An algorithm for eliminating gross errors in Beidou navigation satellite positioning data near vast waters

Abstract

The present invention relates to the technical field of intelligent processing of Beidou navigation satellite signals, and in particular to an algorithm for eliminating gross errors in Beidou navigation satellite positioning data near a vast area of ​​water. The method comprises the following steps: acquiring a satellite receiving signal; performing signal preprocessing on the satellite receiving signal to generate a standard satellite receiving signal; performing indirect path interference analysis on the standard satellite receiving signal to obtain a direct path receiving signal and an indirect path receiving signal; performing signal phase disturbance analysis on the direct path receiving signal and the indirect path receiving signal using a deduced comprehensive signal model to generate a phase drift of the indirect path receiving signal. The present invention uses a signal processing and repair algorithm to intelligently identify the reflected signals generated by a large area of ​​water, and automatically eliminates the gross errors generated by the reflected signals, thereby ensuring the correctness and stability of the measurement results.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent processing of Beidou navigation satellite signals, and in particular to an algorithm for eliminating gross errors in Beidou navigation satellite positioning data near a vast water area. Background Art

[0002] Under ideal conditions, the Beidou navigation satellite positioning receiver only receives signals from Beidou navigation satellites in orbit (direct signals) and calculates the precise spatial position of the receiver antenna. However, in complex application scenarios, especially in vast waters such as near rivers, lakes, and reservoirs, satellite signals (indirect signals) will be reflected. After being received by the Beidou navigation satellite positioning receiver, they will interfere with the signals directly from the Beidou satellite (direct path), commonly known as the indirect path effect, which will inevitably cause gross errors in the solution results. These gross errors will seriously affect the positioning, navigation accuracy and reliability of Beidou navigation satellites, especially in applications with high precision requirements, such as river observation, water navigation and hydrological monitoring. Early gross error elimination methods were mainly based on statistical principles, and gross errors were detected and eliminated by setting thresholds, using least squares methods and residual analysis. However, these methods have limited processing capabilities for the impact of the highly random indirect path effect on navigation and positioning, and inevitably cause gross errors in the solution results. There is an urgent need to use signal processing and repair algorithms to intelligently identify the reflected signals generated by large areas of water and automatically eliminate the gross errors caused by them, so as to ensure the accuracy and stability of Beidou navigation satellite measurement results. Summary of the invention

[0003] Based on this, it is necessary to provide a Beidou navigation satellite positioning data gross error elimination algorithm near vast waters to solve at least one of the above technical problems.

[0004] To achieve the above purpose, an algorithm for eliminating gross errors in Beidou navigation satellite positioning data near vast waters is provided, and the method comprises the following steps:

[0005] Step S1: Acquire a satellite reception signal; perform signal preprocessing on the satellite reception signal to generate a standard satellite reception signal;

[0006] Step S2: performing indirect path interference analysis on the standard satellite receiving signal to obtain a direct path receiving signal and an indirect path receiving signal; performing signal phase disturbance analysis on the direct path receiving signal and the indirect path receiving signal using a deduced integrated signal model to generate a phase drift amount of the indirect path receiving signal;

[0007] Step S3: performing actual signal disturbance analysis on the standard satellite reception signal through the indirect path reception signal phase drift to generate actual signal disturbance data; performing average disturbance amplitude calculation on the actual signal disturbance data to obtain actual signal average disturbance amplitude data; performing multi-level signal interference elimination on the actual signal disturbance data based on the actual signal average disturbance amplitude data using the Beidou navigation satellite positioning data gross error elimination algorithm, thereby generating a satellite reception disturbance optimization signal;

[0008] Step S4: Perform signal environment simulation based on the satellite reception disturbance optimization signal to obtain signal environment simulation data; perform signal elimination optimization performance evaluation on the environmental simulation data through the Beidou navigation satellite positioning data gross error elimination algorithm to generate optimization performance evaluation data; perform signal gross error elimination environment adaptability analysis on the satellite reception disturbance optimization signal through the optimization performance evaluation data to generate data gross error elimination algorithm adaptability data.

[0009] The present invention obtains satellite receiving signals. The satellite receiving signals are preprocessed to generate standard satellite receiving signals. The signal preprocessing step helps to remove noise and interference in the initial receiving signal, generate a clean and standardized signal, and facilitate subsequent processing. The standard satellite receiving signal is subjected to indirect path interference analysis to obtain a direct path receiving signal and an indirect path receiving signal. The direct path receiving signal and the indirect path receiving signal are subjected to signal phase disturbance analysis using a deduced comprehensive signal model to generate an indirect path receiving signal phase drift amount. By separating the direct path and the indirect path signals and analyzing the indirect path phase drift amount, the influence of the multipath effect on the signal can be better understood and eliminated, and the signal accuracy can be improved. The standard satellite receiving signal is subjected to actual signal disturbance analysis using the indirect path receiving signal phase drift amount to generate actual signal disturbance data. The actual signal disturbance data is subjected to average disturbance amplitude calculation to obtain actual signal average disturbance amplitude data. The Beidou navigation satellite positioning data gross error elimination algorithm is used to perform multi-level signal interference elimination on the actual signal disturbance data based on the actual signal average disturbance amplitude data to generate a satellite receiving disturbance optimization signal. This step can effectively reduce the error in the signal and improve the signal quality by analyzing and calculating the disturbance amplitude of the actual signal and using the algorithm to perform multi-level signal interference elimination. Signal environment simulation is performed based on the satellite receiving disturbance optimization signal to obtain signal environment simulation data. The signal elimination optimization performance of the environment simulation data is evaluated by the Beidou navigation satellite positioning data gross error elimination algorithm to generate optimization performance evaluation data. The satellite receiving disturbance optimization signal is analyzed for signal gross error elimination environmental adaptability by optimizing the performance evaluation data to generate data gross error elimination algorithm adaptability data. Through signal environment simulation and adaptability analysis, the performance of the signal elimination algorithm is evaluated and optimized to ensure that the algorithm can work effectively in various environments, thereby improving the accuracy and reliability of satellite positioning. Through the above steps, the method can effectively process and optimize the satellite receiving signal, eliminate interference and errors in the signal, and improve the stability and accuracy of the signal. This is of great significance for improving the accuracy of Beidou navigation satellite positioning. Therefore, the present invention uses a signal processing and repair algorithm to intelligently identify the reflection signal generated by a large area of ​​water, and automatically eliminates the gross errors generated by it, thereby ensuring the correctness and stability of the measurement results.

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

[0011] Step S11: Acquire satellite reception signals through a Beidou navigation satellite positioning receiver;

[0012] Step S12: converting the satellite received signal into a digital signal to obtain a satellite received digital signal;

[0013] Step S13: demodulating the satellite received digital signal to generate a satellite demodulated signal;

[0014] Step S14: Perform signal gain on the satellite demodulated signal to obtain a standard satellite reception signal.

[0015] The present invention can accurately receive satellite signals through the Beidou navigation satellite positioning receiver to ensure that the received signal contains all necessary positioning information. Performing digital signal conversion helps to convert the received analog signal into a digital signal that is easier to process, which is convenient for subsequent signal processing steps. The signal demodulation step helps to extract effective satellite positioning information from the digital signal and eliminate unnecessary interference and noise. Gain processing is performed on the demodulated signal to improve the strength and quality of the signal, making it more stable and reliable, and laying a good foundation for subsequent interference analysis and optimization. Through detailed signal preprocessing, indirect path interference analysis, actual signal disturbance analysis, signal environment simulation and adaptability analysis, step S1 can effectively eliminate interference and errors in satellite reception signals, improve the accuracy and stability of signals, and improve the accuracy of Beidou navigation satellite positioning.

[0016] Preferably, step S2 comprises the following steps:

[0017] Step S21: performing reception timing analysis on the standard satellite reception signal to obtain satellite signal reception timing data;

[0018] Step S22: performing indirect path interference analysis on the standard satellite reception signal through the satellite signal reception timing data to obtain a direct path reception signal and an indirect path reception signal;

[0019] Step S23: constructing a deduced integrated signal model; using the deduced integrated signal model to perform GNSS integrated signal deduction on the direct path received signal and the indirect path received signal, thereby generating a satellite integrated deduced signal;

[0020] Step S24: performing signal phase disturbance analysis on the indirect path receiving signal according to the satellite comprehensive deduction signal to generate a phase drift amount of the indirect path receiving signal.

[0021] The present invention can accurately determine the arrival time and path of the signal through receiving timing analysis, thereby providing an accurate data basis for subsequent indirect path interference analysis. By using the receiving timing data for indirect path interference analysis, the direct path and indirect path signals can be effectively separated, so as to better understand and eliminate the impact of multipath effects on the signal. The deduced comprehensive signal model combines the direct path and indirect path signals, and can generate more accurate satellite comprehensive deduction signals through comprehensive analysis, providing reliable data support for subsequent phase disturbance analysis. Signal phase disturbance analysis can quantify the phase drift of the indirect path signal, thereby providing key parameters for actual signal disturbance analysis and optimization, and effectively reducing the error in the signal. Through multi-step processing of satellite received signals, including signal preprocessing, indirect path interference analysis, actual signal disturbance analysis, and signal environment simulation and adaptability analysis, it is possible to effectively reduce interference and errors in the signal and improve the accuracy and stability of Beidou navigation satellite positioning.

[0022] Preferably, step S22 includes the following steps:

[0023] Step S221: performing time sequence signal segmentation on the standard satellite reception signal according to the satellite signal reception time sequence data to obtain time sequence segmentation signal segments;

[0024] Step S222: performing Hilbert transform on the time series segmentation signal segment to obtain the time series segmentation signal envelope; performing change trend analysis on the time series segmentation signal envelope to generate time series segmentation signal strength data;

[0025] Step S223: performing instantaneous signal phase calculation on the time-series segmentation signal envelope to obtain instantaneous signal phase data; performing phase difference analysis of adjacent signal segments on the time-series segmentation signal segments using the instantaneous signal phase data to generate instantaneous phases of adjacent signal segments;

[0026] Step S224: performing indirect path interference analysis on the time-series segmented signal segments based on the time-series segmented signal strength data and the instantaneous phases of adjacent signal segments to obtain direct path received signals and indirect path received signals;

[0027] The calculation formula for indirect path interference analysis is as follows:

[0028]

[0029]

[0030] In the formula, Represents the direct path receiving signal, Indicates that the signal is received by the indirect path, Expressed as the amplitude of the direct path signal, Expressed as the phase of the direct path signal, Expressed as the signal reflection coefficient, Expressed as the amplitude of the indirect path signal, Represents the phase delay caused by the indirect path signal.

[0031] The present invention can decompose the received satellite signal into multiple independent signal segments through time-series signal segmentation, so as to analyze the characteristics of each signal segment more finely. The time-series segmentation signal envelope is obtained through Hilbert transform, and the change trend is analyzed, so as to extract the intensity change characteristics of the signal, so as to better understand the propagation characteristics of the signal. By calculating the phase of the instantaneous signal and analyzing the phase difference of adjacent signal segments, the phase change of the signal can be accurately measured, so as to provide accurate phase data for interference analysis. By performing indirect path interference analysis on the time-series segmentation signal segment, the direct path and indirect path signals can be effectively distinguished, and the amplitude and phase relationship between the two can be calculated by formula, so as to better eliminate the interference caused by the indirect path. Step S22 provides a specific process of indirect path interference analysis. Through signal segmentation, envelope analysis, phase calculation and interference analysis, the direct path and indirect path signals can be effectively separated and analyzed, which can greatly reduce the interference in the signal and improve the accuracy and reliability of Beidou navigation satellite positioning.

[0032] Preferably, step S23 includes the following steps:

[0033] Step S231: using an environmental sensor to collect environmental information of a Beidou navigation satellite positioning receiver to obtain receiver environmental information data;

[0034] Step S232: performing three-dimensional environment modeling on the receiver environment information data to obtain three-dimensional receiver environment data; performing signal ray tracing on the direct path received signal and the indirect path received signal through the three-dimensional receiver environment data to generate signal propagation simulation data, wherein the signal propagation simulation data includes propagation path simulation data and signal reflection simulation data;

[0035] Step S233: training a comprehensive signal model based on the propagation path simulation data and the signal reflection simulation data, thereby generating a deduced comprehensive signal model; importing the direct path received signal and the indirect path received signal into the deduced comprehensive signal model for signal superposition, thereby generating a satellite comprehensive deduced signal;

[0036] The signal superposition processing formula for the deduced comprehensive signal model is as follows:

[0037]

[0038] In the formula, It is represented by the satellite integrated deduction signal. Represents the direct path receiving signal, Indicates that the signal is received by the indirect path, Expressed as the signal reflection coefficient, It is represented as the phase delay caused by the indirect path signal;

[0039] The generalized formula of satellite integrated deduction signal is as follows:

[0040]

[0041] In the formula, Represented as the deduced comprehensive signal model, It is represented by the phase delay caused by the indirect path signal, Expressed as signal reflection coefficient.

[0042] The present invention can accurately obtain the environmental characteristics around the receiver by using environmental sensors to collect receiver environmental information data, and provide basic data for subsequent three-dimensional modeling and signal propagation analysis. Through environmental three-dimensional modeling, the geometric and physical characteristics of the environment in which the receiver is located can be fully understood. Signal ray tracing simulates the propagation path and reflection of the signal, and can accurately analyze the propagation characteristics of the signal in a complex environment. Through comprehensive signal model training, an accurate signal propagation and reflection model can be constructed to better simulate and predict the behavior of the signal. Using the deduced comprehensive signal model for signal superposition, the influence of direct path and indirect path signals can be comprehensively considered, thereby generating a more accurate satellite comprehensive deduction signal. Step S23 provides a specific process for deducing a comprehensive signal model. Through environmental information collection, three-dimensional modeling and signal ray tracing, the propagation path and reflection of the signal can be accurately simulated. The comprehensive signal model training and signal superposition can effectively comprehensively consider the influence of direct path and indirect path signals, thereby generating a more accurate satellite comprehensive deduction signal, which can greatly reduce interference in the signal and improve the accuracy and reliability of Beidou navigation satellite positioning.

[0043] Preferably, step S24 includes the following steps:

[0044] Step S241: Acquire satellite orbit position data;

[0045] Step S242: extracting nearby hydrological features from the receiver environment information data to obtain receiver environment hydrological feature data, wherein the receiver environment hydrological feature data includes nearby water surface height data and nearby water surface position data;

[0046] Step S243: performing a receiving antenna position analysis on the Beidou navigation satellite positioning receiver to generate receiver receiving antenna position information data; performing a spatial periodic change analysis on the satellite orbit position data, the adjacent water surface height data and the adjacent water surface position data, and the receiver receiving antenna position information data to generate signal reception spatial change data;

[0047] Step S244: performing phase delay variation analysis on the satellite integrated deduction signal based on the signal reception spatial variation data to generate indirect signal phase delay variation data, and importing the indirect signal phase delay variation data into the deduction integrated signal model to perform phase drift deduction, thereby generating the indirect path reception signal phase drift;

[0048] The deduction formula for phase drift is as follows:

[0049]

[0050] In the formula, It is expressed as the phase drift of the indirect path received signal, Represented as indirect signal phase delay change data, Expressed as the length of the signal receiving space variation, Represented as the output value of the deduced comprehensive signal model, It is represented by the phase delay caused by the indirect path signal, Expressed as signal reflection coefficient.

[0051] The present invention can provide a basis for subsequent spatial periodic change analysis and ensure the accuracy of the analysis results by obtaining accurate satellite orbit position data. By extracting the adjacent hydrological characteristics of the receiver environment, the impact of the environment on signal propagation can be better understood, especially in the case of adjacent water bodies. By analyzing the position data of the receiving antenna, the accuracy of the spatial position of signal reception can be ensured. By performing spatial periodic change analysis, the changing law of the signal in the receiving space can be fully understood, so as to better predict the behavior of the signal. By performing phase delay change analysis based on the spatial change data of signal reception, the phase delay change data of the indirect signal can be accurately calculated. By deducing the phase drift amount by deducing the comprehensive signal model, the phase drift amount of the indirect path receiving signal can be accurately predicted, thereby improving the accuracy and reliability of Beidou navigation satellite positioning.

[0052] Preferably, step S3 comprises the following steps:

[0053] Step S31: performing actual signal disturbance analysis on the standard satellite reception signal through the phase drift of the indirect path reception signal to generate actual signal disturbance data;

[0054] Step S32: performing fast Fourier transform on the actual signal disturbance data to obtain an actual signal disturbance spectrum diagram; performing average disturbance amplitude calculation on the actual signal disturbance spectrum diagram to obtain actual signal average disturbance amplitude data;

[0055] Step S33: comparing the actual signal average disturbance amplitude data with the preset disturbance amplitude threshold. When the actual signal average disturbance amplitude data is greater than or equal to the preset disturbance amplitude threshold, the actual signal disturbance data is subjected to high-precision indirect signal interference elimination by using the Beidou navigation satellite positioning data gross error elimination algorithm, thereby generating a satellite reception disturbance optimization signal.

[0056] Step S34: When the actual signal average disturbance amplitude data is less than the preset disturbance amplitude threshold, conventional signal denoising is performed on the actual signal disturbance data to generate a satellite reception disturbance optimization signal.

[0057] The present invention can accurately identify the actual signal disturbance in the standard satellite reception signal by analyzing the phase drift of the indirect path reception signal, thereby ensuring the accuracy of subsequent signal processing. Fast Fourier Transform (FFT) can convert the actual signal disturbance data into the frequency domain, which is convenient for analyzing the spectral components and disturbance characteristics in the signal. By calculating the average disturbance amplitude, the intensity of the signal disturbance can be quantified, providing a basis for subsequent signal processing steps. When the actual signal average disturbance amplitude data exceeds the preset threshold, the Beidou navigation satellite positioning data gross error elimination algorithm is applied for high-precision interference elimination, which can effectively remove strong interference signals and improve positioning accuracy and reliability. When the actual signal average disturbance amplitude data is lower than the preset threshold, the weak interference signal can be removed through conventional signal denoising processing to ensure the quality of the generated satellite reception disturbance optimization signal.

[0058] Preferably, the Beidou navigation satellite positioning data gross error elimination algorithm in step S33 is as follows:

[0059]

[0060] In the formula, Expressed as Input signal, Expressed as output signal, Expressed as the gross error extraction coefficient, Expressed as the input signal order, Expressed as An optimization signal, Expressed as the unit weight of the indirect path low-frequency signal, Expressed as the correlation coefficient between the optimization signal and the input signal, Expressed as the autocorrelation coefficient of the input signal, Expressed as the optimized signal order, Expressed as the maximum order of the input signal, Represented as a time series of indirect signals.

[0061] The present invention analyzes and integrates a Beidou navigation satellite positioning data gross error elimination algorithm. The input signal in the algorithm represents is the original positioning signal sequence received from the Beidou navigation satellite, i.e. Input signal. Output signal The signal after optimization processing, i.e. By optimizing the input signal Obtained. Gross error extraction coefficient Represents the extraction coefficient of gross error, which is used to quantify the degree of gross error in the optimized signal. To eliminate gross errors. Input signal order Specifies the order of the input signal, which affects the complexity and effect of the optimization process. Represents the optimized signal, which is used to replace the original input signal , to reduce the gross error in the signal. The unit weight of the low-frequency signal in the indirect path It is used to weigh the influence of the low-frequency signal of the indirect path on the gross error and is a key parameter in the optimization process. The correlation coefficient between the optimization signal and the input signal Measured optimization signals With the original input signal The correlation between the input signals helps optimize the signal processing. Measured the original input signal The autocorrelation property of plays an important role in eliminating gross errors and optimizing signals. Optimizing signal order Optimization signal specified The order of the input signal affects the complexity and accuracy of the optimized signal processing. Defines the maximum order of the input signal, affecting the computational complexity of the overall algorithm and the depth of signal processing. Time series of indirect signals The time series representing the indirect signal has an impact on the time characteristics of signal processing during the optimization process. By optimizing the generation of the signal and minimizing the gross error extraction coefficient, the accuracy and stability in the Beidou navigation satellite positioning data can be effectively improved. By considering the autocorrelation of the input signal and the correlation of the optimized signal, the gross error can be extracted more accurately to avoid the influence of the abnormal points in the signal on the navigation positioning. The complex interaction between the parameters can improve the calculation efficiency and real-time performance of the algorithm while ensuring the effectiveness of the algorithm, and adapt to the complex and dynamic signal environment of the Beidou navigation system. When using the Beidou navigation satellite positioning data gross error elimination algorithm conventional in the art, the satellite reception disturbance optimization signal can be obtained. By applying the Beidou navigation satellite positioning data gross error elimination algorithm provided by the present invention, the satellite reception disturbance optimization signal can be more accurately calculated. Through the joint action of the factors in the algorithm, the above formula can effectively deal with the gross error problem in the Beidou navigation satellite positioning data, and improve positioning accuracy and reliability.

[0062] Preferably, step S4 comprises the following steps:

[0063] Step S41: performing signal environment simulation based on the satellite reception disturbance optimization signal to obtain signal environment simulation data;

[0064] Step S42: performing multi-directional reception settings on the environmental simulation data to obtain environmental simulation multi-directional reception data, wherein the multi-directional reception settings include near water direction, far water direction and sky direction reception;

[0065] Step S43: performing signal accuracy change analysis on the environment simulation multi-directional receiving data according to the signal environment simulation data, and generating a near-water receiving signal accuracy change graph, a far-water receiving signal accuracy change graph, and an antenna receiving signal accuracy change graph;

[0066] Step S44: using the Beidou navigation satellite positioning data gross error elimination algorithm to perform signal elimination optimization performance evaluation on the near-water receiving signal accuracy change diagram, the far-water receiving signal accuracy change diagram and the celestial receiving signal accuracy change diagram, and generate optimization performance evaluation data;

[0067] Step S45: Performing adaptability analysis of the signal gross error elimination environment on the satellite reception disturbance optimization signal by optimizing the performance evaluation data, and generating data gross error elimination algorithm adaptability data.

[0068] The present invention can generate simulation data in real scenarios, including different signal strengths and disturbance conditions, by simulating the signal environment based on the satellite receiving disturbance optimization signal, so as to provide authenticity and comparability for subsequent analysis. The environmental simulation data is set for multi-directional reception, including near water area, far water area and sky receiving directions. This setting can simulate the reception of satellite signals under different environmental conditions and examine the changes and influences of signals in different directions. According to the environmental simulation data, the signal accuracy change analysis is performed on the multi-directional receiving data. The near water area, far water area and sky receiving signal accuracy change diagram is generated to help understand the distribution and change law of signal accuracy under different environmental conditions. The Beidou navigation satellite positioning data gross error elimination algorithm is used to evaluate and optimize the received signal accuracy change diagram. This step can evaluate the performance of the algorithm under different signal environments and verify its effectiveness and stability in eliminating gross errors. By optimizing the performance evaluation data, the adaptability of the satellite receiving disturbance optimization signal under different signal environment conditions is analyzed. The adaptability data of the data gross error elimination algorithm is generated to help optimize the applicability and effect of the algorithm in practical applications. By generating signal environment simulation data, the optimization of Beidou navigation satellite positioning data is more practical and referenceable. The multi-directional reception setting can more comprehensively simulate the signal reception under different environmental conditions in actual scenarios, enhancing the complexity and accuracy of the simulation. Through the analysis of signal accuracy changes, we can deeply understand the characteristics of signals in different environments and provide specific guidance for the subsequent optimization of gross error elimination algorithms. Through performance evaluation and adaptability analysis, the reliability and effect of the gross error elimination algorithm in various actual application scenarios are ensured, and the accuracy and stability of data processing and navigation positioning are improved.

[0069] Preferably, performing signal environment simulation based on satellite reception disturbance optimization signal includes:

[0070] Confirm the location of the observation site based on the satellite receiving disturbance optimization signal to obtain the location information data of the observation site;

[0071] The signal environment is constructed according to the location information data of the observation site to obtain the initial signal collection environment;

[0072] The observation site location information data is subjected to a large-area water area proximity simulation to obtain the observation site-water area path data; the observation site location information data is subjected to an environmental occlusion analysis to generate the observation site environmental occlusion analysis data;

[0073] The signal collection refraction environment impact modeling is performed on the initial signal collection environment through the observation site-water path data and the observation site environmental occlusion analysis data to obtain the signal environment simulation data.

[0074] The present invention determines the location information of the observation site, which is the basis for establishing the signal environment simulation. The accurate location data of the observation site is obtained through this step. According to the location information of the observation site, the initial signal acquisition environment is constructed. This includes environmental factors such as terrain, buildings, and vegetation around the observation site, providing basic data for subsequent signal simulation. The proximity distance between the observation site and a large area of ​​water is analyzed to obtain the path data from the observation site to the water area. This step takes into account the influence of the water area on signal transmission, especially the reflection, attenuation, etc. on the signal transmission path. The environment around the observation site is blocked and the environmental blockage analysis data is generated. These data describe the degree of signal blocking by obstacles (such as buildings, mountains, etc.) on the signal transmission path. Combined with the path data from the observation site to the water area and the environmental blockage analysis data, a signal acquisition refraction environment impact model is established. This model takes into account the propagation, refraction and reflection process of the signal in the actual environment and generates the final signal environment simulation data. By confirming the location of the observation site and constructing the signal environment, the signal acquisition environment in the real world is simulated, which improves the authenticity of the signal simulation and the reliability of the model. The simulation of proximity distances in large areas of water and environmental occlusion analysis enable the model to more comprehensively consider the signal transmission characteristics under different environmental conditions and effectively predict the attenuation and changes of signals. By establishing a signal acquisition refraction environmental impact model, the propagation and impact of signals in complex environments can be accurately simulated, providing accurate data support for subsequent signal processing and optimization.

[0075] The beneficial effect of the present invention is that by preprocessing the satellite reception signal, the signal data can be cleaned and standardized, and a standard satellite reception signal can be generated, providing an accurate data basis for subsequent analysis. By performing indirect path interference analysis on the standard satellite reception signal, a direct path reception signal and an indirect path reception signal can be obtained, and a signal phase disturbance analysis is performed on it using a deduced comprehensive signal model to generate an indirect path reception signal phase drift amount, which helps to understand the interference and phase disturbance in signal transmission. The actual signal disturbance analysis of the standard satellite reception signal is performed through the indirect path reception signal phase drift amount, the actual signal disturbance data is generated, and the average disturbance amplitude is calculated to evaluate the degree of disturbance of the signal. The Beidou navigation satellite positioning data gross error elimination algorithm is used to perform multi-level signal interference elimination on the actual signal disturbance data based on the actual signal average disturbance amplitude data, thereby generating a satellite reception disturbance optimization signal, reducing signal interference and disturbance, and improving signal quality and accuracy. Based on the satellite receiving disturbance optimization signal, the signal environment simulation is performed to obtain the signal environment simulation data, and the Beidou navigation satellite positioning data gross error elimination algorithm is used to evaluate the signal elimination optimization performance of the simulation data, and the optimization performance evaluation data is generated to evaluate the optimization effect and performance of the signal. The satellite receiving disturbance optimization signal is subjected to the signal gross error elimination environment adaptability analysis through the optimization performance evaluation data, and the data gross error elimination algorithm adaptability data is generated to help evaluate the adaptability and effect of the data processing algorithm in different signal environments. Therefore, the present invention uses the signal processing repair algorithm to intelligently identify the reflected signal generated by a large area of ​​water, and automatically eliminates the gross error generated by it, thereby ensuring the correctness and stability of the measurement results. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Figure 1 A schematic diagram of the steps of an algorithm for eliminating gross errors in Beidou navigation satellite positioning data near a vast water area;

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

[0078] Figure 3 It is an original schematic diagram of the variation diagram of the accuracy of the received signal in the antenna direction in the present invention;

[0079] Figure 4 It is a schematic diagram of a change diagram of the accuracy of the celestial receiving signal after being processed by the Beidou navigation satellite positioning data gross error elimination algorithm in 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 , an algorithm for eliminating gross errors in Beidou navigation satellite positioning data near a vast water area, the method comprising the following steps:

[0085] Step S1: Acquire a satellite reception signal; perform signal preprocessing on the satellite reception signal to generate a standard satellite reception signal;

[0086] Step S2: performing indirect path interference analysis on the standard satellite receiving signal to obtain a direct path receiving signal and an indirect path receiving signal; performing signal phase disturbance analysis on the direct path receiving signal and the indirect path receiving signal using a deduced integrated signal model to generate a phase drift amount of the indirect path receiving signal;

[0087] Step S3: performing actual signal disturbance analysis on the standard satellite reception signal through the indirect path reception signal phase drift to generate actual signal disturbance data; performing average disturbance amplitude calculation on the actual signal disturbance data to obtain actual signal average disturbance amplitude data; performing multi-level signal interference elimination on the actual signal disturbance data based on the actual signal average disturbance amplitude data using the Beidou navigation satellite positioning data gross error elimination algorithm, thereby generating a satellite reception disturbance optimization signal;

[0088] Step S4: Perform signal environment simulation based on the satellite reception disturbance optimization signal to obtain signal environment simulation data; perform signal elimination optimization performance evaluation on the environmental simulation data through the Beidou navigation satellite positioning data gross error elimination algorithm to generate optimization performance evaluation data; perform signal gross error elimination environment adaptability analysis on the satellite reception disturbance optimization signal through the optimization performance evaluation data to generate data gross error elimination algorithm adaptability data.

[0089] The present invention obtains satellite receiving signals. The satellite receiving signals are preprocessed to generate standard satellite receiving signals. The signal preprocessing step helps to remove noise and interference in the initial receiving signal, generate a clean and standardized signal, and facilitate subsequent processing. The standard satellite receiving signal is subjected to indirect path interference analysis to obtain a direct path receiving signal and an indirect path receiving signal. The direct path receiving signal and the indirect path receiving signal are subjected to signal phase disturbance analysis using a deduced comprehensive signal model to generate an indirect path receiving signal phase drift amount. By separating the direct path and the indirect path signals and analyzing the indirect path phase drift amount, the influence of the multipath effect on the signal can be better understood and eliminated, and the signal accuracy can be improved. The standard satellite receiving signal is subjected to actual signal disturbance analysis using the indirect path receiving signal phase drift amount to generate actual signal disturbance data. The actual signal disturbance data is subjected to average disturbance amplitude calculation to obtain actual signal average disturbance amplitude data. The Beidou navigation satellite positioning data gross error elimination algorithm is used to perform multi-level signal interference elimination on the actual signal disturbance data based on the actual signal average disturbance amplitude data to generate a satellite receiving disturbance optimization signal. This step can effectively reduce the error in the signal and improve the signal quality by analyzing and calculating the disturbance amplitude of the actual signal and using the algorithm to perform multi-level signal interference elimination. Signal environment simulation is performed based on the satellite receiving disturbance optimization signal to obtain signal environment simulation data. The signal elimination optimization performance of the environment simulation data is evaluated by the Beidou navigation satellite positioning data gross error elimination algorithm to generate optimization performance evaluation data. The satellite receiving disturbance optimization signal is analyzed for signal gross error elimination environmental adaptability by optimizing the performance evaluation data to generate data gross error elimination algorithm adaptability data. Through signal environment simulation and adaptability analysis, the performance of the signal elimination algorithm is evaluated and optimized to ensure that the algorithm can work effectively in various environments, thereby improving the accuracy and reliability of satellite positioning. Through the above steps, the method can effectively process and optimize the satellite receiving signal, eliminate interference and errors in the signal, and improve the stability and accuracy of the signal. This is of great significance for improving the accuracy of Beidou navigation satellite positioning. Therefore, the present invention uses a signal processing and repair algorithm to intelligently identify the reflection signal generated by a large area of ​​water, and automatically eliminates the gross errors generated by it, thereby ensuring the correctness and stability of the measurement results.

[0090] In the embodiment of the present invention, reference Figure 1 The present invention is a schematic flow chart of the steps of a Beidou navigation satellite positioning data gross error elimination algorithm near a vast water area. In this example, the Beidou navigation satellite positioning data gross error elimination algorithm near a vast water area comprises the following steps:

[0091] Step S1: Acquire a satellite reception signal; perform signal preprocessing on the satellite reception signal to generate a standard satellite reception signal;

[0092] In the embodiment of the present invention, by using a specific satellite receiving device, such as a satellite antenna and a receiver, installed in a suitable position, it is ensured that the signal of the target satellite can be effectively received. The azimuth and pitch angle of the receiving device are determined to maximize the signal reception efficiency. The receiving device is started and the signal is received according to the orbit of the satellite and the predetermined receiving time window. It is ensured that the receiving device is in a stable state and the quality of the received signal meets the expected requirements. The frequency, polarization mode and other necessary parameters of the target satellite are set to ensure that the signal transmitted by the satellite can be correctly received. The received raw satellite signal data is recorded using a suitable data acquisition device or software. The accuracy and completeness of the data record are ensured, including information such as timestamps and receiving parameters. The quality of the received raw signal is evaluated, including analysis of the signal-to-noise ratio, spectrum characteristics and other relevant parameters. According to the evaluation results, it is determined whether further signal processing or correction is required. The raw signal is processed using digital signal processing techniques, such as filters and denoising algorithms. The existing noise and interference are removed to improve the clarity and accuracy of the signal. The pre-processed signal is standardized to ensure that the data format, unit and range of the signal meet the predetermined standard requirements. According to the characteristics of the receiving equipment and the calibration information, necessary corrections are made to the signal to ensure the reliability and comparability of the data.

[0093] Step S2: performing indirect path interference analysis on the standard satellite receiving signal to obtain a direct path receiving signal and an indirect path receiving signal; performing signal phase disturbance analysis on the direct path receiving signal and the indirect path receiving signal using a deduced integrated signal model to generate a phase drift amount of the indirect path receiving signal;

[0094] In an embodiment of the present invention, the received satellite signal is analyzed and processed by using specific signal processing techniques, such as spatial filtering and beamforming. Direct path received signals and indirect path received signals are distinguished to ensure that the target signal and background interference signal can be accurately obtained. An indirect path interference model is established, taking into account the propagation path, reflection and scattering phenomena of the signal. According to the propagation characteristics and receiving conditions of the signal, the propagation effect and interference of the signal on the direct path and the indirect path are determined. The interference effect of the indirect path signal on the direct path signal is analyzed, including the effects of signal attenuation, multipath effect and phase distortion caused by interference. Mathematical modeling and simulation tools, such as signal processing libraries in Matlab or Python, are used to quantitatively analyze and evaluate signal interference. A deductive comprehensive signal model is established, taking into account the phase characteristics of the direct path received signal and the indirect path received signal. Various influencing factors encountered by the signal during propagation, such as atmospheric propagation conditions, ground reflection and obstacle scattering, are determined. The phase of the direct path received signal and the indirect path received signal is mathematically modeled using the established signal model. The phase drift of the indirect path received signal relative to the direct path received signal is calculated, taking into account the influence of time changes and environmental conditions. Perform data analysis and statistical processing on the calculated phase drift to evaluate its changing trend and impact in different situations. Perform experimental verification or simulation to verify the effectiveness and accuracy of the deduced comprehensive signal model.

[0095] Step S3: performing actual signal disturbance analysis on the standard satellite reception signal through the indirect path reception signal phase drift to generate actual signal disturbance data; performing average disturbance amplitude calculation on the actual signal disturbance data to obtain actual signal average disturbance amplitude data; performing multi-level signal interference elimination on the actual signal disturbance data based on the actual signal average disturbance amplitude data using the Beidou navigation satellite positioning data gross error elimination algorithm, thereby generating a satellite reception disturbance optimization signal;

[0096] In an embodiment of the present invention, actual signal disturbance analysis is performed on the standard satellite received signal by using the indirect path received signal phase drift data calculated in step S2. The signal phase change and interference effect caused by the indirect path are analyzed to evaluate its impact on the quality of the satellite received signal. In an actual environment or in a simulation experiment, the actual disturbance data of the standard satellite received signal under different conditions are obtained. The phase change and interference of the satellite signal received each time are recorded to form an actual signal disturbance data set. The actual signal disturbance data is statistically analyzed to calculate the average disturbance amplitude in multiple samples. Mathematical statistical methods such as mean and standard deviation are used to evaluate the stability and consistency of the actual signal disturbance. According to the actual signal average disturbance amplitude data, a specific Beidou navigation satellite positioning data gross error elimination algorithm is designed. The elimination algorithm is used to perform multi-level interference elimination and correction on the signal data received by the satellite to improve the signal quality and positioning accuracy. According to the data after eliminating interference, an optimized version of the satellite received signal, that is, the satellite received disturbance optimization signal, is generated. Ensure that the optimized signal has stable performance and accurate data transmission capability under different environmental conditions.

[0097] Step S4: Perform signal environment simulation based on the satellite reception disturbance optimization signal to obtain signal environment simulation data; perform signal elimination optimization performance evaluation on the environmental simulation data through the Beidou navigation satellite positioning data gross error elimination algorithm to generate optimization performance evaluation data; perform signal gross error elimination environment adaptability analysis on the satellite reception disturbance optimization signal through the optimization performance evaluation data to generate data gross error elimination algorithm adaptability data.

[0098] In an embodiment of the present invention, a signal environment simulation is performed by using the satellite reception disturbance optimization signal generated in step S3. Different signal reception conditions and environmental conditions are simulated, including different interference sources and signal transmission paths. In the simulation environment, various characteristics and parameters of the simulation signal, such as signal strength, phase change, noise level, etc., are recorded. The comprehensiveness and accuracy of data acquisition are ensured to support subsequent signal optimization performance evaluation and adaptability analysis. According to the Beidou navigation satellite positioning data gross error elimination algorithm designed in step S3, the signal data in the simulation environment is processed and optimized. The effect and performance of the elimination algorithm under different signal environments are evaluated, including elimination accuracy, elimination time and adaptability. The processed data is analyzed to generate signal elimination optimization performance evaluation data. The elimination effect and optimization results under each environmental condition are recorded to form a detailed evaluation report and data statistics. Based on the optimization performance evaluation data, the gross error elimination adaptability of the satellite reception disturbance optimization signal under different environments is analyzed. The application capabilities and limitations of the elimination algorithm in a complex signal environment are explored, including the response capability to specific interference types and intensities. According to the analysis results, data gross error elimination algorithm adaptability data is generated. Conclusions and recommendations on the applicability of the algorithm are provided to guide future signal processing and optimization strategies.

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

[0100] Step S11: Acquire satellite reception signals through a Beidou navigation satellite positioning receiver;

[0101] Step S12: converting the satellite received signal into a digital signal to obtain a satellite received digital signal;

[0102] Step S13: demodulating the satellite received digital signal to generate a satellite demodulated signal;

[0103] Step S14: Perform signal gain on the satellite demodulated signal to obtain a standard satellite reception signal.

[0104] In an embodiment of the present invention, a dedicated Beidou navigation satellite positioning receiver device is used, such as a professional receiver or antenna system. Signal reception is performed at a suitable location and time period to ensure that a valid signal from a Beidou navigation satellite is received. The received analog signal is converted into a digital signal. Digital signal processing technology, such as an analog-to-digital converter (ADC), is used to convert the analog signal into a digital format for subsequent digital signal processing. The acquired digital signal is demodulated to extract useful information. The demodulation process includes converting a complex received signal into a baseband signal or an intermediate frequency signal, and removing unnecessary frequency components or modulation. The acquired digital signal is demodulated to extract useful information. The demodulation process includes converting a complex received signal into a baseband signal or an intermediate frequency signal, and removing unnecessary frequency components or modulation.

[0105] As an example of the present invention, refer to Figure 2 As shown, in this example, step S2 includes:

[0106] Step S21: performing reception timing analysis on the standard satellite reception signal to obtain satellite signal reception timing data;

[0107] Step S22: performing indirect path interference analysis on the standard satellite reception signal through the satellite signal reception timing data to obtain a direct path reception signal and an indirect path reception signal;

[0108] Step S23: constructing a deduced integrated signal model; using the deduced integrated signal model to perform GNSS integrated signal deduction on the direct path received signal and the indirect path received signal, thereby generating a satellite integrated deduced signal;

[0109] Step S24: performing signal phase disturbance analysis on the indirect path receiving signal according to the satellite comprehensive deduction signal to generate a phase drift amount of the indirect path receiving signal.

[0110] In an embodiment of the present invention, real-time or historical satellite signal data is obtained by using a pre-configured Beidou navigation satellite positioning receiver device. A timing analysis is performed on the acquired satellite reception signal. The analysis process includes evaluation and statistics of the time series characteristics, volatility, stability, etc. of the signal. An indirect path interference analysis is performed based on the received satellite signal data. This includes analyzing the relationship and difference between the direct path reception signal and the indirect path reception signal. Based on the analyzed characteristics of the direct path reception signal and the indirect path reception signal, a comprehensive signal model is constructed. The model can cover key features such as the frequency, phase, and amplitude of the signal. Using the established comprehensive signal model, the direct path reception signal and the indirect path reception signal are comprehensively analyzed and deduced. The purpose is to generate a more accurate and comprehensive satellite comprehensive deduction signal. Phase analysis is performed on the generated satellite comprehensive deduction signal. During the analysis process, attention is paid to the change and drift of the signal phase, especially the phase drift of the indirect path reception signal.

[0111] Preferably, step S22 includes the following steps:

[0112] Step S221: performing time sequence signal segmentation on the standard satellite reception signal according to the satellite signal reception time sequence data to obtain time sequence segmentation signal segments;

[0113] Step S222: performing Hilbert transform on the time series segmentation signal segment to obtain the time series segmentation signal envelope; performing change trend analysis on the time series segmentation signal envelope to generate time series segmentation signal strength data;

[0114] Step S223: performing instantaneous signal phase calculation on the time-series segmentation signal envelope to obtain instantaneous signal phase data; performing phase difference analysis of adjacent signal segments on the time-series segmentation signal segments using the instantaneous signal phase data to generate instantaneous phases of adjacent signal segments;

[0115] Step S224: performing indirect path interference analysis on the time-series segmented signal segments based on the time-series segmented signal strength data and the instantaneous phases of adjacent signal segments to obtain direct path received signals and indirect path received signals;

[0116] The calculation formula for indirect path interference analysis is as follows:

[0117]

[0118]

[0119] In the formula, Represents the direct path receiving signal, Indicates that the signal is received by the indirect path, Expressed as the amplitude of the direct path signal, Expressed as the phase of the direct path signal, Expressed as the signal reflection coefficient, Expressed as the amplitude of the indirect path signal, Represents the phase delay caused by the indirect path signal.

[0120] In an embodiment of the present invention, the standard satellite reception signal is segmented by using the acquired satellite signal reception timing data to obtain the timing segmentation signal segment. The timing segmentation signal segment is subjected to Hilbert transform to obtain the timing segmentation signal envelope. The Hilbert transform can extract the envelope of the signal, that is, the change of the amplitude of the signal over time. The timing segmentation signal envelope is subjected to change trend analysis to generate the timing segmentation signal strength data. Analysis of the change trend of the envelope can reflect the change characteristics of the signal strength. The instantaneous signal phase is calculated for the timing segmentation signal envelope to obtain the instantaneous signal phase data. The instantaneous signal phase reflects the phase information of the signal at a certain moment. The phase difference analysis of adjacent timing segmentation signal segments is performed using the instantaneous signal phase data. The instantaneous phase difference between adjacent signal segments is calculated, which can be used to analyze the phase delay caused by the indirect path. Indirect path interference analysis is performed according to a given calculation formula. The calculation formula is used to perform indirect path interference analysis on the timing segmentation signal segment to obtain the relevant data of the direct path reception signal and the indirect path reception signal. Ensure that the phase change and amplitude change of the signal, as well as the comprehensive analysis of influencing factors such as the reflection coefficient are taken into account during the calculation process.

[0121] Preferably, step S23 includes the following steps:

[0122] Step S231: using an environmental sensor to collect environmental information of a Beidou navigation satellite positioning receiver to obtain receiver environmental information data;

[0123] Step S232: performing three-dimensional environment modeling on the receiver environment information data to obtain three-dimensional receiver environment data; performing signal ray tracing on the direct path received signal and the indirect path received signal through the three-dimensional receiver environment data to generate signal propagation simulation data, wherein the signal propagation simulation data includes propagation path simulation data and signal reflection simulation data;

[0124] Step S233: training a comprehensive signal model based on the propagation path simulation data and the signal reflection simulation data, thereby generating a deduced comprehensive signal model; importing the direct path received signal and the indirect path received signal into the deduced comprehensive signal model for signal superposition, thereby generating a satellite comprehensive deduced signal;

[0125] The signal superposition processing formula for the deduced comprehensive signal model is as follows:

[0126]

[0127] In the formula, It is represented by the satellite integrated deduction signal. Represents the direct path receiving signal, Indicates that the signal is received by the indirect path, Expressed as the signal reflection coefficient, It is represented as the phase delay caused by the indirect path signal;

[0128] The generalized formula of satellite integrated deduction signal is as follows:

[0129]

[0130] In the formula, Represented as the deduced comprehensive signal model, It is represented by the phase delay caused by the indirect path signal, Expressed as signal reflection coefficient.

[0131] In an embodiment of the present invention, environmental information around the receiver is obtained by using an environmental sensor, including temperature, humidity, atmospheric pressure and other data. Receiver environmental information data is obtained for subsequent signal propagation simulation and modeling. The environmental information around the receiver is three-dimensionally modeled to generate three-dimensional environmental data of the receiver. Ensure that the modeling includes the position, shape, reflection characteristics, etc. of surrounding objects. Use the three-dimensional environmental data of the receiver to perform signal ray tracing. Track the direct path received signal and the indirect path received signal to obtain signal propagation simulation data. Including propagation path simulation data and signal reflection simulation data, these data will be used for subsequent comprehensive signal model training. Based on the propagation path simulation data and signal reflection simulation data, the comprehensive signal model is trained. Ensure that the model can accurately reflect the characteristics of the direct path received signal and the indirect path received signal and their interactions. The direct path received signal and indirect path receiving signal Import the deduced integrated signal model to perform signal superposition. Calculate according to the given signal superposition processing formula to generate the satellite integrated deduced signal .

[0132] Preferably, step S24 includes the following steps:

[0133] Step S241: Acquire satellite orbit position data;

[0134] Step S242: extracting nearby hydrological features from the receiver environment information data to obtain receiver environment hydrological feature data, wherein the receiver environment hydrological feature data includes nearby water surface height data and nearby water surface position data;

[0135] Step S243: performing a receiving antenna position analysis on the Beidou navigation satellite positioning receiver to generate receiver receiving antenna position information data; performing a spatial periodic change analysis on the satellite orbit position data, the adjacent water surface height data and the adjacent water surface position data, and the receiver receiving antenna position information data to generate signal reception spatial change data;

[0136] Step S244: performing phase delay variation analysis on the satellite integrated deduction signal based on the signal reception spatial variation data to generate indirect signal phase delay variation data, and importing the indirect signal phase delay variation data into the deduction integrated signal model to perform phase drift deduction, thereby generating the indirect path reception signal phase drift;

[0137] The deduction formula for phase drift is as follows:

[0138]

[0139] In the formula, It is expressed as the phase drift of the indirect path received signal, Represented as indirect signal phase delay change data, Expressed as the length of the signal receiving space variation, Represented as the output value of the deduced comprehensive signal model, It is represented by the phase delay caused by the indirect path signal, Expressed as signal reflection coefficient.

[0140] In an embodiment of the present invention, the real-time orbital position data of the satellite is obtained from the Beidou navigation satellite system or other related satellite systems. The data should include key information such as the satellite's position coordinates (longitude, latitude, altitude) and speed. Use environmental sensors or ground measurement tools to obtain hydrological characteristic data around the receiver. The extracted characteristic data includes height data and geographic location data (such as longitude and latitude) near the water surface. The receiving antenna position of the Beidou navigation satellite positioning receiver is analyzed and measured in detail. Determine the exact position and orientation of the receiving antenna, which has an important impact on the spatial angle and path of signal reception. Combine the satellite orbital position data, nearby hydrological characteristic data and receiving antenna position information to analyze the spatial periodic changes in the signal reception process. This includes the influence of factors such as terrain and water surface height on the signal in the propagation path, and how these factors lead to changes in the signal propagation path and changes in signal reception. Use spatial periodic change data to analyze the phase delay change of the satellite received signal. According to the satellite comprehensive deduction signal model, calculate the phase delay change of the indirect path received signal The calculated indirect signal phase delay changes Import into the deduced integrated signal model to calculate the phase drift 's deduction.

[0141] Preferably, step S3 comprises the following steps:

[0142] Step S31: performing actual signal disturbance analysis on the standard satellite reception signal through the phase drift of the indirect path reception signal to generate actual signal disturbance data;

[0143] Step S32: performing fast Fourier transform on the actual signal disturbance data to obtain an actual signal disturbance spectrum diagram; performing average disturbance amplitude calculation on the actual signal disturbance spectrum diagram to obtain actual signal average disturbance amplitude data;

[0144] Step S33: comparing the actual signal average disturbance amplitude data with the preset disturbance amplitude threshold. When the actual signal average disturbance amplitude data is greater than or equal to the preset disturbance amplitude threshold, the actual signal disturbance data is subjected to high-precision indirect signal interference elimination by using the Beidou navigation satellite positioning data gross error elimination algorithm, thereby generating a satellite reception disturbance optimization signal.

[0145] Step S34: When the actual signal average disturbance amplitude data is less than the preset disturbance amplitude threshold, conventional signal denoising is performed on the actual signal disturbance data to generate a satellite reception disturbance optimization signal.

[0146] In an embodiment of the present invention, the actual signal disturbance analysis is performed on the standard satellite receiving signal by using the phase drift data of the indirect path receiving signal obtained in step S31. According to the phase drift data, the actual signal disturbance data is generated, that is, the actual disturbance of the satellite receiving signal in a complex environment. The actual signal disturbance data generated in step S31 is subjected to a fast Fourier transform (FFT) to obtain a spectrum diagram of the actual signal disturbance. The fast Fourier transform converts the signal from the time domain to the frequency domain, and can clearly show the disturbance of the signal at different frequencies. Based on the actual signal disturbance spectrum diagram, its average disturbance amplitude data is calculated. This step evaluates the overall disturbance degree of the signal in the frequency domain. The average disturbance amplitude data of the actual signal is compared with the preset disturbance amplitude threshold. If the average disturbance amplitude of the actual signal is greater than or equal to the preset threshold, step S33 is executed; if it is less than the preset threshold, step S34 is executed. When the average disturbance amplitude data of the actual signal is greater than or equal to the preset disturbance amplitude threshold, the Beidou navigation satellite positioning data gross error elimination algorithm is used. The algorithm eliminates high-precision indirect signal interference in the actual signal disturbance data to generate a satellite reception disturbance optimization signal. When the average disturbance amplitude data of the actual signal is less than the preset disturbance amplitude threshold, a conventional signal denoising operation is performed. Conventional signal denoising technology can include filtering, noise reduction algorithms, etc. to reduce noise and interference in the signal, and also generate a satellite reception disturbance optimization signal.

[0147] Preferably, the Beidou navigation satellite positioning data gross error elimination algorithm in step S33 is as follows:

[0148]

[0149] In the formula, Expressed as Input signal, Expressed as output signal, Expressed as the gross error extraction coefficient, Expressed as the input signal order, Expressed as An optimization signal, Expressed as the unit weight of the indirect path low-frequency signal, Expressed as the correlation coefficient between the optimization signal and the input signal, Expressed as the autocorrelation coefficient of the input signal, Expressed as the optimized signal order, Expressed as the maximum order of the input signal, Represented as a time series of indirect signals.

[0150] The present invention analyzes and integrates a Beidou navigation satellite positioning data gross error elimination algorithm. The input signal in the algorithm represents is the original positioning signal sequence received from the Beidou navigation satellite, i.e. Input signal. Output signal The signal after optimization processing, i.e. By optimizing the input signal Obtained. Gross error extraction coefficient Represents the extraction coefficient of gross error, which is used to quantify the degree of gross error in the optimized signal. To eliminate gross errors. Input signal order Specifies the order of the input signal, which affects the complexity and effect of the optimization process. Represents the optimized signal, which is used to replace the original input signal , to reduce the gross error in the signal. The unit weight of the low-frequency signal in the indirect path It is used to weigh the influence of the low-frequency signal of the indirect path on the gross error and is a key parameter in the optimization process. The correlation coefficient between the optimization signal and the input signal Measured optimization signals With the original input signal The correlation between the input signals helps optimize the signal processing. Measured the original input signal The autocorrelation property of plays an important role in eliminating gross errors and optimizing signals. Optimizing signal order Optimization signal specified The order of the input signal affects the complexity and accuracy of the optimized signal processing. Defines the maximum order of the input signal, affecting the computational complexity of the overall algorithm and the depth of signal processing. Time series of indirect signals The time series representing the indirect signal has an impact on the time characteristics of signal processing during the optimization process. By optimizing the generation of the signal and minimizing the gross error extraction coefficient, the accuracy and stability in the Beidou navigation satellite positioning data can be effectively improved. By considering the autocorrelation of the input signal and the correlation of the optimized signal, the gross error can be extracted more accurately to avoid the influence of the abnormal points in the signal on the navigation positioning. The complex interaction between the parameters can improve the calculation efficiency and real-time performance of the algorithm while ensuring the effectiveness of the algorithm, and adapt to the complex and dynamic signal environment of the Beidou navigation system. When using the Beidou navigation satellite positioning data gross error elimination algorithm conventional in the art, the satellite reception disturbance optimization signal can be obtained. By applying the Beidou navigation satellite positioning data gross error elimination algorithm provided by the present invention, the satellite reception disturbance optimization signal can be more accurately calculated. Through the joint action of the factors in the algorithm, the above formula can effectively deal with the gross error problem in the Beidou navigation satellite positioning data, and improve positioning accuracy and reliability.

[0151] Preferably, step S4 comprises the following steps:

[0152] Step S41: performing signal environment simulation based on the satellite reception disturbance optimization signal to obtain signal environment simulation data;

[0153] Step S42: performing multi-directional reception settings on the environmental simulation data to obtain environmental simulation multi-directional reception data, wherein the multi-directional reception settings include near water direction, far water direction and sky direction reception;

[0154] Step S43: performing signal accuracy change analysis on the environment simulation multi-directional receiving data according to the signal environment simulation data, and generating a near-water receiving signal accuracy change graph, a far-water receiving signal accuracy change graph, and an antenna receiving signal accuracy change graph;

[0155] Step S44: using the Beidou navigation satellite positioning data gross error elimination algorithm to perform signal elimination optimization performance evaluation on the near-water receiving signal accuracy change diagram, the far-water receiving signal accuracy change diagram and the celestial receiving signal accuracy change diagram, and generate optimization performance evaluation data;

[0156] Step S45: Performing adaptability analysis of the signal gross error elimination environment on the satellite reception disturbance optimization signal by optimizing the performance evaluation data, and generating data gross error elimination algorithm adaptability data.

[0157] In an embodiment of the present invention, a signal environment simulation is performed by using the satellite reception disturbance optimization signal generated in step S41. According to the actual situation and preset conditions, signal data in the simulated environment is generated, including characteristics such as signal strength and phase. The generated signal environment simulation data is set for multi-directional reception, including but not limited to: near water direction reception; far water direction reception; sky direction reception. Based on the multi-directional reception data in step S42, the accuracy change analysis is performed on the signal in each receiving direction. Data such as the near water receiving signal accuracy change diagram, the far water receiving signal accuracy change diagram and the sky receiving signal accuracy change diagram are generated. Using the Beidou navigation satellite positioning data gross error elimination algorithm, the signal accuracy change diagram generated in step S43 is optimized for performance evaluation. The effect of the elimination algorithm under different receiving directions and environmental conditions is evaluated, and optimization performance evaluation data is generated. Based on the optimization performance evaluation data of step S44, the satellite reception disturbance optimization signal is subjected to a signal gross error elimination environmental adaptability analysis. The adaptability of the elimination algorithm under different environments and receiving conditions is analyzed, and data gross error elimination algorithm adaptability data is generated.

[0158] Preferably, performing signal environment simulation based on satellite reception disturbance optimization signal includes:

[0159] Confirm the location of the observation site based on the satellite receiving disturbance optimization signal to obtain the location information data of the observation site;

[0160] The signal environment is constructed according to the location information data of the observation site to obtain the initial signal collection environment;

[0161] The observation site location information data is subjected to a large-area water area proximity simulation to obtain the observation site-water area path data; the observation site location information data is subjected to an environmental occlusion analysis to generate the observation site environmental occlusion analysis data;

[0162] The signal collection refraction environment impact modeling is performed on the initial signal collection environment through the observation site-water path data and the observation site environmental occlusion analysis data to obtain the signal environment simulation data.

[0163] In an embodiment of the present invention, the location information data of the observation site is determined by optimizing the signal based on the disturbance received by the satellite. The specific geographical location of each observation site is confirmed, including information such as longitude and latitude. According to the confirmed location information data of the observation site, an initial signal acquisition environment is established. The environmental features such as terrain and buildings around the observation site are determined as the basis for the initial signal acquisition environment. The proximity distance of a large area of ​​water is simulated for the location information data of the observation site. The distance data between each observation site and the adjacent water area is determined, including the type and area of ​​the water area. The environmental shielding around the location of the observation site is analyzed. Including the influence of buildings, trees and other objects on signal reception, the environmental shielding analysis data of the observation site is generated. The initial signal acquisition environment is modeled by combining the observation site-water path data and the environmental shielding analysis data. A propagation model of the signal in the environment around the observation site is established, taking into account the influence of water reflection, refraction and shielding on signal propagation. According to the above modeling results, the final signal environment simulation data is generated. The data includes changes in signal strength, phase and other conditions around the observation site, as well as detailed information such as reflection and refraction of the signal under environmental conditions.

[0164] The beneficial effect of the present invention is that by preprocessing the satellite reception signal, the signal data can be cleaned and standardized, and a standard satellite reception signal can be generated, providing an accurate data basis for subsequent analysis. By performing indirect path interference analysis on the standard satellite reception signal, a direct path reception signal and an indirect path reception signal can be obtained, and a signal phase disturbance analysis is performed on it using a deduced comprehensive signal model to generate an indirect path reception signal phase drift amount, which helps to understand the interference and phase disturbance in signal transmission. The actual signal disturbance analysis of the standard satellite reception signal is performed through the indirect path reception signal phase drift amount, the actual signal disturbance data is generated, and the average disturbance amplitude is calculated to evaluate the degree of disturbance of the signal. The Beidou navigation satellite positioning data gross error elimination algorithm is used to perform multi-level signal interference elimination on the actual signal disturbance data based on the actual signal average disturbance amplitude data, thereby generating a satellite reception disturbance optimization signal, reducing signal interference and disturbance, and improving signal quality and accuracy. Based on the satellite receiving disturbance optimization signal, the signal environment simulation is performed to obtain the signal environment simulation data, and the Beidou navigation satellite positioning data gross error elimination algorithm is used to evaluate the signal elimination optimization performance of the simulation data, and the optimization performance evaluation data is generated to evaluate the optimization effect and performance of the signal. The satellite receiving disturbance optimization signal is subjected to the signal gross error elimination environment adaptability analysis through the optimization performance evaluation data, and the data gross error elimination algorithm adaptability data is generated to help evaluate the adaptability and effect of the data processing algorithm in different signal environments. Therefore, the present invention uses the signal processing repair algorithm to intelligently identify the reflected signal generated by a large area of ​​water, and automatically eliminates the gross error generated by it, thereby ensuring the correctness and stability of the measurement results.

[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. An algorithm for eliminating gross errors in Beidou navigation satellite positioning data near vast waters, characterized in that: The following steps are involved: Step S1: Acquire satellite reception signals; Perform signal preprocessing on satellite reception signals to generate standard satellite reception signals; Step S2: performing indirect path interference analysis on the standard satellite reception signal to obtain a direct path reception signal and an indirect path reception signal; The signal phase disturbance analysis of the direct path receiving signal and the indirect path receiving signal is performed by using the deduced integrated signal model to generate the phase drift of the indirect path receiving signal; Step S3: performing actual signal disturbance analysis on the standard satellite reception signal through the phase drift of the indirect path reception signal to generate actual signal disturbance data; The average disturbance amplitude of the actual signal disturbance data is calculated to obtain the actual signal average disturbance amplitude data; the Beidou navigation satellite positioning data gross error elimination algorithm is used to perform multi-level signal interference elimination on the actual signal disturbance data based on the actual signal average disturbance amplitude data, thereby generating a satellite reception disturbance optimization signal; Step S4: Perform signal environment simulation based on the satellite reception disturbance optimization signal to obtain signal environment simulation data; perform signal elimination optimization performance evaluation on the environmental simulation data through the Beidou navigation satellite positioning data gross error elimination algorithm to generate optimization performance evaluation data; perform signal gross error elimination environment adaptability analysis on the satellite reception disturbance optimization signal through the optimization performance evaluation data to generate data gross error elimination algorithm adaptability data.

2. The algorithm for eliminating gross errors of Beidou navigation satellite positioning data near vast waters according to claim 1 is characterized in that: Step S1 includes the following steps: Step S11: Acquire satellite reception signals through a Beidou navigation satellite positioning receiver; Step S12: converting the satellite received signal into a digital signal to obtain a satellite received digital signal; Step S13: demodulating the satellite received digital signal to generate a satellite demodulated signal; Step S14: Perform signal gain on the satellite demodulated signal to obtain a standard satellite reception signal.

3. The algorithm for eliminating gross errors of Beidou navigation satellite positioning data near vast waters according to claim 1 is characterized in that: Step S2 includes the following steps: Step S21: performing reception timing analysis on the standard satellite reception signal to obtain satellite signal reception timing data; Step S22: performing indirect path interference analysis on the standard satellite reception signal through the satellite signal reception timing data to obtain a direct path reception signal and an indirect path reception signal; Step S23: constructing a deduced integrated signal model; using the deduced integrated signal model to perform GNSS integrated signal deduction on the direct path received signal and the indirect path received signal, thereby generating a satellite integrated deduced signal; Step S24: performing signal phase disturbance analysis on the indirect path receiving signal according to the satellite comprehensive deduction signal to generate a phase drift amount of the indirect path receiving signal.

4. The algorithm for eliminating gross errors of Beidou navigation satellite positioning data near vast waters according to claim 3 is characterized in that: Step S22 includes the following steps: Step S221: performing time sequence signal segmentation on the standard satellite reception signal according to the satellite signal reception time sequence data to obtain time sequence segmentation signal segments; Step S222: performing Hilbert transform on the time series segmentation signal segment to obtain the time series segmentation signal envelope; performing change trend analysis on the time series segmentation signal envelope to generate time series segmentation signal strength data; Step S223: performing instantaneous signal phase calculation on the time-series segmentation signal envelope to obtain instantaneous signal phase data; performing phase difference analysis of adjacent signal segments on the time-series segmentation signal segments using the instantaneous signal phase data to generate instantaneous phases of adjacent signal segments; Step S224: performing indirect path interference analysis on the time-series segmented signal segments based on the time-series segmented signal strength data and the instantaneous phases of adjacent signal segments to obtain direct path received signals and indirect path received signals; The calculation formula for indirect path interference analysis is as follows: In the formula, Represents the direct path receiving signal, Indicates that the signal is received by the indirect path, Expressed as the amplitude of the direct path signal, Expressed as the phase of the direct path signal, Expressed as the signal reflection coefficient, Expressed as the amplitude of the indirect path signal, Represents the phase delay caused by the indirect path signal.

5. The algorithm for eliminating gross errors of Beidou navigation satellite positioning data near vast waters according to claim 3 is characterized in that: Step S23 includes the following steps: Step S231: using an environmental sensor to collect environmental information of a Beidou navigation satellite positioning receiver to obtain receiver environmental information data; Step S232: performing three-dimensional environment modeling on the receiver environment information data to obtain three-dimensional receiver environment data; performing signal ray tracing on the direct path received signal and the indirect path received signal through the three-dimensional receiver environment data to generate signal propagation simulation data, wherein the signal propagation simulation data includes propagation path simulation data and signal reflection simulation data; Step S233: training a comprehensive signal model based on the propagation path simulation data and the signal reflection simulation data, thereby generating a deduced comprehensive signal model; importing the direct path received signal and the indirect path received signal into the deduced comprehensive signal model for signal superposition, thereby generating a satellite comprehensive deduced signal; The signal superposition processing formula for the deduced comprehensive signal model is as follows: In the formula, It is represented by the satellite integrated deduction signal. Represents the direct path receiving signal, Indicates that the signal is received by the indirect path, Expressed as the signal reflection coefficient, It is represented as the phase delay caused by the indirect path signal; The generalized formula of satellite integrated deduction signal is as follows: In the formula, Represented as the deduced comprehensive signal model, It is represented by the phase delay caused by the indirect path signal, Expressed as signal reflection coefficient.

6. The algorithm for eliminating gross errors of Beidou navigation satellite positioning data near vast waters according to claim 3 is characterized in that: Step S24 includes the following steps: Step S241: Acquire satellite orbit position data; Step S242: extracting nearby hydrological features from the receiver environment information data to obtain receiver environment hydrological feature data, wherein the receiver environment hydrological feature data includes nearby water surface height data and nearby water surface position data; Step S243: performing a receiving antenna position analysis on the Beidou navigation satellite positioning receiver to generate receiver receiving antenna position information data; performing a spatial periodic change analysis on the satellite orbit position data, the adjacent water surface height data and the adjacent water surface position data, and the receiver receiving antenna position information data to generate signal reception spatial change data; Step S244: performing phase delay variation analysis on the satellite integrated deduction signal based on the signal reception spatial variation data to generate indirect signal phase delay variation data, and importing the indirect signal phase delay variation data into the deduction integrated signal model to perform phase drift deduction, thereby generating the indirect path reception signal phase drift; The deduction formula for phase drift is as follows: In the formula, It is expressed as the phase drift of the indirect path received signal, Represented as indirect signal phase delay change data, Expressed as the length of the signal receiving space variation, Represented as the output value of the deduced comprehensive signal model, It is represented by the phase delay caused by the indirect path signal, Expressed as signal reflection coefficient.

7. The algorithm for eliminating gross errors of Beidou navigation satellite positioning data near vast waters according to claim 1 is characterized in that: Step S3 includes the following steps: Step S31: performing actual signal disturbance analysis on the standard satellite reception signal through the phase drift of the indirect path reception signal to generate actual signal disturbance data; Step S32: performing fast Fourier transform on the actual signal disturbance data to obtain an actual signal disturbance spectrum diagram; performing average disturbance amplitude calculation on the actual signal disturbance spectrum diagram to obtain actual signal average disturbance amplitude data; Step S33: comparing the actual signal average disturbance amplitude data with the preset disturbance amplitude threshold. When the actual signal average disturbance amplitude data is greater than or equal to the preset disturbance amplitude threshold, the actual signal disturbance data is subjected to high-precision indirect signal interference elimination by using the Beidou navigation satellite positioning data gross error elimination algorithm, thereby generating a satellite reception disturbance optimization signal. Step S34: When the actual signal average disturbance amplitude data is less than the preset disturbance amplitude threshold, conventional signal denoising is performed on the actual signal disturbance data to generate a satellite reception disturbance optimization signal.

8. The algorithm for eliminating gross errors of Beidou navigation satellite positioning data near vast waters according to claim 7 is characterized in that: The Beidou navigation satellite positioning data gross error elimination algorithm in step S33 is as follows: In the formula, Expressed as Input signal, Expressed as output signal, Expressed as the gross error extraction coefficient, Expressed as the input signal order, Expressed as An optimization signal, Expressed as the unit weight of the indirect path low-frequency signal, Expressed as the correlation coefficient between the optimization signal and the input signal, Expressed as the autocorrelation coefficient of the input signal, Expressed as the optimized signal order, Expressed as the maximum order of the input signal, Represented as a time series of indirect signals.

9. The Beidou navigation satellite positioning data gross error elimination algorithm according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: performing signal environment simulation based on the satellite reception disturbance optimization signal to obtain signal environment simulation data; Step S42: performing multi-directional reception settings on the environmental simulation data to obtain environmental simulation multi-directional reception data, wherein the multi-directional reception settings include near water direction, far water direction and sky direction reception; Step S43: performing signal accuracy change analysis on the environment simulation multi-directional receiving data according to the signal environment simulation data, and generating a near-water receiving signal accuracy change graph, a far-water receiving signal accuracy change graph, and an antenna receiving signal accuracy change graph; Step S44: using the Beidou navigation satellite positioning data gross error elimination algorithm to perform signal elimination optimization performance evaluation on the near-water receiving signal accuracy change diagram, the far-water receiving signal accuracy change diagram and the celestial receiving signal accuracy change diagram, and generate optimization performance evaluation data; Step S45: Performing adaptability analysis of the signal gross error elimination environment on the satellite reception disturbance optimization signal by optimizing the performance evaluation data, and generating data gross error elimination algorithm adaptability data.

10. The Beidou navigation satellite positioning data gross error elimination algorithm according to claim 9, characterized in that: Signal environment simulation based on satellite reception disturbance optimization signal includes: Confirm the location of the observation site based on the satellite receiving disturbance optimization signal to obtain the location information data of the observation site; The signal environment is constructed according to the location information data of the observation site to obtain the initial signal collection environment; The observation site location information data is subjected to a large-area water area proximity simulation to obtain the observation site-water area path data; the observation site location information data is subjected to an environmental occlusion analysis to generate the observation site environmental occlusion analysis data; The signal collection refraction environment impact modeling is performed on the initial signal collection environment through the observation site-water path data and the observation site environmental occlusion analysis data to obtain the signal environment simulation data.

Images