processing of multipath effects: Multipath effects are particularly significant in urban and highly reflective scenes. Traditional linear models are difficult to effectively suppress the errors caused by this effect. By introducing the above parameters, the model can better describe the complex effects caused by differences in signal path lengths, thereby effectively reducing the impact of multipath effects on pseudorange measurements.

[0073] Specifically, each adjustment factor is fitted by the gradient descent method.

[0074] Step 103: perform accuracy evaluation on the differentially processed data according to the pseudorange change evaluation value, and correct the differentially processed data according to the evaluation result.

[0075] Specifically, an accuracy threshold is set, and when the pseudorange change evaluation value is less than or equal to the accuracy threshold, the data after the difference processing meets the accuracy requirement.

[0076] Example 2

[0077] like Figure 2 As shown, the embodiment of the present invention further proposes an accuracy monitoring system for data differential post-processing in a navigation system, comprising:

[0078] A data acquisition module is used to acquire data in the navigation system and perform differential processing on the data to generate differentially processed data, wherein the differentially processed data includes: light speed, satellite clock error, receiver clock error, ionospheric delay, first observation frequency, second observation frequency, pseudorange value measured at the first observation frequency, pseudorange value measured at the second observation frequency, tropospheric delay, ambient air pressure, ambient temperature, ambient humidity, measured pseudorange and theoretical pseudorange;

[0079] Specifically, generating the data after differential processing also includes: performing format conversion and screening on the data after differential processing to remove abnormal values.

[0080] Specifically, an interpolation method is used to fill in the missing data points in the differentially processed data to ensure the integrity of the data.

[0081] Setting a model module, used for setting a pseudorange change evaluation model, and calculating a pseudorange change evaluation value according to the differentially processed data, wherein the pseudorange change evaluation model includes a nonlinear function of ionospheric delay, a nonlinear estimation function of tropospheric delay, and a nonlinear estimation function of receiver noise and multipath effect;

[0082] Specifically, the pseudorange change evaluation model includes:

[0083] ,

[0084] in, is the pseudorange change evaluation value, is the speed of light, is the satellite clock error, is the receiver clock error, is the ionospheric delay, is a nonlinear function of ionospheric delay, which is used to describe the complex ionospheric nonlinear effects. is the first observation frequency, is the second observation frequency, is the pseudorange value measured at the first observation frequency, is the pseudorange value measured at the second observation frequency, is the tropospheric delay, is the nonlinear estimation function of tropospheric delay, which is used to describe the nonlinear response of tropospheric delay under different air pressures. is the ambient air pressure, is the ambient temperature, is the ambient humidity, is the receiver noise value, is the nonlinear estimation function of receiver noise and multipath effect, which is used to describe the nonlinear characteristics of receiver noise and multipath effect under different pseudorange conditions. is the measured pseudorange, is the theoretical pseudorange.

[0085] Specifically, the nonlinear function of the ionospheric delay is include:

[0086] ,

[0087] in, is the first adjustment factor for ionospheric delay, is the second adjustment factor for ionospheric delay, is the fourth adjustment factor for ionospheric delay, is the fifth adjustment factor for ionospheric delay, is the third adjustment factor for ionospheric delay.

[0088] Specifically, the nonlinear estimation function of the tropospheric delay is include:

[0089] ,

[0090] in, is the first adjustment factor for tropospheric delay, is the second adjustment factor for tropospheric delay, is the third adjustment factor for tropospheric delay, is the fourth adjustment factor for tropospheric delay, is the fifth adjustment factor for tropospheric delay, is the sixth adjustment factor for tropospheric delay, is the seventh adjustment factor for tropospheric delay.

[0091] Specifically, the nonlinear evaluation function of the receiver noise and multipath effect is include:

[0092] ,

[0093] in, is the first adjustment factor for receiver noise and multipath effects, is the second adjustment factor for receiver noise and multipath effects, is the third adjustment factor for receiver noise and multipath effects, is the fourth adjustment factor for receiver noise and multipath effects.

[0094] Specifically, each adjustment factor is fitted by the gradient descent method.

[0095] The accuracy evaluation module is used to perform accuracy evaluation on the differentially processed data according to the pseudorange change evaluation value, and to correct the differentially processed data according to the evaluation result.

[0096] Specifically, an accuracy threshold is set, and when the pseudorange change evaluation value is less than or equal to the accuracy threshold, the data after the difference processing meets the accuracy requirement.

[0097] Example 3

[0098] The embodiment of the present invention further provides a storage medium storing a plurality of instructions, wherein the instructions are used to implement the accuracy monitoring method of data differential post-processing in a navigation system.

[0099] Optionally, in this embodiment, the above storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group.

[0100] Optionally, in this embodiment, the storage medium is configured to store a program code for executing the method steps: Step 101, acquiring data in a navigation system, and performing differential processing on the data to generate differentially processed data, wherein the differentially processed data includes: light speed, satellite clock error, receiver clock error, ionospheric delay, first observation frequency, second observation frequency, pseudorange value measured at the first observation frequency, pseudorange value measured at the second observation frequency, tropospheric delay, ambient air pressure, ambient temperature, ambient humidity, measured pseudorange and theoretical pseudorange;

[0101] Specifically, generating the data after differential processing also includes: performing format conversion and screening on the data after differential processing to remove abnormal values.

[0102] Specifically, an interpolation method is used to fill in the missing data points in the differentially processed data to ensure the integrity of the data.

[0103] Step 102, setting a pseudorange change evaluation model, and calculating a pseudorange change evaluation value according to the differentially processed data, wherein the pseudorange change evaluation model includes a nonlinear function of ionospheric delay, a nonlinear estimation function of tropospheric delay, and a nonlinear estimation function of receiver noise and multipath effect;

[0104] Specifically, the pseudorange change evaluation model includes:

[0105] ,

[0106] in, is the pseudorange change evaluation value, is the speed of light, is the satellite clock error, is the receiver clock error, is the ionospheric delay, is a nonlinear function of ionospheric delay, which is used to describe the complex ionospheric nonlinear effects. is the first observation frequency, is the second observation frequency, is the pseudorange value measured at the first observation frequency, is the pseudorange value measured at the second observation frequency, is the tropospheric delay, is the nonlinear estimation function of tropospheric delay, which is used to describe the nonlinear response of tropospheric delay under different air pressures. is the ambient air pressure, is the ambient temperature, is the ambient humidity, is the receiver noise value, is the nonlinear estimation function of receiver noise and multipath effect, which is used to describe the nonlinear characteristics of receiver noise and multipath effect under different pseudorange conditions. is the measured pseudorange, is the theoretical pseudorange.

[0107] Specifically, the nonlinear function of the ionospheric delay is include:

[0108] ,

[0109] in, is the first adjustment factor for ionospheric delay, is the second adjustment factor for ionospheric delay, is the fourth adjustment factor for ionospheric delay, is the fifth adjustment factor for ionospheric delay, is the third adjustment factor for ionospheric delay.

[0110] Specifically, the nonlinear estimation function of the tropospheric delay is include:

[0111] ,

[0112] in, is the first adjustment factor for tropospheric delay, is the second adjustment factor for tropospheric delay, is the third adjustment factor for tropospheric delay, is the fourth adjustment factor for tropospheric delay, is the fifth adjustment factor for tropospheric delay, is the sixth adjustment factor for tropospheric delay, is the seventh adjustment factor for tropospheric delay.

[0113] Specifically, the nonlinear evaluation function of the receiver noise and multipath effect is include:

[0114] ,

[0115] in, is the first adjustment factor for receiver noise and multipath effects, is the second adjustment factor for receiver noise and multipath effects, is the third adjustment factor for receiver noise and multipath effects, is the fourth adjustment factor for receiver noise and multipath effects.

[0116] Specifically, each adjustment factor is fitted by the gradient descent method.

[0117] Step 103: perform accuracy evaluation on the differentially processed data according to the pseudorange change evaluation value, and correct the differentially processed data according to the evaluation result.

[0118] Specifically, an accuracy threshold is set, and when the pseudorange change evaluation value is less than or equal to the accuracy threshold, the data after the difference processing meets the accuracy requirement.

[0119] Example 4

[0120] An embodiment of the present invention also proposes an electronic device, including a processor and a storage medium connected to the processor, wherein the storage medium stores multiple instructions, and the instructions can be loaded and executed by the processor to enable the processor to execute a method for monitoring the accuracy of data differential post-processing in a navigation system.

[0121] Specifically, the electronic device of this embodiment may be a computer terminal, and the computer terminal may include: one or more processors, and a storage medium.

[0122] Among them, the storage medium can be used to store software programs and modules, such as a method for monitoring the accuracy of post-processing of data differential in a navigation system in an embodiment of the present invention, and the corresponding program instructions / modules. The processor executes various functional applications and data processing by running the software programs and modules stored in the storage medium, that is, realizing the above-mentioned method for monitoring the accuracy of post-processing of data differential in a navigation system. The storage medium may include a high-speed random storage medium, and may also include a non-volatile storage medium, such as one or more magnetic storage systems, flash memory, or other non-volatile solid-state storage media. In some instances, the storage medium may further include a storage medium remotely arranged relative to the processor, and these remote storage media may be connected to the terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0123] The processor can call the information and application stored in the storage medium through the transmission system to execute the method steps: Step 101, obtain data in the navigation system, and perform differential processing on the data to generate differentially processed data, wherein the differentially processed data includes: light speed, satellite clock error, receiver clock error, ionospheric delay, first observation frequency, second observation frequency, pseudorange value measured at the first observation frequency, pseudorange value measured at the second observation frequency, tropospheric delay, ambient air pressure, ambient temperature, ambient humidity, measured pseudorange and theoretical pseudorange;

[0124] Specifically, generating the data after differential processing also includes: performing format conversion and screening on the data after differential processing to remove abnormal values.

[0125] Specifically, an interpolation method is used to fill in the missing data points in the differentially processed data to ensure the integrity of the data.

[0126] Step 102, setting a pseudorange change evaluation model, and calculating a pseudorange change evaluation value according to the differentially processed data, wherein the pseudorange change evaluation model includes a nonlinear function of ionospheric delay, a nonlinear estimation function of tropospheric delay, and a nonlinear estimation function of receiver noise and multipath effect;

[0127] Specifically, the pseudorange change evaluation model includes:

[0128] ,

[0129] in, is the pseudorange change evaluation value, is the speed of light, is the satellite clock error, is the receiver clock error, is the ionospheric delay, is a nonlinear function of ionospheric delay, which is used to describe the complex ionospheric nonlinear effects. is the first observation frequency, is the second observation frequency, is the pseudorange value measured at the first observation frequency, is the pseudorange value measured at the second observation frequency, is the tropospheric delay, is the nonlinear estimation function of tropospheric delay, which is used to describe the nonlinear response of tropospheric delay under different air pressures. is the ambient air pressure, is the ambient temperature, is the ambient humidity, is the receiver noise value, is the nonlinear estimation function of receiver noise and multipath effect, which is used to describe the nonlinear characteristics of receiver noise and multipath effect under different pseudorange conditions. is the measured pseudorange, is the theoretical pseudorange.

[0130] Specifically, the nonlinear function of the ionospheric delay is include:

[0131] ,

[0132] in, is the first adjustment factor for ionospheric delay, is the second adjustment factor for ionospheric delay, is the fourth adjustment factor for ionospheric delay, is the fifth adjustment factor for ionospheric delay, is the third adjustment factor for ionospheric delay.

[0133] Specifically, the nonlinear estimation function of the tropospheric delay is include:

[0134] ,

[0135] in, is the first adjustment factor for tropospheric delay, is the second adjustment factor for tropospheric delay, is the third adjustment factor for tropospheric delay, is the fourth adjustment factor for tropospheric delay, is the fifth adjustment factor for tropospheric delay, is the sixth adjustment factor for tropospheric delay, is the seventh adjustment factor for tropospheric delay.

[0136] Specifically, the nonlinear evaluation function of the receiver noise and multipath effect is include:

[0137] ,

[0138] in, is the first adjustment factor for receiver noise and multipath effects, is the second adjustment factor for receiver noise and multipath effects, is the third adjustment factor for receiver noise and multipath effects, is the fourth adjustment factor for receiver noise and multipath effects.

[0139] Specifically, each adjustment factor is fitted by the gradient descent method.

[0140] Step 103: perform accuracy evaluation on the differentially processed data according to the pseudorange change evaluation value, and correct the differentially processed data according to the evaluation result.

[0141] Specifically, an accuracy threshold is set, and when the pseudorange change evaluation value is less than or equal to the accuracy threshold, the data after the difference processing meets the accuracy requirement.

[0142] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0143] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0144] In the several embodiments provided by the present invention, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the system embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0145] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0146] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0147] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only storage medium (ROM, Read-Only Memory), random access storage medium (RAM, RandomAccess Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0148] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the invention.

Claims

1. A method for monitoring the accuracy of data differential post-processing in a navigation system. It is characterized in that include: Acquire data in the navigation system, and perform differential processing on the data to generate differentially processed data, wherein the differentially processed data includes: speed of light, satellite clock error, receiver clock error, ionospheric delay, first observation frequency, second observation frequency, pseudorange value measured at the first observation frequency, pseudorange value measured at the second observation frequency, tropospheric delay, ambient air pressure, ambient temperature, ambient humidity, measured pseudorange and theoretical pseudorange; Setting a pseudorange change evaluation model, and calculating a pseudorange change evaluation value according to the differentially processed data, wherein the pseudorange change evaluation model includes a nonlinear function of ionospheric delay, a nonlinear estimation function of tropospheric delay, and a nonlinear estimation function of receiver noise and multipath effect; The pseudorange change assessment model includes: ， in, is the pseudorange change evaluation value, is the speed of light, is the satellite clock error, is the receiver clock error, is the ionospheric delay, is a nonlinear function of ionospheric delay, which is used to describe the complex ionospheric nonlinear effects. is the first observation frequency, is the second observation frequency, is the pseudorange value measured at the first observation frequency, is the pseudorange value measured at the second observation frequency, is the tropospheric delay, is the nonlinear estimation function of tropospheric delay, which is used to describe the nonlinear response of tropospheric delay under different air pressures. is the ambient air pressure, is the ambient temperature, is the ambient humidity, is the receiver noise value, is the nonlinear estimation function of receiver noise and multipath effect, which is used to describe the nonlinear characteristics of receiver noise and multipath effect under different pseudorange conditions. is the measured pseudorange, is the theoretical pseudorange; The nonlinear function of the ionospheric delay include: ， in, is the first adjustment factor for ionospheric delay, is the second adjustment factor for ionospheric delay, is the fourth adjustment factor for ionospheric delay, is the fifth adjustment factor for ionospheric delay, is the third adjustment factor for ionospheric delay; The nonlinear estimation function of the tropospheric delay is include: ， in, is the first adjustment factor for tropospheric delay, is the second adjustment factor for tropospheric delay, is the third adjustment factor for tropospheric delay, is the fourth adjustment factor for tropospheric delay, is the fifth adjustment factor for tropospheric delay, is the sixth adjustment factor for tropospheric delay, is the seventh adjustment factor for tropospheric delay; The nonlinear evaluation function of the receiver noise and multipath effect include: ， in, is the first adjustment factor for receiver noise and multipath effects, is the second adjustment factor for receiver noise and multipath effects, is the third adjustment factor for receiver noise and multipath effects, is the fourth adjustment factor for receiver noise and multipath effects; According to the pseudorange change evaluation value, the accuracy of the data after the difference processing is evaluated, and according to the evaluation result, the data after the difference processing is corrected.

2. The accuracy monitoring method of data differential post-processing in a navigation system according to claim 1, It is characterized in that Generating the differentially processed data also includes: performing format conversion and screening on the differentially processed data to remove abnormal values.

3. The accuracy monitoring method of data differential post-processing in a navigation system according to claim 2, It is characterized in that Interpolation methods are used to fill in missing data points in the differentially processed data to ensure data integrity.

4. The accuracy monitoring method of data differential post-processing in a navigation system according to claim 1, It is characterized in that A precision threshold is set, and when the pseudorange change evaluation value is less than or equal to the precision threshold, the data after the difference processing meets the precision requirement.

5. The accuracy monitoring method of data differential post-processing in a navigation system according to claim 1, It is characterized in that Each adjustment factor is fitted by gradient descent.

6. An accuracy monitoring system for data differential post-processing in a navigation system, It is characterized in that include: A data acquisition module is used to acquire data in the navigation system and perform differential processing on the data to generate differentially processed data, wherein the differentially processed data includes: light speed, satellite clock error, receiver clock error, ionospheric delay, first observation frequency, second observation frequency, pseudorange value measured at the first observation frequency, pseudorange value measured at the second observation frequency, tropospheric delay, ambient air pressure, ambient temperature, ambient humidity, measured pseudorange and theoretical pseudorange; Setting a model module, used for setting a pseudorange change evaluation model, and calculating a pseudorange change evaluation value according to the differentially processed data, wherein the pseudorange change evaluation model includes a nonlinear function of ionospheric delay, a nonlinear estimation function of tropospheric delay, and a nonlinear estimation function of receiver noise and multipath effect; The pseudorange change assessment model includes: ， in, is the pseudorange change evaluation value, is the speed of light, is the satellite clock error, is the receiver clock error, is the ionospheric delay, is a nonlinear function of ionospheric delay, which is used to describe the complex ionospheric nonlinear effects. is the first observation frequency, is the second observation frequency, is the pseudorange value measured at the first observation frequency, is the pseudorange value measured at the second observation frequency, is the tropospheric delay, is the nonlinear estimation function of tropospheric delay, which is used to describe the nonlinear response of tropospheric delay under different air pressures. is the ambient air pressure, is the ambient temperature, is the ambient humidity, is the receiver noise value, is the nonlinear estimation function of receiver noise and multipath effect, which is used to describe the nonlinear characteristics of receiver noise and multipath effect under different pseudorange conditions. is the measured pseudorange, is the theoretical pseudorange; The nonlinear function of the ionospheric delay include: ， in, is the first adjustment factor for ionospheric delay, is the second adjustment factor for ionospheric delay, is the fourth adjustment factor for ionospheric delay, is the fifth adjustment factor for ionospheric delay, is the third adjustment factor for ionospheric delay; The nonlinear estimation function of the tropospheric delay is include: ， in, is the first adjustment factor for tropospheric delay, is the second adjustment factor for tropospheric delay, is the third adjustment factor for tropospheric delay, is the fourth adjustment factor for tropospheric delay, is the fifth adjustment factor for tropospheric delay, is the sixth adjustment factor for tropospheric delay, is the seventh adjustment factor for tropospheric delay; The nonlinear evaluation function of the receiver noise and multipath effect include: ， in, is the first adjustment factor for receiver noise and multipath effects, is the second adjustment factor for receiver noise and multipath effects, is the third adjustment factor for receiver noise and multipath effects, is the fourth adjustment factor for receiver noise and multipath effects; The accuracy evaluation module is used to perform accuracy evaluation on the differentially processed data according to the pseudorange change evaluation value, and to correct the differentially processed data according to the evaluation result.

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