A method for purifying Beidou navigation satellite observation data under complex electromagnetic background

Abstract

The present invention relates to the field of signal denoising technology, and in particular to a method for purifying Beidou navigation satellite observation data under a complex electromagnetic background. The method comprises the following steps: obtaining satellite observation site location data and satellite location data; performing satellite signal acquisition on the satellite observation site based on the satellite observation site location data and satellite location data to obtain a satellite observation site receiving signal; discretizing the satellite observation site receiving signal into a multi-angle initial signal to generate an initial satellite observation comprehensive signal discrete graph. The present invention improves the recognition capability and filtering efficiency of interference signals through systematic interference identification, signal purification, multi-angle processing and automated precision optimization, thereby weakening the problem of electromagnetic interference to Beidou navigation satellite signals under a complex electromagnetic background, which not only improves the flexibility of the site selection of Beidou navigation satellite continuous observation stations, but also improves the accuracy and stability of its positioning, navigation and timing services.

Description

Technical Field

[0001] The present invention relates to the technical field of signal denoising, and in particular to a method for purifying Beidou navigation satellite observation data under a complex electromagnetic background. Background Art

[0002] Beidou navigation satellite continuous observation station is a station that uses the high-precision Beidou satellite signal receiver installed to receive signals transmitted by multiple satellites, thereby accurately determining its spatial position and providing positioning, timing, and navigation services. Since Beidou navigation satellite signals are electromagnetic waves of a certain frequency and low power, and they must penetrate the atmosphere to be received by the receiver antenna, they are easily disturbed by electromagnetic waves emitted by electromagnetic interference sources in the environment. Therefore, Beidou navigation satellite continuous observation stations are required to have a certain distance from electromagnetic interference nodes, such as microwave stations, radio transmitters, high-voltage line crossing areas, etc. The distance should be greater than 200 meters, and the distance from high-voltage transmission lines and microwave channels should be greater than 100 meters. Beidou navigation satellite continuous observation stations are generally built in two ways: ground stations and rooftop stations. A ground station is a Beidou navigation satellite continuous observation station established on the surface. Due to the restrictions of land acquisition conditions, it is difficult to avoid nearby electromagnetic wave interference sources. In some specific scenarios, if there are no land acquisition conditions, it is necessary to build a Beidou navigation satellite continuous observation station on an existing building, commonly known as a rooftop station. Since most rooftop stations are located in human settlements, there are many electromagnetic signal radiation sources nearby, the buildings are fixed in position, and the space on the roof is limited, it is not easy to optimize the site of the Beidou navigation satellite continuous observation station to avoid the influence of interference sources. Therefore, it is extremely important to improve the Beidou navigation satellite observation data purification capability under complex electromagnetic backgrounds, and further enhance the intelligent processing of Beidou navigation satellite observation data in high-precision positioning application scenarios, thereby improving the accuracy and stability of its services. Summary of the invention

[0003] Based on this, it is necessary to provide a method for purifying Beidou navigation satellite observation data under complex electromagnetic background to solve at least one of the above technical problems.

[0004] To achieve the above purpose, a method for purifying Beidou navigation satellite observation data under complex electromagnetic background is provided, the method comprising the following steps:

[0005] Step S1: obtaining satellite observation site location data and satellite location data; collecting satellite signals from the satellite observation site based on the satellite observation site location data and satellite location data to obtain satellite observation site receiving signals; discretizing the satellite observation site receiving signals into multi-angle initial signals to generate an initial satellite observation comprehensive signal discrete graph;

[0006] Step S2: Perform environmental perception of the satellite observation site according to the satellite observation site location data to generate satellite observation site environmental perception data; perform interference signal impact degree analysis on the satellite observation site environmental perception data to generate interference signal impact degree data; perform secondary screening of high-impact nodes on the satellite observation site environmental perception data using the interference signal impact degree data to generate high electromagnetic interference signal sources;

[0007] Step S3: constructing a comprehensive signal digital model for the high electromagnetic interference signal source, the satellite observation site receiving signal and the initial satellite observation comprehensive signal discrete graph according to the interference signal influence degree data, and generating a comprehensive satellite observation signal digital model; calculating the type interference signal frequency of the high electromagnetic interference signal source according to the interference signal influence degree data, and generating communication base station type interference signal source frequency data and transformer type interference signal source frequency data; performing signal purification on the communication base station type interference signal source frequency data and the transformer type interference signal source frequency data based on the comprehensive satellite observation signal digital model, and generating a satellite observation comprehensive pure signal;

[0008] Step S4: discretize the satellite observation integrated pure signal to generate an optimized satellite observation integrated signal discrete curve; perform three-dimensional spatial accuracy observation on the optimized satellite observation integrated signal discrete curve and the initial satellite observation integrated signal discrete graph to obtain observation accuracy optimization data; compare the observation accuracy optimization data with a preset accuracy optimization threshold, and when the observation accuracy optimization data is less than the preset accuracy optimization threshold, repeat the signal purification until the observation accuracy optimization data is greater than or equal to the preset accuracy optimization threshold, so as to perform high-precision Beidou navigation satellite observation operations.

[0009] The present invention, in step S1, discretizes the received signal at multiple angles to generate a comprehensive signal discrete graph, effectively improves the signal coverage and data integrity, and ensures that satellite observation data can be fully collected and utilized at different angles and orientations. The environmental perception and interference signal analysis in step S2 can effectively identify and screen out high electromagnetic interference signal sources, thereby purifying the signal in subsequent steps and significantly improving the quality of satellite observation signals. The environmental perception module in step S2 enables the system to dynamically adapt to different observation site environments, especially in the presence of high electromagnetic interference. Through secondary screening and analysis, the signal processing strategy can be adjusted in time, enhancing the system's adaptability to complex environments. The signal discretization and three-dimensional spatial precision observation in step S4 ensure that the final satellite observation signal reaches the preset accuracy standard, and through repeated optimization until the high-precision requirements are met, reliable data support is provided for high-precision Beidou navigation satellite observation operations. Step S3 constructs a comprehensive satellite observation signal digital model, combining various data (such as interference signal impact degree data, received signal, initial signal discrete graph, etc.), making the signal purification process more comprehensive and accurate. The frequency of different types of interference signal sources (such as communication base stations and transformers) is calculated, and targeted signal purification is performed based on the comprehensive model, which improves the pertinence and effectiveness of signal purification and ensures that the output signal is purer. In the observation accuracy optimization link, by comparing the observation accuracy optimization data with the preset threshold, it can automatically determine whether the purification steps need to be repeated until the high-precision requirements are met, which makes the entire process have strong automation and adaptability. Therefore, the present invention improves the recognition and filtering efficiency of interference signals through systematic interference identification, signal purification, multi-angle processing and automated accuracy optimization, thereby effectively improving the spatial positioning accuracy of Beidou navigation satellites.

[0010] Preferably, step S1 comprises the following steps:

[0011] Step S11: Acquire satellite observation site location data and satellite location data;

[0012] Step S12: collecting satellite signals from the satellite observation site based on the satellite observation site position data and the satellite position data to obtain a satellite observation site receiving signal;

[0013] Step S13: performing signal preprocessing on the satellite observation site receiving signal to generate a standard satellite observation site receiving signal, wherein the signal preprocessing includes signal denoising, signal gain and signal normalization;

[0014] Step S14: discretize the signals received by the standard satellite observation site into multi-angle initial signals to generate a discrete graph of the initial satellite observation integrated signal.

[0015] The present invention provides an accurate spatial reference for subsequent signal acquisition and processing by accurately acquiring the location information of satellites and observation sites. This ensures that the signal acquisition has high spatial resolution and accuracy, thereby improving the reliability of the data. Through location-based signal acquisition, it can be ensured that the received signal is closely related to the satellite position and the observation station position, reducing the influence of noise and error, and enhancing the authenticity and accuracy of the signal. The signal preprocessing step improves the quality of the received signal, removes noise, enhances the strength of the useful signal, and standardizes the signal for comparison and integration with other data. This step lays the foundation for generating more consistent and usable signal data. Through multi-angle discretization, a comprehensive signal map containing more perspectives and information can be generated. This helps to analyze satellite signals from multiple dimensions, improve the comprehensiveness and accuracy of signal processing, and provide a rich data foundation for further data analysis and applications (such as three-dimensional modeling or geographic information system analysis).

[0016] Preferably, step S14 comprises the following steps:

[0017] Step S141: performing satellite signal reception angle analysis on the satellite observation site location data and the satellite location data to generate satellite signal reception angle data;

[0018] Step S142: performing signal digitization processing on the signal received by the standard satellite observation site to obtain a satellite observation reception numerical signal sequence;

[0019] Step S143: performing multi-angle decomposition of the satellite observation reception numerical signal sequence through the satellite signal reception angle data to generate a signal multi-angle component; performing angle signal classification on the standard satellite observation station reception signal according to the signal multi-angle component to generate an angle classification signal;

[0020] Step S144: discretize the angle classification signals in time and space to generate a discrete graph of the initial satellite observation integrated signal.

[0021] The present invention can obtain the specific angle information of satellite signal received by each observation station through receiving angle analysis. This enables the subsequent signal processing to take into account the change of spatial angle, thereby more accurately reflecting the characteristics of the signal at different angles and improving the spatial resolution of signal processing. Through signal digital processing, the original analog signal is converted into a numerical signal sequence. This digital processing makes the signal easier to be processed and analyzed by a computer, facilitates accurate mathematical operations and signal analysis, and reduces the errors generated in analog signal processing. Multi-angle decomposition enables each angle component of the signal to be extracted and analyzed separately, providing more detailed signal feature information. By classifying these components, the signal changes at different angles can be better understood and utilized, providing a rich data foundation for further signal integration and application. Through time and space discretization processing, the signal is converted into discrete time and space data points, which not only makes it easier to perform time and space analysis on the signal data, but also generates a comprehensive signal discrete diagram to show the signal distribution at different times and spaces. This diagram can provide accurate data support for subsequent geographic information system analysis or other spatial data applications.

[0022] Preferably, step S144 includes the following steps:

[0023] Step S1441: time discretize the angle classification signal to generate discrete time point signal values;

[0024] Step S1442: spatially discretizing the angle classification signal to generate a discrete spatial signal grid;

[0025] Step S1443: synthesizing angle signal components based on discrete time point signal values ​​and discrete space signal grids, thereby generating a multi-angle signal matrix;

[0026] Step S1444: extract signal features from the multi-angle signal matrix to obtain a multi-angle signal feature matrix; map the multi-angle signal feature matrix to a two-dimensional image for visualization to generate an initial satellite observation integrated signal discrete map.

[0027] The present invention decomposes a continuous signal into a series of discrete time point signal values ​​through time discretization, so that the change characteristics of the signal at different time points are clearer. This step allows the subsequent signal analysis to be concentrated on a specific time point, so as to more accurately capture the signal characteristics in the time dimension, which is convenient for time series analysis and processing. Through spatial discretization, the signal is mapped to a discrete spatial grid, so that the complex spatial signal distribution can be converted into processable grid data. This grid processing makes the change of the signal in the spatial dimension more intuitive and easy to analyze, which is helpful for spatial feature extraction and regional analysis. By combining the time discrete points and the spatial signal grid, the angle signal components are integrated into a multi-angle signal matrix. This matrix form can integrate the information of the two dimensions of time and space, provide a multi-dimensional representation for the signal, facilitate the joint analysis and processing of multi-angle signals, and improve the comprehensiveness and accuracy of signal representation. The signal feature extraction step can extract key signal features from the multi-angle signal matrix, and these features retain the most representative information in the signal. On this basis, the signal feature matrix is ​​mapped to a two-dimensional image for visualization. This graphical representation makes the signal features easier to understand and analyze, which is convenient for further research and decision support. The resulting initial satellite observation integrated signal scatter diagram provides an intuitive display of signal distribution and characteristics, which is helpful for the analysis and application of satellite observation data.

[0028] Preferably, step S2 comprises the following steps:

[0029] Step S21: performing environmental perception of the satellite observation site according to the satellite observation site location data to generate satellite observation site environmental perception data;

[0030] Step S22: Screening interference signal impact nodes on the satellite observation site environment perception data to obtain interference signal screening nodes, wherein the interference signal screening nodes include communication base station screening nodes and transformer screening nodes;

[0031] Step S23: analyzing the interference signal impact degree of the interference signal screening node to generate interference signal impact degree data;

[0032] Step S24: using the interference signal impact degree data to perform secondary screening of high-impact nodes on the interference signal screening nodes to generate high electromagnetic interference signal sources.

[0033] The present invention can identify and record the environmental conditions around the satellite observation site, including factors affecting the reception of satellite signals, through environmental perception. This step provides comprehensive environmental background information, so that the subsequent interference signal analysis can be carried out based on accurate environmental data, ensuring the accuracy and reliability of the analysis results. By screening the existing interference sources, such as communication base stations and transformers, the key nodes that interfere with the satellite signal are preliminarily identified. This step helps to narrow the scope of the interference signal analysis, making the subsequent analysis more centralized and efficient, thereby improving the accuracy of interference source identification. The interference signal impact degree analysis can quantify the interference intensity of each screening node on the satellite signal. This quantitative analysis provides a more accurate interference signal impact assessment, making it possible to clarify which nodes have a significant impact on the signal, providing a basis for further screening. By performing secondary screening on the nodes with high impact, the high electromagnetic interference signal source is finally identified. These high-impact nodes are the source of the greatest interference to the satellite signal. Identifying these nodes helps to take targeted measures, such as avoiding these areas or taking signal interference suppression measures to improve the quality and stability of the satellite signal.

[0034] Preferably, step S23 includes the following steps:

[0035] Step S231: confirming the position of the interference signal screening node to obtain the interference signal node position data; calculating the interference distance of the satellite observation site position data according to the interference signal node position data to obtain the interference impact distance data;

[0036] Step S232: performing out-of-band radiation interference analysis on the communication base station screening nodes in the interference signal screening nodes to generate communication base station node interference feature data;

[0037] Step S233: performing equipment discharge interference analysis on the transformer screening node in the interference signal screening node to generate transformer node interference feature data;

[0038] Step S234: Perform electromagnetic interference impact analysis on the transformer node interference feature data and the communication base station node interference feature data to generate interference signal node electromagnetic interference impact data; perform electromagnetic interference impact degree analysis on the interference signal node electromagnetic interference impact data according to the interference impact distance data to generate interference signal impact degree data.

[0039] The present invention determines the positional relationship of these nodes relative to the satellite observation site by accurately locating the interference signal screening nodes, and quantifies the distance between the interference source and the observation site by calculating the interference distance. This process enables subsequent interference analysis to be performed based on the real spatial distance, thereby improving the accuracy of the interference impact assessment. Interference analysis of the out-of-band radiation of the communication base station can identify and quantify the specific interference characteristics of the communication base station on the satellite signal. This analysis provides key data for understanding the interference mode of the communication base station, which helps to accurately locate and deal with these interference sources and reduce their negative impact on the satellite signal. Equipment discharge interference analysis can capture the unique interference characteristics of transformer nodes, especially the electromagnetic interference generated by equipment discharge. By generating these characteristic data, the interference mode and intensity of the transformer node on the satellite signal are clarified, which provides an important basis for the subsequent comprehensive interference analysis. The interference characteristics of the communication base station and the transformer node are comprehensively analyzed to generate the overall electromagnetic interference impact data, thereby providing a comprehensive interference impact assessment. This analysis combines the spatial distance and interference characteristics, further quantifies the actual impact of the interference signal on the satellite observation site, and provides strong support for identifying the most critical interference sources and taking corresponding measures.

[0040] Preferably, step S3 comprises the following steps:

[0041] Step S31: Calculate the interference signal strength of the high electromagnetic interference signal source according to the interference signal influence degree data to obtain the satellite observation interference signal;

[0042] The formula for calculating the interference signal strength is as follows:

[0043]

[0044] In the formula, is represented as interference signal, is the number of interference nodes in a complex electromagnetic environment, is the amplitude of each interference signal, is the frequency of each signal, is the initial phase of the interference signal, It is expressed as the measurement time;

[0045] Step S32: performing background signal separation on the initial satellite observation integrated signal discrete graph to generate a satellite observation background signal; performing satellite observation integrated signal calculation on the standard satellite observation station receiving signal and the satellite observation background signal through the satellite observation interference signal to obtain a satellite observation integrated signal;

[0046] The calculation formula of satellite observation integrated signal is as follows:

[0047]

[0048] In the formula, It is the integrated signal received by the Beidou navigation satellite continuous observation station. is the initial Beidou navigation satellite signal, is the interference signal, is the background signal;

[0049] Step S33: constructing a digital model of the integrated signal based on the satellite observation integrated signal to generate a digital model of the integrated satellite observation signal;

[0050] The formula for constructing the comprehensive signal digital model is as follows:

[0051]

[0052] In the formula, It represents the integrated signal received by the BeiDou navigation satellite continuous observation station. Represents the initial Beidou navigation satellite signal, Expressed as the number of interfering nodes in a complex electromagnetic environment, is the amplitude of each interference signal, is the frequency of each signal, is the initial phase of the interference signal, is the measurement time, It is indicated as background signal;

[0053] Step S34: calculating the type interference signal frequency of the satellite observation interference signal according to the interference signal influence degree data, and generating communication base station type interference signal source frequency data and transformer type interference signal source frequency data;

[0054] The formula for calculating the frequency of the type interference signal is as follows;

[0055]

[0056]

[0057] In the formula, It represents the frequency data of interference signal source of communication base station type. Represented as transformer type interference signal source frequency data;

[0058] Step S35: Using the Beidou navigation satellite observation data purification formula to purify the communication base station type interference signal source frequency data and the transformer type interference signal source frequency data based on the comprehensive satellite observation signal digital model, to generate a satellite observation comprehensive pure signal.

[0059] The present invention accurately quantifies the influence of various interference sources on satellite observation signals in complex electromagnetic environments through interference signal calculation formulas. This calculation takes into account the amplitude, frequency and initial phase of different interference sources, ensures the accurate expression of interference signals, and provides an accurate interference information basis for subsequent signal processing. The separation of background signals and the calculation of integrated signals make the composition of satellite observation signals clearer. By separating and recombining interference signals, background signals and initial signals, a more accurate integrated signal is generated. This lays the foundation for further analysis and processing of interference signals, and also ensures the integrity and accuracy of satellite observation signals. By constructing a digital model of integrated signals, complex satellite observation signal data is integrated into a unified mathematical model. This model can comprehensively consider interference signals, initial signals and background signals, and provide a complete signal description, which is convenient for further signal processing, simulation and optimization. The calculation of the frequency of type interference signals further subdivides interference signals into different types of interference sources, such as communication base stations and transformers. This classification and frequency calculation can help to more accurately identify and process different types of interference signals, and help to improve the efficiency and effect of the signal purification process.

[0060] Preferably, the Beidou navigation satellite observation data purification formula in step S35 is as follows:

[0061]

[0062]

[0063] In the formula, It is represented by the integrated pure signal of satellite observation, It represents the integrated signal received by the BeiDou navigation satellite continuous observation station. Expressed as the number of interfering nodes in a complex electromagnetic environment, The amplitude of the interference signal source represented by the communication base station type, Expressed as the amplitude of the interference signal source of the transformer type, Represents the initial phase of the interference signal source of the communication base station type, The initial phase of the interference signal source represented by the transformer type, It represents the frequency data of interference signal source of communication base station type. Expressed as transformer type interference signal source frequency data, Represented as a transformer type interference signal, Represented as background signal.

[0064] The present invention analyzes and integrates a Beidou navigation satellite observation data purification formula, in which It is represented as the original integrated signal, including satellite signal, interference signal and background signal. It is the basic data for purification. The amplitude of the interference signal source represented by the communication base station type indicates the interference intensity of the communication base station on the signal. The higher the amplitude value, the greater the impact of the interference signal on the observed signal. The frequency of the interference signal from the communication base station is defined. The frequency of the interference signal is one of its characteristics, and accurate frequency data helps to accurately remove this interference. The initial phase of the interference signal source, represented as a communication base station type, describes the phase offset of the interference signal, which is crucial for the accurate representation of the interference signal. The phase information helps to correctly align with the interference part in the observed signal. Represented as a transformer type interference signal, this is a transformer type interference signal, according to its amplitude ,frequency and initial phase Calculated, it represents the contribution of the transformer interference signal to the overall signal. The amplitude of the interference signal source of the transformer type is expressed as Similarly, amplitude affects how much the interfering signal affects the observed signal. It is expressed as transformer type interference signal source frequency data, which defines the frequency of the transformer interference signal and helps to identify and separate this type of interference signal. The initial phase of the interference signal source represented as a transformer type, the phase information of the interference signal, is used to accurately describe the time characteristics of the interference signal. Represented as background signal, the background signal is other non-interference signals mixed in the integrated signal, which needs to be separated out so that the pure signal after removing the interference signal can more accurately reflect the actual observation data. When using the conventional Beidou navigation satellite observation data purification formula in this field, a satellite observation comprehensive pure signal can be obtained. By applying the Beidou navigation satellite observation data purification formula provided by the present invention, the satellite observation comprehensive pure signal can be calculated more accurately. The purification formula obtains the pure signal of satellite observation by subtracting the estimated interference signal (including interference signals of communication base stations and transformer types) from the integrated satellite observation signal. The key to the formula is to accurately represent and remove specific interference signals so that the remaining signal is as close to the actual satellite observation data as possible. The interference signals (interference signals of communication base stations and transformers) and the background signals involved in the formula are processed separately. By calculating the impact of these two interference signals separately and subtracting them from the integrated signal, their impact on the satellite observation signal can be effectively eliminated. Accurate interference signal calculation (including frequency, amplitude and phase) and background signal separation ensure that the purified signal is as real as possible. This process improves the quality of satellite observation signals and makes the signal data closer to the actual observation results. The purified satellite observation signals can be used for further analysis and applications, such as navigation, positioning and other high-precision scenarios to ensure the reliability and accuracy of the data.

[0065] Preferably, step S4 comprises the following steps:

[0066] Step S41: discretizing the satellite observation integrated pure signal to generate an optimized satellite observation integrated signal discrete curve;

[0067] Step S42: performing discrete overlap of the optimized satellite observation integrated signal discrete curve and the initial satellite observation integrated signal discrete graph to generate a satellite observation signal comparison discrete graph;

[0068] Step S43: perform three-dimensional spatial accuracy observation on the satellite observation signal comparison discrete graph to generate a spatial observation accuracy comparison graph; perform accuracy optimization analysis on the spatial observation accuracy comparison graph to obtain observation accuracy optimization data; compare the observation accuracy optimization data with a preset accuracy optimization threshold. When the observation accuracy optimization data is less than the preset accuracy optimization threshold, return to S35 and repeat the execution until the observation accuracy optimization data is greater than or equal to the preset accuracy optimization threshold to perform high-precision Beidou navigation satellite observation operations.

[0069] The present invention converts continuous satellite observation signals into discrete signal data points by signal discretization. This discretization process helps to further analyze and process the signal, and the generated discrete curve provides basic data for subsequent comparison and optimization. By overlapping the optimized discrete curve with the initial discrete graph, the signal performance before and after optimization can be intuitively compared. This comparison helps to identify the effect and difference of signal optimization and ensure that the optimization process brings actual improvement. Three-dimensional spatial precision observation can evaluate the performance and accuracy of the signal in space. By analyzing and comparing the data in the discrete graph, precision optimization data can be obtained, which are used to evaluate whether the optimization effect meets the expected standard. When the observation precision optimization data is less than the preset precision optimization threshold, return to S35 and repeat the execution: this ensures that the optimization process will not stop before the predetermined precision optimization requirement is met. By repeating the execution, the signal processing can be further adjusted and improved until the accuracy requirement is met. When the observation precision optimization data is greater than or equal to the preset precision optimization threshold, a high-precision Beidou navigation satellite observation operation is performed: once the optimization data reaches or exceeds the threshold, a high-precision satellite observation operation can be performed to ensure that the final observation result has sufficient accuracy and reliability. By gradually optimizing and comparing discrete graphs, the accuracy of satellite observation signals can be significantly improved, ensuring that the signals meet high-precision requirements in practical applications. Repeating the optimization process until the accuracy requirements are met ensures the reliability and accuracy of the final data, which is suitable for application scenarios that require high-precision data. Comparing discrete graphs and three-dimensional spatial observations provides an intuitive means of analyzing optimization effects, which helps to effectively monitor and adjust the optimization process. By setting the accuracy optimization threshold and making dynamic adjustments, the optimization process can be flexibly processed according to actual needs to adapt to different accuracy requirements.

[0070] Preferably, performing three-dimensional spatial accuracy observation on the satellite observation signal comparison discrete graph to obtain observation accuracy optimization data includes:

[0071] Perform time segmentation on the satellite observation signal contrast discrete graph to generate observation time segmentation data;

[0072] The initial discrete range of the satellite observation signal comparison discrete graph is calculated by observing the time segment data to obtain the initial signal discrete range data; the error convergence calculation of the initial signal discrete range data is performed by optimizing the satellite observation comprehensive signal discrete curve to generate satellite observation accuracy error optimization data;

[0073] According to the satellite observation accuracy error optimization data, the three-dimensional spatial accuracy of the satellite observation signal comparison discrete map is calculated to obtain the observation accuracy optimization data.

[0074] The present invention can divide the entire signal data into smaller time periods by segmenting the signal comparison discrete graph according to time, so as to analyze the signal characteristics in each time period. Time segmentation makes the signal analysis more detailed, helps to find inconsistent signal characteristics in time, helps to perform local optimization for signals in different time periods, and improves the accuracy of the overall signal. The discrete range in each time period is calculated according to the time segmented data, and an initial signal discrete measurement is provided, which provides a benchmark for subsequent error calculation, so that the preliminary discrete range is clarified, and the preliminary discrete range is clarified. By comparing the optimized signal discrete curve with the initial signal discrete range data, the error is calculated and converged. This step is used to evaluate the error of the optimized signal. Through the error convergence calculation, the error in the signal can be reduced and the accuracy of the signal can be improved. The generated precision error optimization data is used to evaluate the effect of signal optimization and ensure that the signal meets the expected precision requirements. The error optimization data is used to perform precision observation of the signal in three-dimensional space to further verify the optimization effect of the signal. Three-dimensional space observation provides a comprehensive precision evaluation of the signal in space, which helps to understand the spatial distribution characteristics of signal optimization, ensure that the precision of the optimized signal in practical applications meets the requirements, and meet the standards of high-precision observation. Through time segmentation, discrete range calculation, error convergence and other steps, the accuracy of satellite observation signals can be deeply analyzed and optimized to ensure the accuracy and reliability of the signals. Time segmentation and error optimization provide local and overall improvement strategies to improve the overall quality of the signals. Error convergence calculation ensures the effective control and reduction of errors during signal optimization and enhances the accuracy of the signals. Three-dimensional spatial precision observation ensures that signal optimization reaches the preset accuracy standard and provides reliable signal data for practical applications.

[0075] The beneficial effect of the present invention is that by collecting signals from satellite observation sites and discretizing these signals from multiple angles, a discrete graph of the initial satellite observation integrated signal is generated. Basic signal data and discrete graphs are obtained, providing initial data support for subsequent signal analysis and optimization. Environmental perception data of satellite observation sites are generated, the influence of interference signals is analyzed, and the source of high electromagnetic interference signals is identified, which helps to identify and evaluate the influence of interference signals, can accurately locate the source of electromagnetic interference, and helps to locate the target of subsequent signal purification. A digital model of integrated satellite observation signals is established, the frequency of interference signals is calculated, and signal purification is performed. By establishing a digital model and calculating the frequency of interference signals, the purity of the signal is improved, the quality and accuracy of the signal are enhanced, and the foundation for high-precision satellite observation is laid. The discretization process of the satellite observation integrated signal is optimized, the accuracy of the optimized signal is compared with the accuracy of the initial signal, and the accuracy is optimized. Through continuous optimization and accuracy evaluation, the accuracy of satellite observation data is improved to ensure that high-precision navigation requirements are met. Through gradual optimization and refined processing, high-precision satellite observation is finally achieved, and the reliability and accuracy of the satellite navigation system are improved. Therefore, the present invention improves the efficiency of identifying and filtering interference signals through systematic interference identification, signal purification, multi-angle processing and automated precision optimization, thereby effectively improving the spatial positioning accuracy of Beidou navigation satellites. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Figure 1 A schematic diagram of the steps of a Beidou navigation satellite observation data purification method under complex electromagnetic background;

[0077] Figure 2 for Figure 1 Detailed implementation steps of step S2 in the flowchart;

[0078] Figure 3 It is a schematic diagram of satellite observation signal contrast dispersion of the present invention;

[0079] Figure 4 A schematic diagram of the comparison of space observation accuracy of the present invention;

[0080] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0081] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0082] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0083] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0084] To achieve this, please refer to Figures 1 to 4 , a method for purifying Beidou navigation satellite observation data under complex electromagnetic background, the method comprising the following steps:

[0085] Step S1: obtaining satellite observation site location data and satellite location data; collecting satellite signals from the satellite observation site based on the satellite observation site location data and satellite location data to obtain satellite observation site receiving signals; discretizing the satellite observation site receiving signals into multi-angle initial signals to generate an initial satellite observation comprehensive signal discrete graph;

[0086] Step S2: Perform environmental perception of the satellite observation site according to the satellite observation site location data to generate satellite observation site environmental perception data; perform interference signal impact degree analysis on the satellite observation site environmental perception data to generate interference signal impact degree data; perform secondary screening of high-impact nodes on the satellite observation site environmental perception data using the interference signal impact degree data to generate high electromagnetic interference signal sources;

[0087] Step S3: constructing a comprehensive signal digital model for the high electromagnetic interference signal source, the satellite observation site receiving signal and the initial satellite observation comprehensive signal discrete graph according to the interference signal influence degree data, and generating a comprehensive satellite observation signal digital model; calculating the type interference signal frequency of the high electromagnetic interference signal source according to the interference signal influence degree data, and generating communication base station type interference signal source frequency data and transformer type interference signal source frequency data; performing signal purification on the communication base station type interference signal source frequency data and the transformer type interference signal source frequency data based on the comprehensive satellite observation signal digital model, and generating a satellite observation comprehensive pure signal;

[0088] Step S4: discretize the satellite observation integrated pure signal to generate an optimized satellite observation integrated signal discrete curve; perform three-dimensional spatial accuracy observation on the optimized satellite observation integrated signal discrete curve and the initial satellite observation integrated signal discrete graph to obtain observation accuracy optimization data; compare the observation accuracy optimization data with a preset accuracy optimization threshold, and when the observation accuracy optimization data is less than the preset accuracy optimization threshold, repeat the signal purification until the observation accuracy optimization data is greater than or equal to the preset accuracy optimization threshold, so as to perform high-precision Beidou navigation satellite observation operations.

[0089] The present invention, in step S1, discretizes the received signal at multiple angles to generate a comprehensive signal discrete graph, effectively improves the signal coverage and data integrity, and ensures that satellite observation data can be fully collected and utilized at different angles and orientations. The environmental perception and interference signal analysis in step S2 can effectively identify and screen out high electromagnetic interference signal sources, thereby purifying the signal in subsequent steps and significantly improving the quality of satellite observation signals. The environmental perception module in step S2 enables the system to dynamically adapt to different observation site environments, especially in the presence of high electromagnetic interference. Through secondary screening and analysis, the signal processing strategy can be adjusted in time, enhancing the system's adaptability to complex environments. The signal discretization and three-dimensional spatial precision observation in step S4 ensure that the final satellite observation signal reaches the preset accuracy standard, and through repeated optimization until the high-precision requirements are met, reliable data support is provided for high-precision Beidou navigation satellite observation operations. Step S3 constructs a comprehensive satellite observation signal digital model, combining various data (such as interference signal impact degree data, received signal, initial signal discrete graph, etc.), making the signal purification process more comprehensive and accurate. The frequency of different types of interference signal sources (such as communication base stations and transformers) is calculated, and targeted signal purification is performed based on the comprehensive model, which improves the pertinence and effectiveness of signal purification and ensures that the output signal is purer. In the observation accuracy optimization link, by comparing the observation accuracy optimization data with the preset threshold, it can automatically determine whether the purification steps need to be repeated until the high-precision requirements are met, which makes the entire process have strong automation and adaptability. Therefore, the present invention improves the recognition and filtering efficiency of interference signals through systematic interference identification, signal purification, multi-angle processing and automated accuracy optimization, thereby effectively improving the spatial positioning accuracy of Beidou navigation satellites.

[0090] In the embodiment of the present invention, reference Figure 1 The above is a schematic flow chart of the steps of a method for purifying Beidou navigation satellite observation data under a complex electromagnetic background of the present invention. In this example, the method for purifying Beidou navigation satellite observation data under a complex electromagnetic background includes the following steps:

[0091] Step S1: obtaining satellite observation site location data and satellite location data; collecting satellite signals from the satellite observation site based on the satellite observation site location data and satellite location data to obtain satellite observation site receiving signals; discretizing the satellite observation site receiving signals into multi-angle initial signals to generate an initial satellite observation comprehensive signal discrete graph;

[0092] In an embodiment of the present invention, the approximate position data of the Beidou navigation satellite observation site and the precise ephemeris of the Beidou navigation satellite are obtained, so as to accurately calculate, predict, depict and track the time, position, speed and other operating states of the satellite and the flying body. The position information of the observation site is stored in a database or file for subsequent processing. The position of the satellite at the current moment is obtained through the satellite orbit data (it can also be calculated using the known satellite orbit parameters and time). The geographic coordinates and orbital altitude of the satellite at the specified time are calculated. Ensure that each satellite observation site is equipped with a high-precision signal receiving device that can receive the signal transmitted by the target satellite. The received signal is a multi-signal signal, which not only contains the navigation signal emitted by the Beidou navigation satellite, but also contains the interference signal emitted by the nearby electromagnetic interference source. The equipment should be able to capture multiple properties of the signal, such as signal strength, frequency, phase, etc. Within the specified time, the observation site continuously receives the signal from the target satellite through the receiving device. Match the timestamp of the received signal with the position data of the observation site, and record the received signal. Sort the collected signals according to the time series, and classify the data according to the position relationship between the observation site and the satellite. Considering the relative azimuth and elevation angles between the observation site and the satellite, the signal is divided into multiple different viewing angles. Discretization processing is performed for each data set at different angles. The continuous signal value can be divided into discrete signal blocks, and the key features of each discrete block (such as the average value and peak value of the signal) are extracted. Generate the initial signal discretization results for each angle. Summarize the discretized signal data of multiple angles, combine the weights and signal characteristics of each angle, and generate a comprehensive signal graph. Use data visualization tools to draw the signal discrete graph to show the distribution of the signal at different angles. Check the integrity and consistency of the data by analyzing the generated initial satellite observation comprehensive signal discrete graph. Preliminary marking of abnormal points or interference in the signal graph provides a basis for subsequent signal processing and analysis.

[0093] Step S2: Perform environmental perception of the satellite observation site according to the satellite observation site location data to generate satellite observation site environmental perception data; perform interference signal impact degree analysis on the satellite observation site environmental perception data to generate interference signal impact degree data; perform secondary screening of high-impact nodes on the satellite observation site environmental perception data using the interference signal impact degree data to generate high electromagnetic interference signal sources;

[0094] In an embodiment of the present invention, an environmental perception device, such as an electromagnetic spectrum analyzer, an antenna array, etc., is deployed at each satellite observation site to monitor the electromagnetic environment around the site in real time, wherein the electromagnetic environment includes the location and radiation intensity of the electromagnetic interference source. These devices can measure the electromagnetic signal strength, spectrum characteristics, signal source direction and other data within different frequency ranges, continuously monitor and record the environmental data of each satellite observation site, and generate a detailed environmental perception data set, including information such as signal strength, frequency distribution, and interference source location. The environmental perception data is preprocessed, such as denoising and filtering, to ensure the accuracy and reliability of the data. The interference signal source is identified, and the degree of influence of these signals in each frequency band is marked to master the spectrum characteristic data of the interference signal. The signal processing algorithm is used to analyze the strength and characteristics of the interference signal in each frequency band. The degree of influence of the interference signal on the satellite signal received by the satellite observation site is evaluated, and the interference signal influence degree data is generated. According to the interference signal influence degree data, high-impact nodes that cause significant interference to the satellite signal are screened out. Focus on those signal sources that cause significant interference to multiple frequency bands. For the high-impact nodes that are initially screened out, a secondary analysis is performed, and the screening results are further confirmed and optimized in combination with factors such as the specific location of the site and the characteristics of the surrounding environment. Finally determine the location and characteristics of the high electromagnetic interference signal source. Record and store the data of the high electromagnetic interference signal source that is finally screened, including its location, impact level, frequency range and other detailed information. Generate a detailed report or database for further processing and analysis. According to the high electromagnetic interference signal source data, optimize the layout of satellite observation sites, adjust the signal reception strategy, or take shielding, filtering and other measures to reduce the interference effect.

[0095] Step S3: constructing a comprehensive signal digital model for the high electromagnetic interference signal source, the satellite observation site receiving signal and the initial satellite observation comprehensive signal discrete graph according to the interference signal influence degree data, and generating a comprehensive satellite observation signal digital model; calculating the type interference signal frequency of the high electromagnetic interference signal source according to the interference signal influence degree data, and generating communication base station type interference signal source frequency data and transformer type interference signal source frequency data; performing signal purification on the communication base station type interference signal source frequency data and the transformer type interference signal source frequency data based on the comprehensive satellite observation signal digital model, and generating a satellite observation comprehensive pure signal;

[0096] In an embodiment of the present invention, by collecting and integrating interference signal impact degree data, high electromagnetic interference signal source data, signal data received by satellite observation sites, and initial satellite observation integrated signal discrete graphs. These data are converted into a unified format for subsequent processing. Mathematical modeling and signal processing techniques are used to construct the integrated data into a comprehensive satellite observation signal digital model. The model should be able to reflect the signal reception conditions of each observation site, the degree of influence of the interference source, and the distribution of the signal in different frequency bands. In the process of model construction, a multidimensional matrix, a signal superposition model or other suitable mathematical methods can be used to ensure that the model can accurately describe the actual signal environment. The model is calibrated and verified using known observation data and experimental results to ensure its accuracy and reliability. Based on the interference signal impact degree data, the high electromagnetic interference signal source is identified and classified into different categories such as communication base station type and transformer type. The characteristics of each category of interference signal source are analyzed to determine key information such as its frequency range and signal strength. The frequency of each type of interference signal source is calculated to generate communication base station type interference signal source frequency data and transformer type interference signal source frequency data. Frequency calculation can be achieved through signal processing methods such as Fourier transform to accurately extract the main frequency components of various interference sources. Based on the digital model of the integrated satellite observation signal, select appropriate signal purification algorithms, such as adaptive filters, bandpass filters, or signal reconstruction technology, to remove interference signals of specific frequencies. Focus on processing the frequency data from communication base stations and transformer-type interference signal sources to ensure that the purification process does not affect the integrity of satellite signals. Perform signal purification on the frequency data of communication base station-type interference signal sources and transformer-type interference signal sources. Superimpose the purified signal back into the model to generate a satellite observation integrated pure signal. Compare the generated satellite observation integrated pure signal with the actual observation data to verify the signal purification effect. Based on the verification results, further optimize the purification algorithm and model parameters. Record and output the data of the satellite observation integrated pure signal, including detailed information such as the purified signal strength and frequency distribution.

[0097] Step S4: discretize the satellite observation integrated pure signal to generate an optimized satellite observation integrated signal discrete curve; perform three-dimensional spatial accuracy observation on the optimized satellite observation integrated signal discrete curve and the initial satellite observation integrated signal discrete graph to obtain observation accuracy optimization data; compare the observation accuracy optimization data with a preset accuracy optimization threshold, and when the observation accuracy optimization data is less than the preset accuracy optimization threshold, repeat the signal purification until the observation accuracy optimization data is greater than or equal to the preset accuracy optimization threshold, so as to perform high-precision Beidou navigation satellite observation operations.

[0098] In an embodiment of the present invention, the generated satellite observation integrated pure signal is discretized and converted into discrete data points or discrete time series. Sampling, quantization, or wavelet transform techniques can be used for discretization to maintain the main characteristics of the signal while reducing the amount of data. The signal data points after discretization are plotted into an optimized satellite observation integrated signal discrete curve. Ensure that the curve can accurately reflect the time, frequency and spatial characteristics of the signal, and provide a basis for subsequent three-dimensional spatial analysis. The generated optimized satellite observation integrated signal discrete curve is compared and analyzed with the previously generated initial satellite observation integrated signal discrete graph. Using three-dimensional spatial observation technology, the two are superimposed or difference analyzed in the spatial domain to observe the accuracy of the discrete curve in three-dimensional space. After comparison, the spatial distance, time difference and frequency offset and other indicators are used for accuracy observation to generate observation accuracy optimization data. Focus on analyzing the distribution of the optimized signal in three-dimensional space and the improvement relative to the initial signal. Compare the generated observation accuracy optimization data with the preset accuracy optimization threshold. The preset accuracy optimization threshold is usually set according to the accuracy requirements of the Beidou navigation system, including spatial positioning accuracy, time synchronization accuracy, etc. If the observation accuracy optimization data is less than the preset accuracy optimization threshold, it indicates that the current signal purification effect has not met expectations. Repeat the signal purification process in step S3 to optimize the communication base station type interference signal source frequency data and the transformer type interference signal source frequency data until the observation accuracy optimization data is greater than or equal to the preset accuracy optimization threshold. Once the preset accuracy optimization threshold is reached or exceeded, the iteration is stopped, and the final optimized satellite observation integrated signal discrete curve is used as the input of the high-precision signal. The high-precision satellite observation integrated signal generated in the end is used to perform high-precision observation operations of Beidou navigation satellites. This operation can be applied to actual operations such as high-precision positioning, navigation, and timing to ensure the reliability and accuracy of the Beidou navigation system. Record the results of the observation operation, including accuracy indicators, signal quality and other data, and generate a detailed report to record the entire accuracy optimization process and the final observation results.

[0099] Preferably, step S1 comprises the following steps:

[0100] Step S11: Acquire satellite observation site location data and satellite location data;

[0101] Step S12: collecting satellite signals from the satellite observation site based on the satellite observation site position data and the satellite position data to obtain a satellite observation site receiving signal;

[0102] Step S13: performing signal preprocessing on the satellite observation site receiving signal to generate a standard satellite observation site receiving signal, wherein the signal preprocessing includes signal denoising, signal gain and signal normalization;

[0103] Step S14: discretize the signals received by the standard satellite observation site into multi-angle initial signals to generate a discrete graph of the initial satellite observation integrated signal.

[0104] In an embodiment of the present invention, the precise geographic coordinates of each satellite observation site, including latitude, longitude and altitude, are obtained by using GPS, GLONASS or other positioning systems. These data are recorded and stored in a centralized database for subsequent processing. The real-time position of the satellite, including its orbital parameters, instantaneous coordinates and altitude, is obtained from the satellite orbit data or orbit prediction model. These data can be obtained from a public database or a dedicated satellite tracking system. Signal receiving equipment, such as antennas and receivers, is deployed at each satellite observation site to ensure that signals from the target satellite can be received. The equipment is calibrated to ensure its accuracy and avoid errors caused by the environment or equipment. According to the satellite position and the observation site location, the antenna is adjusted to ensure the best receiving conditions. Satellite signals are collected in real time and stored on a local or remote server. A filter (such as a low-pass filter or an adaptive filter) is used to denoise the collected satellite signals to remove interference noise from the environment, equipment or other satellites. Denoising can be achieved by frequency domain analysis, time domain analysis and other methods. Gain processing is performed on the denoised signal to amplify weak signals and ensure that the dynamic range of the signal is suitable for subsequent processing. Gain processing should avoid introducing distortion and ensure the integrity of signal characteristics. The signal after gain is normalized to standardize the amplitude of the signal to a uniform range for subsequent discretization and analysis. Normalization usually uses maximum and minimum value normalization or mean normalization. The signal after denoising, gain, and normalization is defined as the standard satellite observation station receiving signal and stored in the data set. Use multiple observation sites or adjust the antenna angle to obtain the standard satellite observation station receiving signal at different angles. Synchronize these signals to ensure observation within the same time window. Discretize the standard signals at multiple angles and convert them into discrete signal data points, involving steps such as time sampling, quantization, and segmentation. Ensure that the spatial, temporal, and frequency characteristics of the signal are preserved during the discretization process. Integrate the discretized signal data points into a comprehensive initial satellite observation signal discrete map. The map can be presented in a three-dimensional graph, heat map, or other way to visualize the distribution of the signal.

[0105] Preferably, step S14 comprises the following steps:

[0106] Step S141: performing satellite signal reception angle analysis on the satellite observation site location data and the satellite location data to generate satellite signal reception angle data;

[0107] Step S142: performing signal digitization processing on the signal received by the standard satellite observation site to obtain a satellite observation reception numerical signal sequence;

[0108] Step S143: performing multi-angle decomposition of the satellite observation reception numerical signal sequence through the satellite signal reception angle data to generate a signal multi-angle component; performing angle signal classification on the standard satellite observation station reception signal according to the signal multi-angle component to generate an angle classification signal;

[0109] Step S144: discretize the angle classification signals in time and space to generate a discrete graph of the initial satellite observation integrated signal.

[0110] In an embodiment of the present invention, the signal receiving angle of each observation site relative to the satellite is calculated based on the satellite observation site position data and the satellite position data. The receiving angle can be calculated by geometric relationship, including azimuth and elevation, to determine the propagation path of the signal from the satellite to the observation site. The calculated receiving angle data is saved as a satellite signal receiving angle data set to provide a basis for subsequent multi-angle signal analysis. The data set should contain the receiving angle information of each observation site and be associated with the corresponding signal data. The standard satellite observation site receiving signal is sampled to convert the continuous signal into a discrete signal sequence. The sampling frequency should be high enough to capture all the characteristics of the signal. The sampled signal is quantized, and the signal amplitude of each sampling point is converted into a digital value to generate a satellite observation receiving numerical signal sequence. A suitable quantization level should be selected during the quantization process to ensure that the details of the signal are retained. The quantized signal is saved as a numerical signal sequence to ensure that the signal of each observation site can be accurately described and analyzed in subsequent processing. According to the satellite signal receiving angle data generated in step S141, the satellite observation receiving numerical signal sequence is decomposed from multiple angles. By decomposing the signal sequence according to different receiving angles, signal components corresponding to each angle are generated, that is, signal multi-angle components. The multi-angle components of the signal are classified, and the signal components belonging to the same receiving angle or angle range are classified into one category to generate angle-classified signals. Ensure that the various types of signals retain their original characteristics during the classification process so that the angle dependence of the signal can be accurately reflected in the subsequent analysis. The angle-classified signals are processed in time and space to discretize the continuous time and space signals into discrete data points. This can be achieved through methods such as time sampling, space segmentation or wavelet transform. The temporal and spatial consistency of the signal should be maintained during the discretization process to ensure that the distribution and changes of various types of signals at different angles can be accurately captured. The discretized angle-classified signals are integrated into a comprehensive initial satellite observation signal discrete map. The map can be presented in a three-dimensional graphic or other visualization method to show the distribution of the signal at different angles, time and space.

[0111] Preferably, step S144 includes the following steps:

[0112] Step S1441: time discretize the angle classification signal to generate discrete time point signal values;

[0113] Step S1442: spatially discretizing the angle classification signal to generate a discrete spatial signal grid;

[0114] Step S1443: synthesizing angle signal components based on discrete time point signal values ​​and discrete space signal grids, thereby generating a multi-angle signal matrix;

[0115] Step S1444: extract signal features from the multi-angle signal matrix to obtain a multi-angle signal feature matrix; map the multi-angle signal feature matrix to a two-dimensional image for visualization to generate an initial satellite observation integrated signal discrete map.

[0116] In an embodiment of the present invention, the continuous time signal is divided into multiple discrete time points by discretizing the angle classification signal in time. The corresponding signal value is extracted at each discrete time point to generate a discrete time point signal value sequence. The signal amplitude or intensity value corresponding to each discrete time point is recorded to generate a signal sequence after time discretization. It is ensured that the signal after time discretization can accurately reflect the changing characteristics of the signal over time. The angle classification signal is discretized in space, and the continuous distribution of the signal in space is converted into a discrete spatial grid. According to the receiving angle and the position of the observation site, the signal value is distributed to different spatial grid units to generate a discrete spatial signal grid. Each grid unit corresponds to a signal value, which represents the strength or characteristics of the signal in the spatial area. It is ensured that the signal grid after spatial discretization can accurately describe the spatial distribution of the signal. Based on the discrete time point signal value generated in step S1441 and the discrete spatial signal grid generated in step S1442, the angle signal component is synthesized. The signal values ​​of different time points and spatial grids are combined according to the receiving angle to generate a multi-angle signal matrix. The rows and columns of the matrix represent the time and space dimensions respectively, and each element in the matrix represents the signal value at a specific angle, time point and spatial position. Ensure that the matrix can comprehensively reflect the changes in time, space and angle of the signal. Feature extraction is performed on the generated multi-angle signal matrix to analyze the distribution characteristics of the signal in the matrix, such as frequency, amplitude, phase, etc. After extracting these features, a multi-angle signal feature matrix is ​​generated, which contains signal feature information at different angles, time and space dimensions. The multi-angle signal feature matrix is ​​mapped to a two-dimensional image to display the signal features in a visual way. The intensity and distribution of the signal features are represented by color, brightness or texture, and a discrete map of the initial satellite observation integrated signal is generated. Through two-dimensional image visualization, the generated initial satellite observation integrated signal discrete map can intuitively display the characteristics of the signal at different angles, time and space dimensions. The image will be used in the subsequent signal analysis and optimization process.

[0117] As an example of the present invention, refer to Figure 2 As shown, in this example, step S2 includes:

[0118] Step S21: performing environmental perception of the satellite observation site according to the satellite observation site location data to generate satellite observation site environmental perception data;

[0119] Step S22: Screening interference signal impact nodes on the satellite observation site environment perception data to obtain interference signal screening nodes, wherein the interference signal screening nodes include communication base station screening nodes and transformer screening nodes;

[0120] Step S23: analyzing the interference signal impact degree of the interference signal screening node to generate interference signal impact degree data;

[0121] Step S24: using the interference signal impact degree data to perform secondary screening of high-impact nodes on the interference signal screening nodes to generate high electromagnetic interference signal sources.

[0122] In an embodiment of the present invention, environmental sensing devices such as electromagnetic radiation monitors, temperature and humidity sensors, and weather stations are deployed around each satellite observation site to monitor the surrounding environmental conditions. Ensure that the sensing devices cover all environmental factors that affect signal reception, including electromagnetic interference sources, terrain features, and meteorological conditions. Use environmental sensing devices to collect real-time data of the surrounding environment, such as electromagnetic radiation intensity, meteorological data (wind speed, wind direction, temperature, humidity, etc.), and geographical features (such as mountains, buildings, etc.). Integrate these data into a centralized data set to generate environmental sensing data of the satellite observation site. Perform a preliminary analysis of the environmental sensing data to identify electromagnetic sources that interfere with satellite signal reception. Electromagnetic sources may include communication base stations (such as mobile communication base stations, broadcast towers) and power facilities (such as transformers, power lines). According to the type and location of the interference source, define interference signal screening nodes, including communication base station screening nodes and transformer screening nodes. These nodes represent areas in a specific area where the electromagnetic signal strength is high and interferes with the satellite signal. Perform a detailed analysis of the electromagnetic source in each screening node to evaluate its potential impact on the satellite signal. The analysis content includes signal frequency, strength, and propagation path. Calculate the interference signal impact degree of each node, and generate interference signal impact degree data based on the intensity and frequency of electromagnetic radiation. Express the analysis results in numerical form to form an interference signal impact degree data set. This data set should contain the interference signal strength, frequency range and potential impact on satellite signal reception for each screened node. Using the interference signal impact degree data, further screen the nodes that have been initially screened to identify the electromagnetic interference sources that have the greatest impact on satellite signals. Focus on those nodes with a higher degree of impact, such as high-power communication base stations or large transformers. Define the screened high-impact nodes as high electromagnetic interference signal sources, which will cause significant interference to satellite signal reception. Record the location, characteristics and impact data of these high-impact signal sources to provide a reference for subsequent signal purification and optimization.

[0123] Preferably, step S23 includes the following steps:

[0124] Step S231: confirming the position of the interference signal screening node to obtain the interference signal node position data; calculating the interference distance of the satellite observation site position data according to the interference signal node position data to obtain the interference impact distance data;

[0125] Step S232: performing out-of-band radiation interference analysis on the communication base station screening nodes in the interference signal screening nodes to generate communication base station node interference feature data;

[0126] Step S233: performing equipment discharge interference analysis on the transformer screening node in the interference signal screening node to generate transformer node interference feature data;

[0127] Step S234: Perform electromagnetic interference impact analysis on the transformer node interference feature data and the communication base station node interference feature data to generate interference signal node electromagnetic interference impact data; perform electromagnetic interference impact degree analysis on the interference signal node electromagnetic interference impact data according to the interference impact distance data to generate interference signal impact degree data.

[0128] In an embodiment of the present invention, the precise geographic coordinates of the selected interference signal nodes are obtained by confirming the positions of the nodes. The position data of the interference signal nodes are recorded to ensure the correlation with the position data of the satellite observation site. According to the position data of the interference signal nodes, the distance between each interference source and the satellite observation site is calculated to obtain the interference impact distance data. The calculation of the interference distance should take into account geographical obstacles, terrain undulations and the propagation path of the interference signal. The out-of-band radiation interference analysis is performed on the communication base station screening nodes to evaluate the electromagnetic radiation generated outside the normal working frequency band. The main analysis contents include radiation spectrum, power density, interference range and its potential impact on satellite signals. The interference feature data of the communication base station nodes are generated by analysis, and the frequency range, intensity and spatial distribution characteristics of the out-of-band radiation interference are recorded. These data will be used for subsequent electromagnetic interference impact analysis. The equipment discharge interference analysis is performed on the transformer screening nodes to evaluate the electromagnetic interference caused by aging or failure of the transformer equipment. The analysis content includes the frequency, intensity and interference characteristics of the electromagnetic waves generated by the discharge to the satellite signal. The interference feature data of the transformer node is generated, and the frequency, intensity and spatial impact range of the discharge interference are recorded. Ensure that these data can accurately reflect the potential interference risk of the transformer node to the satellite signal. Combined with the interference feature data of transformer nodes and communication base station nodes, comprehensive electromagnetic interference impact analysis is performed. Through frequency superposition, strength comparison and spatial impact range analysis, the electromagnetic interference impact data of the interference signal node is generated. According to the electromagnetic interference impact data and interference impact distance data of the interference signal node, the actual interference degree of each node to the satellite observation site is evaluated. Considering the distance, signal strength and spectrum characteristics of the interference source, the interference signal impact degree data is generated.

[0129] Preferably, step S3 comprises the following steps:

[0130] Step S31: Calculate the interference signal strength of the high electromagnetic interference signal source according to the interference signal influence degree data to obtain the satellite observation interference signal;

[0131] The formula for calculating the interference signal strength is as follows:

[0132]

[0133] In the formula, is represented as interference signal, is the number of interference nodes in a complex electromagnetic environment, is the amplitude of each interference signal, is the frequency of each signal, is the initial phase of the interference signal, It is expressed as the measurement time;

[0134] Step S32: performing background signal separation on the initial satellite observation integrated signal discrete graph to generate a satellite observation background signal; performing satellite observation integrated signal calculation on the standard satellite observation station receiving signal and the satellite observation background signal through the satellite observation interference signal to obtain a satellite observation integrated signal;

[0135] The calculation formula of satellite observation integrated signal is as follows:

[0136]

[0137] In the formula, It is the integrated signal received by the Beidou navigation satellite continuous observation station. is the initial Beidou navigation satellite signal, is the interference signal, is the background signal;

[0138] Step S33: constructing a digital model of the integrated signal based on the satellite observation integrated signal to generate a digital model of the integrated satellite observation signal;

[0139] The formula for constructing the comprehensive signal digital model is as follows:

[0140]

[0141] In the formula, It represents the integrated signal received by the BeiDou navigation satellite continuous observation station. Represents the initial Beidou navigation satellite signal, Expressed as the number of interfering nodes in a complex electromagnetic environment, is the amplitude of each interference signal, is the frequency of each signal, is the initial phase of the interference signal, is the measurement time, It is indicated as background signal;

[0142] Step S34: calculating the type interference signal frequency of the satellite observation interference signal according to the interference signal influence degree data, and generating communication base station type interference signal source frequency data and transformer type interference signal source frequency data;

[0143] The formula for calculating the frequency of the type interference signal is as follows;

[0144]

[0145]

[0146] In the formula, It represents the frequency data of interference signal source of communication base station type. Represented as transformer type interference signal source frequency data;

[0147] Step S35: Using the Beidou navigation satellite observation data purification formula to purify the communication base station type interference signal source frequency data and the transformer type interference signal source frequency data based on the comprehensive satellite observation signal digital model, to generate a satellite observation comprehensive pure signal.

[0148] In the embodiment of the present invention, the signal of each interference node is calculated one by one according to the parameters (amplitude, frequency, initial phase) in the interference signal impact degree data. All interference signal components are added together to obtain the total satellite observation interference signal The background signal is separated from the initial satellite observation integrated signal discrete graph, and the main interference components and satellite signals are removed to obtain the satellite observation background signal. , the separation of background signals should consider all non-interference sources and non-satellite signal components. The satellite observation composite signal is calculated using the formula for calculating the satellite observation composite signal, and the composite signal digital model is constructed using the formula for constructing the composite signal digital model. This formula combines the initial signal, the interference signal and the background signal to describe the composite signal received by the satellite observation station. Based on the above formula, a composite satellite observation signal digital model is generated, which can comprehensively reflect the characteristics of the actual satellite observation signal, including the influence of interference and background signals. The frequency of the type interference signal of the satellite observation interference signal is calculated based on the interference signal influence degree data, and the frequency data of the communication base station type interference signal source and the frequency data of the transformer type interference signal source are calculated. The frequency data of the communication base station and transformer type interference signal sources are calculated based on the interference signal influence degree data, and a frequency curve is generated. and . Using the Beidou navigation satellite observation data purification formula, the interference signal source frequency data of communication base station type and transformer type is purified based on the integrated satellite observation signal digital model. This process involves removing or reducing the influence of interference signals to obtain clearer satellite observation signals. Through the purification process, a satellite observation integrated pure signal is generated, which is optimized and corrected under the influence of interference signals and background signals.

[0149] Preferably, the Beidou navigation satellite observation data purification formula in step S35 is as follows:

[0150]

[0151]

[0152] In the formula, It is represented by the integrated pure signal of satellite observation, It represents the integrated signal received by the BeiDou navigation satellite continuous observation station. Expressed as the number of interfering nodes in a complex electromagnetic environment, The amplitude of the interference signal source represented by the communication base station type, Expressed as the amplitude of the interference signal source of the transformer type, Represents the initial phase of the interference signal source of the communication base station type, The initial phase of the interference signal source represented by the transformer type, It represents the frequency data of interference signal source of communication base station type. Expressed as transformer type interference signal source frequency data, Represented as a transformer type interference signal, Represented as background signal.

[0153] The present invention analyzes and integrates a Beidou navigation satellite observation data purification formula, in which It is represented as the original integrated signal, including satellite signal, interference signal and background signal. It is the basic data for purification. The amplitude of the interference signal source represented by the communication base station type indicates the interference intensity of the communication base station on the signal. The higher the amplitude value, the greater the impact of the interference signal on the observed signal. The frequency of interference signals from communication base stations is defined. The frequency of interference signals is one of their characteristics, and accurate frequency data helps to accurately remove this interference. The initial phase of the interference signal source, represented as a communication base station type, describes the phase offset of the interference signal, which is crucial for the accurate representation of the interference signal. The phase information helps to correctly align with the interference part in the observed signal. Represented as a transformer type interference signal, this is a transformer type interference signal, according to its amplitude ,frequency and initial phase Calculated, it represents the contribution of the transformer interference signal to the overall signal. The amplitude of the interference signal source of the transformer type is expressed as Similarly, amplitude affects how much the interfering signal affects the observed signal. It is expressed as transformer type interference signal source frequency data, which defines the frequency of the transformer interference signal and helps to identify and separate this type of interference signal. The initial phase of the interference signal source represented as a transformer type, the phase information of the interference signal, is used to accurately describe the time characteristics of the interference signal. Represented as background signal, the background signal is other non-interference signals mixed in the integrated signal, which needs to be separated out so that the pure signal after removing the interference signal can more accurately reflect the actual observation data. When using the conventional Beidou navigation satellite observation data purification formula in this field, a satellite observation comprehensive pure signal can be obtained. By applying the Beidou navigation satellite observation data purification formula provided by the present invention, the satellite observation comprehensive pure signal can be calculated more accurately. The purification formula obtains the pure signal of satellite observation by subtracting the estimated interference signal (including interference signals of communication base stations and transformer types) from the integrated satellite observation signal. The key to the formula is to accurately represent and remove specific interference signals so that the remaining signal is as close to the actual satellite observation data as possible. The interference signals (interference signals of communication base stations and transformers) and the background signals involved in the formula are processed separately. By calculating the impact of these two interference signals separately and subtracting them from the integrated signal, their impact on the satellite observation signal can be effectively eliminated. Accurate interference signal calculation (including frequency, amplitude and phase) and background signal separation ensure that the purified signal is as real as possible. This process improves the quality of satellite observation signals and makes the signal data closer to the actual observation results. The purified satellite observation signals can be used for further analysis and applications, such as navigation, positioning and other high-precision scenarios to ensure the reliability and accuracy of the data.

[0154] Preferably, step S4 comprises the following steps:

[0155] Step S41: discretizing the satellite observation integrated pure signal to generate an optimized satellite observation integrated signal discrete curve;

[0156] Step S42: performing discrete overlap of the optimized satellite observation integrated signal discrete curve and the initial satellite observation integrated signal discrete graph to generate a satellite observation signal comparison discrete graph;

[0157] Step S43: perform three-dimensional spatial accuracy observation on the satellite observation signal comparison discrete graph to generate a spatial observation accuracy comparison graph; perform accuracy optimization analysis on the spatial observation accuracy comparison graph to obtain observation accuracy optimization data; compare the observation accuracy optimization data with a preset accuracy optimization threshold. When the observation accuracy optimization data is less than the preset accuracy optimization threshold, return to S35 and repeat the execution until the observation accuracy optimization data is greater than or equal to the preset accuracy optimization threshold to perform high-precision Beidou navigation satellite observation operations.

[0158] In an embodiment of the present invention, the satellite observation integrated pure signal is discretized. The signal is converted from a continuous domain to a discrete domain to meet the needs of digital processing and analysis. The discretization process may include operations such as sampling and quantization to convert the signal into a signal value at a discrete time point. Based on the discretized signal data, an optimized satellite observation integrated signal discrete curve is generated. This curve represents the value of the optimized signal at a discrete time point. The optimized satellite observation integrated signal discrete curve is compared with the initial satellite observation integrated signal discrete graph. The coincidence process involves aligning the discrete points of the two for detailed analysis. During the comparison process, ensure that the discrete points of the two are aligned within the same time and space range to achieve accurate comparison. Based on the discrete coincidence results, a satellite observation signal comparison discrete graph is generated. The graph shows the difference between the optimized signal and the initial signal, helping to identify the effect of signal improvement. The satellite observation signal comparison discrete graph is subjected to three-dimensional spatial accuracy observation, involving mapping the signal data into a three-dimensional space to analyze its distribution and accuracy in space. The observation accuracy optimization data reflects the resolution and accuracy of the optimized signal in space. The observation accuracy optimization data is compared with a preset accuracy optimization threshold. The preset threshold represents the minimum standard for signal accuracy. If the observation accuracy optimization data is less than the preset threshold, return to step S35 and repeat the signal purification to further improve the signal quality. When the observation accuracy optimization data is greater than or equal to the preset accuracy optimization threshold, it means that the signal accuracy has met the requirements. High-precision Beidou navigation satellite observation operations can be carried out, and the optimized signals can be used for accurate navigation and positioning tasks.

[0159] Preferably, performing three-dimensional spatial accuracy observation on the satellite observation signal comparison discrete graph to obtain observation accuracy optimization data includes:

[0160] Perform time segmentation on the satellite observation signal contrast discrete graph to generate observation time segmentation data;

[0161] The initial discrete range of the satellite observation signal comparison discrete graph is calculated by observing the time segment data to obtain the initial signal discrete range data; the error convergence calculation of the initial signal discrete range data is performed by optimizing the satellite observation comprehensive signal discrete curve to generate satellite observation accuracy error optimization data;

[0162] According to the satellite observation accuracy error optimization data, the three-dimensional spatial accuracy of the satellite observation signal comparison discrete map is calculated to obtain the observation accuracy optimization data.

[0163] In an embodiment of the present invention, the satellite observation signal contrast discrete graph is processed by time segmentation. The signal data is divided into several segments according to time, and each time segment represents the signal data within a specific time range. The purpose of time segmentation is to refine data analysis and facilitate calculation and optimization of signal accuracy. According to the time segmentation result, the observation time segmentation data is generated. These data contain the signal characteristics of each time period and are used for subsequent accuracy calculation. Using the observation time segmentation data, the initial discrete range calculation is performed on the satellite observation signal contrast discrete graph. The range represents the discrete degree and distribution of the signal in each time period. The initial discrete range calculation usually includes information such as the deviation range and fluctuation range of the signal. Through calculation, the initial signal discrete range data is generated. These data describe the discrete characteristics of the initial signal in different time periods. The initial signal discrete range data is calculated by using the optimized satellite observation integrated signal discrete curve. This process aims to reduce the error within the signal discrete range and make the discrete value of the signal closer to the actual value. The error convergence calculation involves comparing the optimized signal with the initial discrete range data, identifying and correcting the error source. Through the error convergence calculation, satellite observation accuracy error optimization data is generated. These data represent the degree of error reduction and accuracy improvement in the optimized signal. Based on the satellite observation accuracy error optimization data, the satellite observation signal is compared with the discrete graph for three-dimensional spatial accuracy observation. This includes mapping the discrete graph into three-dimensional space and analyzing its spatial distribution and accuracy. The three-dimensional spatial accuracy observation involves a detailed analysis of the spatial distribution of the signal and evaluating its performance in three-dimensional space. The observation accuracy optimization data is extracted from the three-dimensional spatial accuracy observation. These data show the accuracy improvement of the optimized signal in three-dimensional space.

[0164] The beneficial effect of the present invention is that by collecting signals from satellite observation sites and discretizing these signals from multiple angles, a discrete graph of the initial satellite observation integrated signal is generated. Basic signal data and discrete graphs are obtained, providing initial data support for subsequent signal analysis and optimization. Environmental perception data of satellite observation sites are generated, the influence of interference signals is analyzed, and the source of high electromagnetic interference signals is identified, which helps to identify and evaluate the influence of interference signals, can accurately locate the source of electromagnetic interference, and helps to locate the target of subsequent signal purification. A digital model of integrated satellite observation signals is established, the frequency of interference signals is calculated, and signal purification is performed. By establishing a digital model and calculating the frequency of interference signals, the purity of the signal is improved, the quality and accuracy of the signal are enhanced, and the foundation for high-precision satellite observation is laid. The discretization process of the satellite observation integrated signal is optimized, the accuracy of the optimized signal is compared with the accuracy of the initial signal, and the accuracy is optimized. Through continuous optimization and accuracy evaluation, the accuracy of satellite observation data is improved to ensure that high-precision navigation requirements are met. Through gradual optimization and refined processing, high-precision satellite observation is finally achieved, and the reliability and accuracy of the satellite navigation system are improved. Therefore, the present invention improves the efficiency of identifying and filtering interference signals through systematic interference identification, signal purification, multi-angle processing and automated precision optimization, thereby effectively improving the spatial positioning accuracy of Beidou navigation satellites.

[0165] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0166] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A method for purifying Beidou navigation satellite observation data under complex electromagnetic background, characterized in that: The following steps are involved: Step S1: Obtain satellite observation site location data and satellite location data; Collect satellite signals from the satellite observation site based on the satellite observation site position data and the satellite position data to obtain a receiving signal from the satellite observation site; Discretize the signals received by the satellite observation station into multi-angle initial signals to generate a discrete graph of the initial satellite observation integrated signal; Step S2: performing environmental perception of the satellite observation site according to the satellite observation site location data to generate satellite observation site environmental perception data; Analyze the interference signal impact degree of the satellite observation site environmental perception data to generate interference signal impact degree data; use the interference signal impact degree data to perform secondary screening of high-impact nodes in the satellite observation site environmental perception data to generate high electromagnetic interference signal sources; Step S3: constructing a comprehensive signal digital model for the high electromagnetic interference signal source, the satellite observation site receiving signal and the initial satellite observation comprehensive signal discrete graph according to the interference signal influence degree data, and generating a comprehensive satellite observation signal digital model; calculating the type interference signal frequency of the high electromagnetic interference signal source according to the interference signal influence degree data, and generating communication base station type interference signal source frequency data and transformer type interference signal source frequency data; performing signal purification on the communication base station type interference signal source frequency data and the transformer type interference signal source frequency data based on the comprehensive satellite observation signal digital model, and generating a satellite observation comprehensive pure signal; Step S4: discretize the satellite observation integrated pure signal to generate an optimized satellite observation integrated signal discrete curve; perform three-dimensional spatial accuracy observation on the optimized satellite observation integrated signal discrete curve and the initial satellite observation integrated signal discrete graph to obtain observation accuracy optimization data; compare the observation accuracy optimization data with a preset accuracy optimization threshold, and when the observation accuracy optimization data is less than the preset accuracy optimization threshold, repeat the signal purification until the observation accuracy optimization data is greater than or equal to the preset accuracy optimization threshold, so as to perform high-precision Beidou navigation satellite observation operations.

2. The Beidou navigation satellite observation data purification method under complex electromagnetic background according to claim 1 is characterized in that: Step S1 includes the following steps: Step S11: Acquire satellite observation site location data and satellite location data; Step S12: collecting satellite signals from the satellite observation site based on the satellite observation site position data and the satellite position data to obtain a satellite observation site receiving signal; Step S13: performing signal preprocessing on the satellite observation site receiving signal to generate a standard satellite observation site receiving signal, wherein the signal preprocessing includes signal denoising, signal gain and signal normalization; Step S14: discretize the signals received by the standard satellite observation site into multi-angle initial signals to generate a discrete graph of the initial satellite observation integrated signal.

3. The Beidou navigation satellite observation data purification method under complex electromagnetic background according to claim 2 is characterized in that: Step S14 includes the following steps: Step S141: performing satellite signal reception angle analysis on the satellite observation site location data and the satellite location data to generate satellite signal reception angle data; Step S142: performing signal digitization processing on the signal received by the standard satellite observation site to obtain a satellite observation reception numerical signal sequence; Step S143: performing multi-angle decomposition of the satellite observation reception numerical signal sequence through the satellite signal reception angle data to generate a signal multi-angle component; performing angle signal classification on the standard satellite observation station reception signal according to the signal multi-angle component to generate an angle classification signal; Step S144: discretize the angle classification signals in time and space to generate a discrete graph of the initial satellite observation integrated signal.

4. The Beidou navigation satellite observation data purification method under complex electromagnetic background according to claim 3 is characterized in that: Step S144 includes the following steps: Step S1441: time discretize the angle classification signal to generate discrete time point signal values; Step S1442: spatially discretizing the angle classification signal to generate a discrete spatial signal grid; Step S1443: synthesizing angle signal components based on discrete time point signal values ​​and discrete space signal grids, thereby generating a multi-angle signal matrix; Step S1444: extract signal features from the multi-angle signal matrix to obtain a multi-angle signal feature matrix; map the multi-angle signal feature matrix to a two-dimensional image for visualization to generate an initial satellite observation integrated signal discrete map.

5. The Beidou navigation satellite observation data purification method under complex electromagnetic background according to claim 1 is characterized in that: Step S2 includes the following steps: Step S21: performing environmental perception of the satellite observation site according to the satellite observation site location data to generate satellite observation site environmental perception data; Step S22: Screening interference signal impact nodes on the satellite observation site environment perception data to obtain interference signal screening nodes, wherein the interference signal screening nodes include communication base station screening nodes and transformer screening nodes; Step S23: analyzing the interference signal impact degree of the interference signal screening node to generate interference signal impact degree data; Step S24: using the interference signal impact degree data to perform secondary screening of high-impact nodes on the interference signal screening nodes to generate high electromagnetic interference signal sources.

6. The Beidou navigation satellite observation data purification method under complex electromagnetic background according to claim 5 is characterized in that: Step S23 includes the following steps: Step S231: confirming the position of the interference signal screening node to obtain the interference signal node position data; calculating the interference distance of the satellite observation site position data according to the interference signal node position data to obtain the interference impact distance data; Step S232: performing out-of-band radiation interference analysis on the communication base station screening nodes in the interference signal screening nodes to generate communication base station node interference feature data; Step S233: performing equipment discharge interference analysis on the transformer screening node in the interference signal screening node to generate transformer node interference feature data; Step S234: Perform electromagnetic interference impact analysis on the transformer node interference feature data and the communication base station node interference feature data to generate interference signal node electromagnetic interference impact data; perform electromagnetic interference impact degree analysis on the interference signal node electromagnetic interference impact data according to the interference impact distance data to generate interference signal impact degree data.

7. The Beidou navigation satellite observation data purification method under complex electromagnetic background according to claim 1 is characterized in that: Step S3 includes the following steps: Step S31: Calculate the interference signal strength of the high electromagnetic interference signal source according to the interference signal influence degree data to obtain the satellite observation interference signal; The formula for calculating the interference signal strength is as follows: In the formula, is represented as interference signal, is the number of interference nodes in a complex electromagnetic environment, is the amplitude of each interference signal, is the frequency of each signal, is the initial phase of the interference signal, It is expressed as the measurement time; Step S32: performing background signal separation on the initial satellite observation integrated signal discrete graph to generate a satellite observation background signal; performing satellite observation integrated signal calculation on the standard satellite observation station receiving signal and the satellite observation background signal through the satellite observation interference signal to obtain a satellite observation integrated signal; The calculation formula of satellite observation integrated signal is as follows: In the formula, It is the integrated signal received by the Beidou navigation satellite continuous observation station. is the initial Beidou navigation satellite signal, is the interference signal, is the background signal; Step S33: constructing a digital model of the integrated signal based on the satellite observation integrated signal to generate a digital model of the integrated satellite observation signal; The formula for constructing the comprehensive signal digital model is as follows: In the formula, It represents the integrated signal received by the BeiDou navigation satellite continuous observation station. Represents the initial Beidou navigation satellite signal, Expressed as the number of interfering nodes in a complex electromagnetic environment, is the amplitude of each interference signal, is the frequency of each signal, is the initial phase of the interference signal, is the measurement time, It is indicated as background signal; Step S34: calculating the type interference signal frequency of the satellite observation interference signal according to the interference signal influence degree data, and generating communication base station type interference signal source frequency data and transformer type interference signal source frequency data; The formula for calculating the frequency of the type interference signal is as follows; In the formula, Represents the frequency data of interference signal source of communication base station type, Represented as transformer type interference signal source frequency data; Step S35: Using the Beidou navigation satellite observation data purification formula to purify the communication base station type interference signal source frequency data and the transformer type interference signal source frequency data based on the comprehensive satellite observation signal digital model, to generate a satellite observation comprehensive pure signal.

8. The Beidou navigation satellite observation data purification method under complex electromagnetic background according to claim 7 is characterized in that: The Beidou navigation satellite observation data purification formula in step S35 is as follows: In the formula, It is represented by the integrated pure signal of satellite observation, It represents the integrated signal received by the BeiDou navigation satellite continuous observation station. Expressed as the number of interfering nodes in a complex electromagnetic environment, The amplitude of the interference signal source represented by the communication base station type, Expressed as the amplitude of the interference signal source of the transformer type, Represents the initial phase of the interference signal source of the communication base station type, The initial phase of the interference signal source represented by the transformer type, Represents the frequency data of interference signal source of communication base station type, Expressed as transformer type interference signal source frequency data, Represented as a transformer type interference signal, Represented as background signal.

9. The Beidou navigation satellite observation data purification method under complex electromagnetic background according to claim 1 is characterized in that: Step S4 includes the following steps: Step S41: discretizing the satellite observation integrated pure signal to generate an optimized satellite observation integrated signal discrete curve; Step S42: performing discrete overlap of the optimized satellite observation integrated signal discrete curve and the initial satellite observation integrated signal discrete graph to generate a satellite observation signal comparison discrete graph; Step S43: perform three-dimensional spatial accuracy observation on the satellite observation signal comparison discrete graph to generate a spatial observation accuracy comparison graph; perform accuracy optimization analysis on the spatial observation accuracy comparison graph to obtain observation accuracy optimization data; compare the observation accuracy optimization data with a preset accuracy optimization threshold. When the observation accuracy optimization data is less than the preset accuracy optimization threshold, return to S35 and repeat the execution until the observation accuracy optimization data is greater than or equal to the preset accuracy optimization threshold to perform high-precision Beidou navigation satellite observation operations.

10. The Beidou navigation satellite observation data purification method under complex electromagnetic background according to claim 9 is characterized in that: The satellite observation signal is compared with the discrete graph to perform three-dimensional spatial precision observation, and the observation precision optimization data obtained include: Perform time segmentation on the satellite observation signal contrast discrete graph to generate observation time segmentation data; The initial discrete range of the satellite observation signal comparison discrete graph is calculated by observing the time segment data to obtain the initial signal discrete range data; the error convergence calculation of the initial signal discrete range data is performed by optimizing the satellite observation comprehensive signal discrete curve to generate satellite observation accuracy error optimization data; According to the satellite observation accuracy error optimization data, the three-dimensional spatial accuracy of the satellite observation signal comparison discrete map is calculated to obtain the observation accuracy optimization data.

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