Big dipper-based enhanced data processing method and system

Abstract

The invention discloses a Beidou satellite-based enhanced data processing method and system, and solves the problems of poor data fusion effect and poor positioning precision caused by large satellite selection error in the prior art. The method comprises the following steps: receiving multiple frequency band signals of a Beidou satellite at the same time, analyzing and extracting signal parameters; selecting an optimal satellite for receiving according to satellite parameters, analyzing enhanced data of the selected satellite, performing fusion processing on data of multiple satellites, and allocating weights according to satellite signal quality; fusing data of different satellite information sources, and distributing weights for the information sources according to characteristics and precision requirements of the information sources; and positioning calculation is carried out according to the fused data, and whether a positioning calculation result is used for adjusting and optimizing a data fusion weight is judged according to a positioning error. The satellite selection function during multi-satellite data fusion is optimized, all factors of satellites are comprehensively considered, various error problems are effectively solved, and the positioning performance of a Beidou satellite navigation system is remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of satellite navigation technology, and in particular to a BeiDou satellite-based augmentation data processing method and system. Background Technology

[0002] Currently, although the BeiDou Navigation Satellite System is widely used, its positioning accuracy and reliability are still constrained by various factors. Ionospheric errors, satellite orbit errors, differential code bias (DCB), satellite clock errors, and tropospheric errors all affect positioning results. The BeiDou Satellite Based Augmentation System (BDSBAS) is a satellite-based augmentation system (SBAS) independently constructed according to international standards. Through distributed monitoring stations, it monitors the integrity of the Global Navigation Satellite System (GNSS) as it passes by.

[0003] During the enhanced positioning calculation process, BDSBAS users need to strictly screen observable satellites based on their service level and the maximum timeout limits of various information to ensure the accuracy and reliability of the positioning results and protection information. Otherwise, significant security risks will arise. For example, the Chinese Patent Office published a patent on April 30, 2021: CN112731471A, "A Method for Screening BeiDou Satellite-Based Enhanced Single-Frequency Positioning Satellites." This method utilizes GPS L1C / A frequency pseudorange and carrier observations, GPS L1C / A basic navigation messages, and BDSBAS B1 single-frequency enhanced messages received by the BDSBAS user receiver to screen available positioning satellites, meeting the user's needs for high-precision position calculation and high integrity assurance. However, the receiver system used in this method has shortcomings in multi-satellite data processing, failing to fully utilize the advantages of each satellite, and the satellite selection is not scientific and reasonable enough, resulting in poor data fusion effects and difficulty in effectively overcoming the aforementioned error problems, thus affecting positioning performance. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing BeiDou satellite-based augmentation systems in multi-satellite data processing, which fail to fully utilize the advantages of each satellite, have unscientific and unreasonable satellite selection, resulting in poor data fusion effects, errors, and low positioning accuracy. This invention provides a BeiDou satellite-based augmentation data processing method and system that optimizes various aspects of the receiver system, especially the satellite selection function during multi-satellite data fusion, comprehensively considers satellite parameters, effectively solves various error problems, and significantly improves the positioning performance of the BeiDou satellite navigation system.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: A method for processing BeiDou satellite-based augmentation data includes the following steps: S1: Simultaneously receive signals from multiple frequency bands of BeiDou satellites, and perform high-sensitivity analysis on the received multi-frequency signals to extract signal parameters; S2: Select the best satellite for reception based on satellite parameters, parse the enhanced data of the selected satellite, fuse the data of multiple satellites, and allocate weights according to the satellite signal quality; S3: Fusion of data from different satellite information sources, and allocation of weights to the information sources based on their characteristics and accuracy requirements; S4: Perform positioning calculations based on the fused data, evaluate the positioning results, and determine whether to use the positioning calculation results to optimize the data fusion weights based on the positioning error.

[0006] By optimizing all aspects of the receiver system, especially the satellite selection function during multi-satellite data fusion, and comprehensively considering factors such as satellite elevation angle, satellite data URA, data integrity, satellite health indicators, data coverage, and data validity period, various error problems are effectively solved, significantly improving the positioning performance of the BeiDou Navigation Satellite System. It can simultaneously receive signals from multiple frequency bands of BeiDou satellites, enhancing its ability to capture weak signals, ensuring signal reception stability in complex environments, and adapting to different types of multi-source data and complex application environments, demonstrating strong versatility and adaptability.

[0007] Preferably, step S1 includes: performing CRC check on the parsed data using a redundancy check code; if one or more bits in the data are found to be incorrect, then using different error correction code techniques to correct the error according to different satellite systems.

[0008] Preferably, in S3, during the data fusion of multiple satellite information sources, the weights of each information source are adjusted according to different application scenarios and environmental conditions: in areas and seasons with intense ionospheric activity, the weight of the BeiDou GEO satellite grid ionospheric information is increased; in scenarios requiring high-precision positioning, the weight of the BeiDou-3 augmentation information is increased.

[0009] Preferably, in step S2, initial screening conditions are set. If the number of satellites that meet the initial screening conditions is greater than the satellite number threshold, then the satellites are screened a second time based on the signal strength.

[0010] Preferably, the initial screening criteria are: selecting satellites with an elevation angle greater than a set first threshold, a URA less than a set second threshold, complete data and normal satellite health indicators, and data covering the current area and within the validity period.

[0011] Preferably, in step S1, matched filtering and coherent integration algorithms are used to analyze the multi-band satellite signals, analyze the phase and frequency characteristics of the multi-band satellite signals, and extract the satellite navigation messages and measurement data by combining the differences in the propagation characteristics of the multi-band satellite signals in the ionosphere.

[0012] As a preferred approach, the positioning results are evaluated for quality. If the positioning error does not exceed the set threshold, the weights of data fusion and the parameters of positioning solution are not adjusted. Otherwise, the weights of data fusion are adjusted using the parameters of positioning solution, and iterative optimization is performed until the positioning error is reduced to below the set threshold.

[0013] A BeiDou satellite-based augmentation data processing system includes: The BeiDou multi-frequency signal receiving module simultaneously receives signals from multiple frequency bands of BeiDou satellites. The data processing module is equipped with multiple channels. Each channel analyzes a frequency band signal and extracts signal parameters, including satellite ephemeris, almanac, clock bias, TGD, URA, health information, carrier phase, Doppler frequency offset, and other information, as well as ionospheric correction information, fast change correction, slow change correction, inter-symbol correction, clock bias correction, orbit correction, and other enhancement information. The satellite data fusion module selects satellites and analyzes the augmented data from the selected satellites to extract positioning information. The multi-source data fusion module integrates data from multiple satellite information sources and selects the data source based on the application scenario, application time, and location. The positioning and solving module performs positioning and solving based on the fused data and outputs the user's location information.

[0014] Preferably, each channel includes a correlator channel connected to the receiver's radio frequency front end. The correlator channel is connected to a data parsing module, which is connected to a data verification and error correction module. The data verification and error correction module is connected to both a satellite data fusion module and a positioning calculation module. The data parsing module parses the multi-frequency signals to extract observational information and satellite message information. The data verification and error correction module uses redundancy check codes and error correction codes to verify and correct the parsed data.

[0015] Preferably, the data fusion module includes: The satellite selection module detects satellite parameters in real time and selects satellites based on these parameters. If the number of selected satellites exceeds the satellite quantity threshold, a secondary selection is performed based on signal strength. The multi-satellite data fusion module analyzes the augmented data of selected satellites, uses the Kalman filter algorithm to fuse the multi-satellite data, and assigns weights to the selected satellites based on the satellite signal quality.

[0016] Therefore, the present invention has the following beneficial effects: 1. By scientifically selecting satellites and effectively fusing data, fully utilizing high-quality satellite data and combining multi-source information fusion, various error problems can be effectively solved, significantly improving the positioning accuracy of the BeiDou Navigation Satellite System and achieving high-precision single-point positioning at the decimeter or even centimeter level.

[0017] 2. Data verification and error correction mechanisms ensure data accuracy. Data fusion from multiple satellites and information sources enables the system to maintain good positioning performance even when some data sources fail, thus enhancing system reliability. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the overall steps of the BeiDou satellite-based augmentation data processing method in Example 1.

[0019] Figure 2 This is a structural block diagram of the BeiDou satellite-based augmentation data processing system in Example 2.

[0020] Figure 3 This is a data flow diagram of the data processing module in Example 2.

[0021] In the diagram: 1. Antenna; 2. Receiver RF front end; 3. Correlator channel; 4. Data parsing module; 5. Data verification and error correction module; 6. Satellite selection module; 7. Multi-satellite data fusion module; 8. Multi-source data fusion module; 9. Positioning calculation module; 10. Data processing module. Detailed Implementation

[0022] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments: Example 1: This embodiment provides a method for processing BeiDou satellite-based augmentation data, such as... Figure 1 As shown, the operation process is as follows: Step 1, simultaneously receive signals from multiple frequency bands of BeiDou satellites and perform high-sensitivity analysis on the received multi-frequency signals to extract signal parameters; Step 2, select the best satellite for reception based on the satellite parameters, analyze the enhanced data of the selected satellite, fuse the data from multiple satellites, and assign weights according to the satellite signal quality; Step 3, fuse the data from different satellite information sources and assign weights to the information sources according to their characteristics and accuracy; Step 4, perform positioning calculations based on the fused data, evaluate the positioning results, and determine whether to use the positioning calculation results to optimize the data fusion weights based on the positioning error.

[0023] The BeiDou satellite-based augmentation data processing method provided in this embodiment, through scientific satellite selection and effective data fusion, makes full use of high-quality satellite data and combines multi-information source fusion to effectively solve various error problems, significantly improve the positioning accuracy of the BeiDou satellite navigation system, and achieve high-precision single-point positioning at the decimeter or even centimeter level.

[0024] The following examples and specific application scenarios further illustrate the technical solution and effects of the present invention. The following examples are explanations of the present invention, but the present invention is not limited to the following examples.

[0025] Step 1: Simultaneously receive signals from multiple frequency bands of BeiDou satellites, and perform high-sensitivity analysis on the received multi-frequency signals to extract signal parameters.

[0026] By utilizing the multi-frequency reception capability of the BeiDou receiver, signals from multiple frequency bands of BeiDou satellites can be received simultaneously, enhancing the ability to capture weak signals and ensuring the stability of signal reception in complex environments.

[0027] Advanced signal processing algorithms are employed to perform high-sensitivity analysis of received multi-frequency signals. By combining the characteristics of multi-frequency signals, data containing key information such as satellite position, time, carrier phase, Doppler frequency offset, and enhancement information are accurately extracted, improving the accuracy and reliability of the analysis.

[0028] Specifically, the method involves using matched filtering and coherent integration algorithms to analyze multi-band satellite signals, identifying their phase and frequency characteristics, and extracting navigation messages and measurement data by considering the differences in propagation characteristics of multi-band satellite signals in the ionosphere.

[0029] Matched filtering utilizes a matched filter (a specially designed linear filter to maximize the correlation between the output signal and a specific known signal). By leveraging prior knowledge of the signal and optimizing the filter weights, it enhances the signal-to-noise ratio, thereby effectively extracting the signal from noise. By matching the signal to a known signal form, the detection capability of a specific signal can be improved.

[0030] When the signal and noise are uncorrelated, a matched filter can effectively suppress noise and improve signal quality. At the same time, a matched filter can maximize the signal-to-noise ratio at the output.

[0031] Coherent integration algorithms integrate received satellite signals, eliminating various signal variations and noise, extracting useful signal components, and ultimately obtaining accurate position or time information through precise numerical calculations and inversions. The length of the coherent integration time affects the signal-to-noise ratio, typically a maximum of 20ms, and it must be performed after bit synchronization; otherwise, data bit transitions will affect the integration effect.

[0032] Coherent integration algorithms can extract the true signal components from complex signal fluctuations, enabling accurate analysis of satellite signals. Coherent integration effectively improves the signal-to-noise ratio (SNR). For example, a 20ms coherent integration loop improves the SNR by approximately 12dB, a 40ms loop by approximately 15dB, and an 80ms loop by approximately 17dB, thereby enhancing receiver sensitivity. Redundancy check codes are used to verify the parsed data, detecting whether errors occurred during transmission and parsing. If one or more bits in the data are found to be incorrect, error-correcting codes are used to correct the errors, ensuring the data is accurate.

[0033] In this embodiment, a CRC code is used to verify the parsed data. CRC, or Cyclic Redundancy Check, is a channel coding technique that generates a short, fixed-length checksum based on data such as network data packets or computer files, using division and remainder principles for verification. If an error is detected, error correction codes are used to correct it, ensuring the accuracy of the extracted message information and measurement data. Different error correction codes are used depending on the satellite system. For example, the BeiDou GEO satellite system uses BCH codes, the PPP-B2B satellite system uses LDPC codes, and the BDS SBAS system uses Turbo codes.

[0034] The second step is to select the best satellite for reception based on the satellite parameters, analyze the enhanced data of the selected satellite, fuse the data from multiple satellites, and assign weights based on the satellite signal quality.

[0035] Real-time monitoring of satellite information includes elevation angle, satellite data URA, data integrity, satellite health indicators, data coverage, and data validity period. Initial screening criteria are set; if the number of satellites meeting these criteria exceeds a certain threshold, a secondary screening is performed based on signal strength.

[0036] In this embodiment, the initial screening criteria include: selecting the best satellite for reception based on factors such as satellite elevation angle, satellite data URA (User Ranging Accuracy), data integrity, satellite health indicators, data coverage, and data validity period. Priority is given to satellites with large elevation angles, small URA, complete data, good satellite health, suitable data coverage, and within their validity period.

[0037] Specifically, select satellites with an elevation angle greater than the set first threshold, URA less than the set second threshold, complete data and normal satellite health indicators, and data covering the current area and within the validity period.

[0038] In this embodiment, the first threshold is 15° and the second threshold is 1 meter.

[0039] The augmented data of the selected satellites is analyzed, and algorithms such as Kalman filtering are used to fuse the data from multiple satellites.

[0040] By utilizing the Kalman filtering algorithm, which fully considers receiver measurement errors and system model uncertainties, the impact of noise can be effectively reduced, improving the accuracy and stability of the fusion results.

[0041] Based on the signal quality (such as signal-to-noise ratio) and reliability of different satellites, appropriate weights are assigned to the data from each satellite to improve the accuracy of the fusion results. Satellites with good signal quality have higher weights, while satellites with poor signal quality have lower weights.

[0042] The third step is to fuse data from different satellite information sources and assign weights to the information sources based on their characteristics and accuracy.

[0043] In this embodiment, data from multiple information sources are fused, including satellite-based augmentation information from BeiDou GEO satellites, augmentation information from BeiDou SBAS, and augmentation information from BeiDou PPP-B2b. The augmentation information includes clock corrections, orbit corrections, inter-symbol offset corrections, grid ionospheric correction data, fast-change corrections, and slow-change corrections.

[0044] By combining data obtained from multi-frequency signal reception and analysis, the integrity and accuracy of the data are further improved. In the data fusion of multiple satellite information sources, the weight of each information source is adjusted according to different application scenarios and environmental conditions. For example, in areas and seasons with intense ionospheric activity, the weight of BeiDou GEO satellite grid ionospheric information is increased; in scenarios requiring high-precision positioning, the weight of BeiDou PPP-B2b enhanced information is increased.

[0045] Step 4: Perform positioning calculations based on the fused data, evaluate the positioning results, and determine whether to use the positioning calculation results to optimize the data fusion weights based on the positioning error.

[0046] The location is calculated based on the fused data, and the positioning equation is solved using the least squares method or other optimization algorithms to obtain the user's location information. By addressing various error issues, the accuracy and reliability of positioning are significantly improved, achieving high-precision single-point positioning at the decimeter or even centimeter level.

[0047] The least squares method can estimate a user's position, velocity, and time deviation (PVT solution) based on observation data acquired by the receiver (such as pseudorange and carrier phase). Its core lies in minimizing the sum of squared errors between the observed and predicted values, thereby obtaining the optimal state quantity estimate.

[0048] This embodiment also includes a quality assessment of the positioning results. If the positioning error does not exceed the set threshold, the weights of data fusion and the parameters of positioning solution are not adjusted. Otherwise, the weights of data fusion are adjusted using the parameters of positioning solution, and iterative optimization is performed until the positioning error is reduced to below the set threshold.

[0049] The BeiDou satellite-based augmentation data processing method provided in this embodiment optimizes various aspects of the receiver system, especially the satellite selection function during multi-satellite data fusion. It comprehensively considers factors such as satellite elevation angle, satellite data URA, data integrity, satellite health indicators, data coverage, and data validity period, effectively solving various error problems and significantly improving the positioning performance of the BeiDou satellite navigation system.

[0050] The BeiDou satellite-based augmentation data processing method provided in this embodiment has the following advantages: (1) Matched filtering and coherent integration algorithms are used to perform high-sensitivity analysis on the received multi-frequency signals and accurately extract the satellite navigation messages and measurement data.

[0051] (2) Redundancy check code and error correction code technology are used to check and correct the parsed data to ensure the accuracy of the extracted message information and measurement data.

[0052] (3) Data fusion from multiple satellites and data fusion from multiple information sources enable the system to maintain good positioning performance even when some data sources fail, thus enhancing the system's reliability.

[0053] (4) It can adapt to different types of multi-source data and complex application environments, and has strong versatility and adaptability.

[0054] Example 2: This embodiment provides a BeiDou satellite-based augmentation data processing system for implementing the BeiDou satellite-based augmentation data processing method in Embodiment 1.

[0055] Specifically, such as Figure 2 As shown, a BeiDou satellite-based augmentation data processing system includes: The BeiDou multi-frequency signal receiving module can simultaneously receive signals from multiple frequency bands of BeiDou satellites.

[0056] Data processing module 10, also known as the correlator channel module, analyzes and demodulates BeiDou / GNSS satellite signals, extracting observations such as pseudorange, carrier phase, Doppler, and CN0, as well as satellite message information. It has multiple channels, each analyzing a frequency band signal and extracting signal parameters.

[0057] The satellite data fusion module selects satellites and analyzes the augmented data of the selected satellites to extract positioning information.

[0058] The multi-source data fusion module 8 integrates data from multiple satellite information sources, selecting data sources based on the application scenario, application time, and location. It adjusts the weights of each information source according to different application scenarios and environmental conditions.

[0059] The positioning calculation module 9 performs positioning calculations based on the fused data and outputs the user's location information.

[0060] The BeiDou multi-frequency signal receiving module is connected to the data processing module. The data processing module is connected to the satellite data fusion module, the multi-source data fusion module, and the positioning calculation module. The satellite data fusion module and the multi-source data fusion module are both connected to the positioning calculation module. The output of the positioning calculation module is then fed back to the satellite data fusion module and the multi-source data fusion module.

[0061] Specifically, such as Figure 2 As shown in the figure, the system comprises various modules of the BeiDou satellite-based augmentation data processing system, including the BeiDou multi-frequency signal receiving module, data processing module, satellite data fusion module, multi-information source data fusion module, and positioning calculation module, as well as the data flow and interaction relationships between the modules.

[0062] Specifically: The BeiDou multi-frequency signal receiving module is a BeiDou receiver, including antenna 1 and receiver RF front-end 2. The antenna is connected to receiver RF front-end 2, and receiver RF front-end is connected to the data processing module. The antenna is used to receive BeiDou multi-frequency signals. As the core component of the receiver system, the receiver RF front-end mainly undertakes the functions of filtering, amplifying, and frequency conversion of RF signals. It is used to discretize the received RF analog signals into lower-frequency digital intermediate frequency signals containing BeiDou signal components, and performs necessary filtering and gain control in this process.

[0063] In this embodiment, the BeiDou receiver uses an antenna that supports multi-band satellite signal reception and multi-channel parallel processing; it also utilizes a low-noise amplifier and an adaptive filter to reduce noise interference, enhance signal strength and stability, improve the ability to receive weak signals, and simultaneously receive satellite signals from multiple frequency bands.

[0064] The data processing module 10 includes multiple channels, each with the same structure, independent of each other, and controllable separately. Each channel includes a correlator channel 3, a data parsing module 4, and a data verification and error correction module 5. The correlator channel is connected to the receiver's RF front end, the data parsing module is connected to the correlator channel, the data verification and error correction module is connected to the data parsing module, and the data verification and error correction module is connected to the satellite data fusion module, the multi-source data fusion module, and the positioning calculation module, respectively.

[0065] Each correlator channel can use the codeword of a certain satellite signal, so multiple correlator channels can work simultaneously to capture and track multiple satellite signals at different frequencies.

[0066] The data analysis module employs advanced algorithms such as matched filtering and coherent integration to analyze multi-band satellite signals, examining their phase, frequency, and other characteristics. By considering the differences in the propagation characteristics of multi-frequency signals in the ionosphere, it extracts satellite navigation messages and measurement data.

[0067] like Figure 3 As shown, the correlator channel performs signal acquisition and tracking to obtain the Doppler frequency, frame synchronization, and carrier phase. Based on the frame synchronization, the message is parsed to obtain the satellite's corrected data and ephemeris / clock bias / TGD. Finally, the positioning solution is performed based on the Doppler frequency, the satellite's corrected data, and the ephemeris / clock bias / TGD and carrier phase.

[0068] The data verification and error correction module performs CRC data verification on the received satellite message. If a bit error is found, error correction code technology is used to correct it. Specifically, after the data parsing module completes parsing, it performs CRC code verification on the data. If an error is detected, different error correction codes are used for correction depending on the satellite system. For example, the BeiDou GEO satellite system uses BCH code, the PPP-B2B satellite system uses LDPC code, and the BDS SBAS system uses Turbo code to ensure the accuracy of the extracted message information and measurement data.

[0069] The satellite data fusion module includes a satellite selection module 6 and a multi-satellite data fusion module 7. The satellite selection module is connected to the data verification and error correction module. The multi-satellite data fusion module is connected to the satellite selection module and the positioning calculation module, respectively. The positioning calculation module is connected to the multi-satellite data fusion module.

[0070] The satellite selection module monitors information such as the elevation angle, satellite data URA, data integrity, satellite health indicators, data coverage, and data validity period of each satellite in real time. Based on the monitored information, it selects satellites, giving priority to those with an elevation angle greater than a certain threshold (e.g., 15°), URA less than a set value (e.g., 1m), complete data, normal satellite health indicators, data coverage of the current area, and within the validity period.

[0071] If the number of satellites meeting the criteria exceeds the satellite quantity threshold, a secondary selection is performed based on signal strength, for example, selecting satellites with a carrier-to-noise ratio (CN0) greater than 40 dB. The carrier-to-noise ratio is the ratio of the carrier power to the noise power of the received signal, reflecting the contrast between signal strength and background noise levels.

[0072] The multi-satellite data fusion module analyzes the augmented data from selected satellites to extract key information. It employs a Kalman filter algorithm to fuse the multi-satellite data, assigning weights to selected satellites based on their signal quality (e.g., signal-to-noise ratio). Satellites with better signal quality have higher weights, while those with poorer signal quality have lower weights.

[0073] Multi-satellite data fusion refers to assigning different weights to different satellites within the same satellite system (e.g., all of them are BeiDou GEO satellite systems, or all of them are PPP-B2B satellite systems, or all of them are BDS SBAS satellite systems) based on their elevation angle, URA, message integrity, message health indicators, and other information. When performing positioning calculations, these data with different weights are used to calculate the position and time.

[0074] The multi-source data fusion module integrates enhanced data from multiple sources, including BeiDou GEO satellites, BeiDou SBAS, and BeiDou PPP-B2b. Based on the characteristics and accuracy of each source in different scenarios, appropriate weights are assigned to each source. For example, in regions and seasons with intense ionospheric activity, the weight of BeiDou GEO satellite grid ionospheric information is increased; in scenarios requiring high-precision positioning, the weight of BeiDou PPP-B2b enhanced information is increased.

[0075] Multi-source fusion refers to assigning different weights to corrected data from different satellite systems (such as corrected data from the BeiDou GEO satellite system, or corrected data from the PPP-B2B satellite system, or corrected data from the BDS SBAS satellite system) in different application scenarios (such as ordinary positioning or high-precision positioning, static positioning or dynamic positioning, such as the location of the receiver and the working time (different geographical locations are affected by the ionosphere differently, and the activity of the ionosphere varies in different seasons)) before participating in the positioning calculation process.

[0076] Multi-source fusion and multi-satellite fusion can be understood as the fusion of correction data from two different dimensions. For example, in low-latitude regions where the ionosphere has a significant impact, during the active periods of spring and summer and autumn and winter, the receiver assigns higher weight to the correction data output by satellites with high elevation angles, small URA, complete messages, and healthy messages in the BDS SBAS or BeiDou GEO satellite systems, and then participates in the final positioning calculation.

[0077] The correction data provided by each system may differ: for example, the BeiDou GEO satellite system provides clock error correction data and grid ionospheric correction data; the BDS SBAS system provides fast-varying corrections, slow-varying corrections, and grid ionospheric correction data; and the PPP-B2B system provides orbit correction data, clock error correction data, and inter-symbol error correction data.

[0078] These correction values ​​are factored into the final positioning result of the user receiver, resulting in a more accurate positioning result.

[0079] The positioning and solving module performs positioning calculations based on the fused data, using the least squares method to solve the positioning equations. During the solution process, the data is iteratively optimized to improve positioning accuracy. Simultaneously, the positioning results are quality-assessed; if the positioning error exceeds a threshold, the weights of the data fusion and the parameters of the positioning calculation are adjusted based on the absolute value of the error. This process is repeated multiple times until the positioning error falls below the set threshold, at which point the optimized positioning result is adopted.

[0080] For example, during seasons when the ionosphere is active, when using a receiver for static positioning, by assigning higher weights to the gridded ionospheric correction data of satellites with high elevation angles, low URA, complete and healthy messages in the BeiDou GEO satellite system, the processed correction data is added as a correction item to the final positioning calculation process of the user receiver. This results in more accurate positioning results with smaller error fluctuations, and especially more accurate altitude information estimation.

[0081] This embodiment provides a BeiDou satellite-based augmentation data processing system. Through scientific satellite selection and effective data fusion, it makes full use of high-quality satellite data and combines multi-information source fusion to effectively solve various error problems, significantly improve the positioning accuracy of the BeiDou satellite navigation system, and achieve high-precision single-point positioning at the decimeter or even centimeter level.

[0082] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any way. Other variations and modifications are possible without departing from the technical solutions described in the claims.

Claims

1. A method for processing BeiDou satellite-based augmentation data, characterized in that, include: S1: Simultaneously receive signals from multiple frequency bands of BeiDou satellites, analyze the received multi-frequency signals, and extract signal parameters; S2: Select the best satellite for reception based on satellite parameters, parse the enhanced data of the selected satellite, fuse the data of multiple satellites, and allocate weights according to the satellite signal quality; S3: Fusion of data from different satellite information sources, and allocation of weights to the information sources based on their characteristics and accuracy requirements; S4: Perform positioning calculations based on the fused data, and determine whether to use the positioning calculation results to optimize the data fusion weights based on the positioning error.

2. The BeiDou satellite-based augmentation data processing method according to claim 1, characterized in that, S1 includes: performing CRC check on the parsed data using a redundancy check code; if one or more bits in the data are found to be incorrect, then using different error correction code techniques to correct the error according to different satellite systems.

3. The BeiDou satellite-based augmentation data processing method according to claim 1, characterized in that, In S3, during the data fusion of multiple satellite information sources, the weights of each information source are adjusted according to different application scenarios and environmental conditions: in areas and seasons with intense ionospheric activity, the weight of the ionospheric information from the BeiDou GEO satellite grid is increased. In scenarios requiring high-precision positioning, the weight of BeiDou-3 augmentation information should be increased.

4. A BeiDou satellite-based augmentation data processing method according to claim 1, 2, or 3, characterized in that, In step S2, initial screening conditions are set. If the number of satellites that meet the initial screening conditions is greater than the satellite number threshold, the satellites are screened a second time based on the signal strength.

5. The BeiDou satellite-based augmentation data processing method according to claim 4, characterized in that, The initial screening criteria are: selecting satellites with an elevation angle greater than a set first threshold, URA less than a set second threshold, complete data with normal satellite health indicators, and data covering the current area and within the validity period.

6. A BeiDou satellite-based augmentation data processing method according to claim 1, 2, or 3, characterized in that, In step S1, matched filtering and coherent integration algorithms are used to analyze multi-band satellite signals, analyze the phase and frequency characteristics of multi-band satellite signals, and extract satellite navigation messages and measurement data by combining the differences in propagation characteristics of multi-band satellite signals in the ionosphere.

7. A BeiDou satellite-based augmentation data processing method according to claim 1, 2, or 3, characterized in that, The positioning results are evaluated for quality. If the positioning error does not exceed the set threshold, the weights of data fusion and the parameters of positioning solution are not adjusted. Otherwise, the weights of data fusion are adjusted using the parameters of positioning solution, and iterative optimization is performed until the positioning error is reduced to below the set threshold.

8. A BeiDou satellite-based augmentation data processing system, characterized in that, include: The BeiDou multi-frequency signal receiving module simultaneously receives signals from multiple frequency bands of BeiDou satellites. The data processing module is equipped with multiple channels, each channel analyzes a frequency band signal and extracts signal parameters; The satellite data fusion module selects satellites and analyzes the augmented data from the selected satellites to extract positioning information. The multi-source data fusion module integrates data from multiple satellite information sources and selects the source data based on the application scenario, application time, and location. The positioning and solving module performs positioning and solving based on the fused data and outputs the user's location information.

9. A BeiDou satellite-based augmentation data processing system according to claim 8, characterized in that, Each channel includes a correlator channel connected to the receiver's radio frequency front end. The correlator channel is connected to a data parsing module, which is connected to a data verification and error correction module. The data verification and error correction module is connected to both a satellite data fusion module and a positioning calculation module. The data parsing module parses the multi-frequency signals to extract observational information and satellite message information. The data verification and error correction module uses redundancy check codes and error correction codes to verify and correct the parsed data.

10. A BeiDou satellite-based augmentation data processing system according to claim 8 or 9, characterized in that, The satellite data fusion module includes: The satellite selection module detects satellite parameters in real time and selects satellites based on these parameters. If the number of selected satellites exceeds the satellite quantity threshold, a secondary selection is performed based on signal strength. The multi-satellite data fusion module analyzes the augmented data of selected satellites, uses the Kalman filter algorithm to fuse the multi-satellite data, and assigns weights to the selected satellites based on the satellite signal quality.

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