A low earth orbit satellite based navigation processing method and system

Abstract

The application provides a kind of navigation processing method and system based on low-orbit satellite, belong to navigation technical field, based on ground monitoring station, low-orbit satellite carried GNSS receiver and ground sensor obtain observation data;Orbit determination is executed and clock difference is determined, and navigation information is formed;Navigation information is encoded, and navigation information is uploaded to low-orbit satellite through ground data station or intersatellite link;Low-orbit satellite broadcasts navigation information to ground terminal in real time through information broadcast module.Ground terminal receives navigation signal from low-orbit satellite and GNSS satellite, and tracks and demodulates navigation signal, and extracts navigation information.The application integrates the multiple observation data of ground monitoring station, low-orbit satellite carried GNSS receiver and ground sensor, also improves the accuracy and real-time performance of navigation information through precise orbit determination and clock difference determination technology.

Description

Technical Field

[0001] This invention belongs to the field of navigation technology, and in particular relates to a navigation processing method and system based on low-Earth orbit satellites. Background Technology

[0002] With the development of global navigation technology, the demand for high-precision, high-reliability, and real-time navigation services is increasing. Traditional Global Navigation Satellite Systems (GNSS), such as GPS, GLONASS, Galileo, and BeiDou, while providing global navigation coverage, may have limitations in positioning accuracy and convergence speed in certain application scenarios, such as complex environments like urban canyons and mountainous areas. To compensate for this deficiency, low-Earth orbit (LEO) satellite navigation is currently used to achieve navigation and positioning in complex environments such as urban canyons and mountainous areas.

[0003] However, existing navigation and positioning methods can only acquire observation data, resulting in inaccurate navigation and positioning data and imprecise location. Due to the lack of effective determination of clock bias, it is impossible to obtain the clock bias of low-orbit satellites, resulting in poor time synchronization accuracy and failing to meet the high-precision requirements of real-time navigation. Summary of the Invention

[0004] This invention provides a navigation processing method based on low-Earth orbit satellites, which integrates multi-dimensional observation data from ground monitoring stations, GNSS receivers carried by low-Earth orbit satellites, and ground sensors. It also improves the accuracy and real-time performance of navigation information through precise orbit determination calculation and clock error determination technology.

[0005] The methods include:

[0006] S101: Observational data is acquired based on ground monitoring stations, GNSS receivers carried by low-orbit satellites, and ground sensors;

[0007] S102: Perform orbit determination calculations and determine clock errors to generate navigation information;

[0008] S103: The navigation information is encoded and uploaded to the low-Earth orbit satellite via ground data transmission station or inter-satellite link; the low-Earth orbit satellite broadcasts the navigation information to the ground terminal in real time through the information broadcasting module.

[0009] Among them, the navigation information format is configured according to the preset format;

[0010] S104: The ground terminal receives navigation signals from low-orbit satellites and GNSS satellites, tracks and demodulates the navigation signals, and extracts navigation information.

[0011] It should be further noted that in step S101, the observation data includes observation data of low-Earth orbit satellites from ground monitoring stations, observation data of inter-satellite links between low-Earth orbit satellites, and observation data of medium and high-Earth orbit navigation satellites.

[0012] It should be further noted that step S102 also includes:

[0013] S1021: Processing observation data based on cycle slip detection and gross error removal;

[0014] S1022: Obtain the position sequence and clock bias of navigation satellites and low-Earth orbit satellites based on navigation satellite broadcast ephemeris;

[0015] S1023: Perform orbit integration based on the dynamic parameters of navigation satellites and low-Earth orbit satellites to obtain the initial orbit and state transition matrix;

[0016] S1024: Configure the joint orbit determination method and set additional prior constraints on the parameters to be estimated. Use the least squares batch processing method to solve the parameters to be estimated by superimposing the normal equations of the epochs.

[0017] S1025: Use dynamic parameter information to perform orbit integration on navigation satellites and low-Earth orbit satellites to obtain orbit and observation residuals;

[0018] S1026: Perform observation residual test. After the post-test residual is less than the preset residual threshold, perform double difference ambiguity fixation to obtain ambiguity fixation mark, and then perform parameter estimation with additional ambiguity fixation mark.

[0019] It should be further explained that in step S1021, the Mw combination method is used to perform cycle slip detection on the ground monitoring station, the GNSS receiver carried by the low-orbit satellite, and the ground sensor to obtain the cycle slip detection results.

[0020] Then, the GF combination method is used to perform secondary cycle slip detection on the cycle slip detection results to obtain the secondary cycle slip detection results.

[0021] It should be further explained that in step S101, a data communication link is established between the ground monitoring station, the low-orbit satellite, and the ground sensors;

[0022] Ground monitoring stations are used to continuously observe low-Earth orbit satellites and collect observation data, including pseudorange and carrier phase.

[0023] The GNSS receiver continuously receives signals from medium and high orbit navigation satellites;

[0024] It also includes a data processing center to receive and integrate all observation data.

[0025] It should be further noted that step S102 also includes: determining the orbital parameters of the low-Earth orbit satellite based on the dynamic model and numerical integration method;

[0026] The orbit determination solution uses a numerical integration method, combining observation data and dynamic models, to perform precise orbit determination for low-Earth orbit satellites;

[0027] Based on the precise orbit determination results, short-term orbit predictions are made for low-Earth orbit satellites to meet real-time navigation requirements.

[0028] It should be further noted that, in the method, after completing the orbit determination and clock error determination, the navigation information encoding stage begins;

[0029] The orbit determination results, clock error information, and navigation parameters are encoded to form a standard navigation information format.

[0030] After encoding, the navigation information will be uploaded to the low-Earth orbit satellite via ground data transmission stations or inter-satellite links; the information broadcasting module carried by the low-Earth orbit satellite is used to broadcast the navigation information to the ground terminal in real time.

[0031] It should be further noted that step S104 also includes: the ground terminal tracks and demodulates the navigation signal, extracts the navigation information, and uses methods such as least squares or Kalman filtering to solve the navigation signal, thereby realizing the positioning and time synchronization of the ground terminal.

[0032] It should be further noted that the method also includes: determining the number of orbital planes based on coverage requirements and the number of satellites;

[0033] Define the number of low-Earth orbit satellites in each orbital plane to ensure the number of low-Earth orbit satellites in each orbital plane;

[0034] By calculating the optimal phase factor, the relative positions of low-Earth orbit satellites within the constellation are determined to optimize inter-satellite links and signal coverage;

[0035] Define the coverage area and orbital inclination;

[0036] Establish a navigation optimization model for multi-target low-Earth orbit satellites;

[0037] Set constraints on the number of satellites and the range of orbital parameters;

[0038] By utilizing the global search capability of genetic algorithms, the optimal solution is found within the parameter space;

[0039] The particle swarm optimization algorithm is used to optimize the navigation optimization model for multi-target low-Earth orbit satellites; adjustments are then made to the optimized navigation optimization model for multi-target low-Earth orbit satellites.

[0040] According to another embodiment of this application, a navigation processing system based on low-Earth orbit satellites is provided, the system comprising:

[0041] The data observation component acquires observation data based on ground monitoring stations, GNSS receivers carried by low-orbit satellites, and ground sensors;

[0042] The information processing component is used to perform orbit determination calculations and determine clock errors to generate navigation information.

[0043] The encoding navigation processing component is used to encode navigation information and upload it to the low-Earth orbit satellite via ground data transmission station or inter-satellite link; the low-Earth orbit satellite broadcasts the navigation information to the ground terminal in real time through the information broadcasting module.

[0044] Ground terminals are used to receive navigation signals from low-Earth orbit satellites and GNSS satellites, track and demodulate the navigation signals, and extract navigation information.

[0045] As can be seen from the above technical solutions, the present invention has the following advantages:

[0046] The navigation processing method based on low-Earth orbit (LEO) satellites provided in this application is based on precise orbit determination results and enables the prediction of LEO satellite orbits. It also combines dynamic models and real-time observation data to accurately predict LEO satellite orbital changes in the near future, thus meeting the high-precision requirements of real-time navigation.

[0047] The navigation processing method based on low-Earth orbit (LEO) satellites provided in this application improves the accuracy and real-time performance of navigation. By integrating observation data from ground monitoring stations, GNSS receivers on LEO satellites, and ground sensors, the information required for navigation can be obtained, thereby improving navigation accuracy. Numerical integration methods and precise orbit determination techniques are employed to perform orbit determination processing on the LEO satellites, ensuring navigation precision.

[0048] This invention enhances the stability and reliability of the navigation system by introducing inter-satellite link observation data. The existence of inter-satellite links enables direct data transmission and calibration between low-Earth orbit satellites, reducing reliance on ground facilities and improving the navigation system's adaptability in complex environments.

[0049] The navigation processing method based on low-Earth orbit (LEO) satellites provided in this application effectively improves the accuracy of time synchronization by determining the clock difference. This allows for more accurate calculation of the LEO satellite clock difference, thereby achieving more precise time synchronization. Attached Figure Description

[0050] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1 This is a flowchart of a navigation processing method based on low-Earth orbit satellites.

[0052] Figure 2 A flowchart illustrating an embodiment of a navigation processing method based on low-Earth orbit satellites;

[0053] Figure 3 This is a schematic diagram of a navigation processing system based on low-Earth orbit satellites. Detailed Implementation

[0054] The navigation processing method based on low-Earth orbit satellites provided in this application integrates multi-dimensional observation data from ground monitoring stations, GNSS receivers carried by low-Earth orbit satellites, and ground sensors. Furthermore, through precise orbit determination calculations and clock error determination techniques, it significantly improves the accuracy and real-time performance of navigation information.

[0055] This application enables the comprehensive fusion of observation data from ground monitoring stations on low-Earth orbit (LEO) satellites, inter-satellite links between LEO satellites, and medium- and high-Earth orbit (MEO) navigation satellites. This data fusion method can fully utilize the advantages of various types of observation data, improving the reliability and accuracy of navigation information.

[0056] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] Please see Figure 1 The diagram shows a flowchart of a navigation processing method based on low-Earth orbit satellites in a specific embodiment. The method includes:

[0058] S101: Observational data is acquired based on ground monitoring stations, GNSS receivers carried by low-orbit satellites, and ground sensors.

[0059] In some embodiments, observation data of low-Earth orbit satellites by ground monitoring stations, GNSS receivers carried by low-Earth orbit satellites, and other relevant sensors are acquired, including observation data of low-Earth orbit satellites by ground monitoring stations, inter-satellite link observation data between low-Earth orbit satellites, and observation data of medium and high-Earth orbit navigation satellites.

[0060] S102: Perform orbit determination calculations and determine clock errors to generate navigation information.

[0061] In this embodiment, observation data acquired by ground monitoring stations, low-orbit satellite-borne GNSS receivers, and inter-satellite link equipment are jointly processed.

[0062] Optionally, the orbit determination solution can be performed using numerical integration methods, combining observation data and dynamic models to perform precise orbit determination solutions for low-Earth orbit satellites.

[0063] This embodiment uses precise orbit determination results to provide short-term orbit predictions (e.g., 1-2 hours) for low-Earth orbit satellites to meet real-time navigation requirements.

[0064] In this embodiment, for determining clock bias, constraints can be set, that is, satellite clock bias can be determined using real-time observation data under the constraints of precise satellite orbit.

[0065] For clock bias calculation, Kalman filtering can be used to calculate the clock bias of low-Earth orbit satellites.

[0066] S103: The navigation information is encoded and uploaded to the low-Earth orbit satellite via ground data transmission station or inter-satellite link; the low-Earth orbit satellite broadcasts the navigation information to the ground terminal in real time through the information broadcasting module; wherein, the navigation information format is configured according to the preset format.

[0067] In this embodiment, the precise orbit and clock error calculation results are encoded into navigation information. This ensures that the format of the navigation information conforms to relevant standards and specifications, facilitating user reception and decoding. The navigation information is then uploaded to the low-Earth orbit satellite via ground data transmission stations or inter-satellite links.

[0068] S104: The ground terminal receives navigation signals from low-orbit satellites and GNSS satellites, tracks and demodulates the navigation signals, and extracts navigation information.

[0069] In this embodiment, the ground user configures a compatible receiver to receive navigation signals from both low-Earth orbit (LEO) satellites and GNSS satellites. The receiver tracks and demodulates the received signals to extract navigation information. The navigation information from the LEO satellites and GNSS satellites is then fused.

[0070] The navigation processing method based on low-Earth orbit (LEO) satellites provided in this application, based on precise orbit determination results, enables short-term prediction of LEO satellite orbits. It also combines dynamic models and real-time observation data to accurately predict LEO satellite orbital changes within a short period, thus meeting the high-precision requirements of real-time navigation. Furthermore, after receiving navigation signals at the ground terminal, this embodiment employs advanced algorithms such as least squares or Kalman filtering to solve the navigation signals. This fully utilizes redundant information from the observation data, improving the stability and accuracy of the solution, and achieving high-precision positioning and time synchronization for the ground terminal.

[0071] Based on the above method, the following are the specific steps for another implementation of the orbit determination calculation and clock error determination to form navigation information, such as... Figure 2 As shown, the specific steps include the following:

[0072] S1021: The observation data is processed based on the method of detecting cycle slips and eliminating gross errors.

[0073] In this embodiment, cycle slip detection is based on the assumptions that the phase measurement value of the GNSS signal changes continuously and the clock error of the satellite receiver changes slowly. A cycle slip is determined by comparing the phase measurement values ​​at two consecutive moments.

[0074] This embodiment can calculate the phase difference using the carrier phase measurement of the GNSS signal. That is, it uses the phase difference and the wavelength of the GNSS signal to calculate the distance change corresponding to the phase difference. If the distance change corresponding to the phase difference exceeds a threshold of one wavelength, a cycle slip is considered to have occurred.

[0075] This embodiment of outlier removal involves preprocessing the observed data to calculate its arithmetic mean and residual error. When calculating the standard deviation, a suitable interval is set. Errors exceeding this interval are considered outliers and removed.

[0076] S1022: Obtain the position sequence and clock bias of navigation satellites and low-Earth orbit satellites based on the broadcast ephemeris of navigation satellites.

[0077] This embodiment can receive broadcast ephemeris data from navigation satellites at a ground receiving station. The broadcast ephemeris is decoded to extract the position sequences and clock bias information of the navigation satellites and low-Earth orbit satellites. The extracted position sequences and clock bias information are synchronized with the time system of the ground receiving station to ensure data accuracy and consistency.

[0078] S1023: Perform orbit integration based on the dynamic parameters of navigation satellites and low-Earth orbit satellites to obtain the initial orbit and state transition matrix.

[0079] In this embodiment, the determined dynamic parameters include the satellite's initial position, velocity, mass, thrust, etc. Based on these dynamic parameters, the satellite's equations of motion are established.

[0080] Optionally, the Runge-Kutta method can be used as a numerical integration method to solve the satellite's equations of motion. Then, the numerical integration method is used to integrate the satellite's equations of motion to obtain the satellite's orbital sequence. During the integration process, the satellite's state changes are recorded, generating a state transition matrix to describe the evolution of the satellite's state over time.

[0081] S1024: Configure the joint orbit determination method and set additional prior constraints on the parameters to be estimated. Use the least squares batch processing method to solve the parameters to be estimated by superimposing the normal equations of the epochs.

[0082] This embodiment selects a suitable joint orbit determination method, such as centralized ground-based calculation or on-board autonomous calculation. The satellite position, velocity, clock bias, etc., to be estimated are determined, and prior constraints on these parameters are set. Then, using observation data and a dynamic model, normal equations for each epoch are constructed. The normal equations from multiple epochs are superimposed to form a large system of linear equations. Finally, a least-squares batch processing method is used to solve the superimposed system of linear equations to obtain the optimal estimates of the parameters to be estimated.

[0083] S1025: Use dynamic parameter information to perform orbit integration on navigation satellites and low-Earth orbit satellites to obtain orbit and observation residuals.

[0084] This embodiment inputs known dynamic parameters into the orbital integral model. Using numerical integration, the satellite's equations of motion are integrated to obtain the satellite's orbital sequence. The orbital integration results are compared with actual observation data to calculate the observation residuals.

[0085] S1026: Perform observation residual test. After the post-test residual is less than the preset residual threshold, perform double difference ambiguity fixation to obtain ambiguity fixation mark, and then perform parameter estimation with additional ambiguity fixation mark.

[0086] This embodiment examines the calculated residuals of the observed values ​​to determine whether they meet the preset residual threshold requirements.

[0087] It should be noted that double-difference ambiguity fixing uses the double-difference observations between signals from two different satellites received by two different observation stations to fix the ambiguity.

[0088] This process involves calculating double-difference observations. The LAMBDA algorithm is then used to search for and fix ambiguities in these observations, resulting in ambiguity fixation markers. These markers are then used as additional constraints to re-estimate parameters. This allows for more comprehensive acquisition of the information needed for navigation, thereby improving navigation accuracy.

[0089] As another implementation of this application, this embodiment establishes a data communication link between the ground monitoring station, the low-Earth orbit satellite, and the ground sensors when constructing the low-Earth orbit satellite navigation processing system. The ground monitoring station is responsible for continuously observing the low-Earth orbit satellite and collecting observation data including pseudorange and carrier phase. At the same time, the GNSS receiver carried by the low-Earth orbit satellite also continuously receives signals from medium and high-Earth orbit navigation satellites, providing data support for subsequent orbit determination calculations.

[0090] This embodiment can also be configured with a data processing center, which receives and integrates all observation data. The data processing center employs a high-performance computer cluster to ensure the real-time performance and accuracy of data processing.

[0091] After data preprocessing, this embodiment proceeds to the orbit determination stage. Based on the dynamic model and numerical integration method, the orbit of the low-Earth orbit satellite is precisely determined.

[0092] In selecting the numerical integration method, this embodiment employs a high-precision, high-efficiency integration algorithm to ensure the accuracy and real-time performance of the orbit determination calculation. By combining observation data and a dynamic model, precise determination of the low-Earth orbit satellite orbit can be achieved to meet the requirements of real-time navigation.

[0093] In this embodiment, regarding clock bias determination, real-time observation data is used to calculate the clock bias of low-Earth orbit satellites under the constraint of satellite orbit. This method can effectively improve the accuracy and stability of clock bias determination, providing an accurate time reference for subsequent navigation information encoding and broadcasting.

[0094] After completing the orbit determination and clock bias determination, this embodiment proceeds to the navigation information encoding stage. The orbit determination results, clock bias information, and navigation parameters are encoded to form a standard navigation information format. The encoding process follows preset format configuration specifications to ensure the universality and compatibility of the navigation information.

[0095] After encoding, the navigation information will be uploaded to the low-Earth orbit (LEO) satellite via ground data transmission stations or inter-satellite links. The information broadcasting module onboard the LEO satellite is responsible for broadcasting the navigation information to ground terminals in real time. During the broadcasting process, we employ efficient modulation techniques and error correction coding methods to ensure the transmission efficiency and reliability of the navigation information.

[0096] In this embodiment, the ground terminal serves as the end-user terminal of the navigation system, capable of receiving navigation signals from low-Earth orbit (LEO) satellites and GNSS satellites. During reception, the ground terminal first tracks and demodulates the navigation signals to extract navigation information. Then, it uses methods such as least squares or Kalman filtering to process the navigation signals, achieving positioning and time synchronization for the ground terminal.

[0097] In this way, the method can not only improve the accuracy and real-time performance of the navigation system, but also expand the coverage and application scenarios of the navigation system.

[0098] In this embodiment, the following implementation steps can be adopted when performing orbit determination calculation.

[0099] Collect observation data from ground monitoring stations on low-Earth orbit satellites, inter-satellite link observation data between low-Earth orbit satellites, and observation data from medium and high-Earth orbit navigation satellites.

[0100] Establish a dynamic model. A dynamic model can accurately describe the motion of a low-Earth orbit satellite in space.

[0101] By combining observational data and dynamic models, a numerical integration method is used to perform precise orbit determination for low-Earth orbit satellites. Through iterative calculations, the satellite orbital parameters are continuously optimized until the preset accuracy requirements are met.

[0102] Based on precise orbit determination results, short-term orbit predictions are made for low-Earth orbit satellites. The prediction results can meet real-time navigation requirements, providing continuous and stable navigation services to ground terminals.

[0103] In this embodiment, navigation information is broadcast in real time and the ground terminal is ensured to receive it accurately during the implementation of the low-orbit satellite navigation system.

[0104] Specifically, encoding navigation information ensures accurate data transmission. After orbit determination and clock bias assessment, the resulting navigation information needs to be configured and encoded according to a preset format. The calculated orbit parameters, clock bias data, and other relevant navigation information are converted into a standardized data format to facilitate subsequent transmission and processing.

[0105] The encoded navigation information is uploaded to low-Earth orbit satellites via ground data transmission stations or inter-satellite links. Ground data transmission stations, acting as the communication hub between the ground and satellites, play a crucial role in uploading navigation information to satellites in real time. Inter-satellite links enable direct communication between satellites, allowing for efficient transmission of navigation information within the satellite network. During the upload process, it is essential to ensure the real-time nature and accuracy of the information to meet the real-time update requirements of the navigation system.

[0106] In this embodiment, the low-Earth orbit (LEO) satellite broadcasts navigation information to the ground terminal in real time via an information broadcasting module. The ground terminal acts as the end-user equipment of the navigation system. After receiving navigation signals from the LEO satellite and GNSS satellite, the ground terminal needs to track and demodulate the signals to extract the navigation information.

[0107] In terms of navigation signal processing, ground terminals can employ methods such as least squares or Kalman filtering to process the received navigation signals, improving the accuracy and stability of the processing. Using the obtained navigation information, the ground terminal can achieve precise positioning and time synchronization, thus meeting the needs of various application scenarios. This ensures that navigation information can be accurately transmitted and processed between low-Earth orbit satellites and ground terminals.

[0108] Based on the above embodiments, in order to further improve the reliability of the low-Earth orbit satellite-based navigation processing method provided in the above embodiments, and as an implementable approach, in one embodiment, the navigation processing method process can be optimized.

[0109] Specifically, in the optimization and implementation of low-Earth orbit (LEO) satellite navigation, the navigation system for LEO satellites is constructed. This involves ensuring global signal coverage and improving positioning accuracy and convergence speed.

[0110] This embodiment can define the navigation configuration of low-Earth orbit (LEO) satellites. LEO satellites can take into account the number of orbital planes, the number of satellites in each orbital plane, and the phase configuration between satellites, thereby meeting the basic requirements for positioning calculation.

[0111] This embodiment optimizes the parameters of low-Earth orbit satellites. Specifically, it involves adjusting the orbital altitude and orbital inclination to find the optimal balance between signal coverage and positioning performance. The choice of orbital altitude directly affects the satellite's coverage area and signal strength, while the orbital inclination relates to the satellite's visibility at different latitudes.

[0112] During the optimization process, a genetic algorithm is used to find the point that achieves the optimal balance between positioning performance, coverage multiplicity, and construction cost. By setting reasonable fitness functions and constraints, it can be ensured that the optimization results meet performance requirements.

[0113] This embodiment also constructs a model relating the equivalent geometric accuracy factor of a low-Earth orbit (LEO) satellite constellation to the probability of successful convergence in precise point positioning. The constellation configuration is adjusted based on the expected positioning performance and convergence speed. Through continuous iteration and optimization, a LEO-based navigation processing method that provides both global coverage and high-precision positioning services is ultimately obtained.

[0114] Specifically, the orbital parameters can be defined first. Based on coverage requirements and the number of satellites, the number of orbital planes is determined. Ensure that the number of satellites in each orbital plane is sufficient to provide continuous signal coverage. By calculating the optimal phase factor, the relative positions of the low-Earth orbit satellites are determined to optimize inter-satellite links and signal coverage.

[0115] Define the objective function and establish a multi-objective optimization model. Based on the actual limitations of satellite launch, operation, and maintenance, set constraints, including the number of satellites and the range of orbital parameters.

[0116] By leveraging the global search capability of genetic algorithms, the optimal solution is sought within the parameter space. Constellation parameters are progressively optimized through operations such as selection, crossover, and mutation.

[0117] Finally, satellite toolkits such as STK can be used for simulation verification to evaluate the performance of the optimized low-orbit satellite parameters in actual operation.

[0118] The genetic algorithm in this embodiment can evaluate the quality of individual low-Earth orbit satellites. The fitness function can be defined as a weighted sum of positioning performance, coverage multiplicity, and construction cost. Superior individuals are selected for genetic inheritance based on their fitness function values. Partial gene exchange between two individuals generates new individuals. Random modifications to the genes of individuals are made with a certain probability to increase population diversity.

[0119] Low Earth Orbit (LEO) satellite orbit calculations can begin by calculating the satellite's period and velocity in a specific orbit. The coverage area of ​​the satellite at different orbital altitudes can then be assessed. The visibility of the satellite to users at different orbital inclinations can be analyzed. Finally, the construction and optimization of LEO satellite constellations can be achieved.

[0120] Combining the above optimization methods, in the optimization process of low-Earth orbit satellites, the use of genetic algorithms can efficiently search in a complex parameter space and find the global optimal solution or a near-optimal solution.

[0121] When implementing the genetic algorithm, a fitness function is defined to ensure optimal results. The genetic algorithm population is then initialized, consisting of a set of candidate low-Earth orbit satellite configurations. Each configuration includes key parameters such as orbital altitude and inclination, which are continuously adjusted during the optimization process.

[0122] In the main loop of the genetic algorithm, operations such as selection, crossover, and mutation were performed to simulate natural selection and genetic processes. Through continuous iteration and optimization, a low-Earth orbit (LEO) satellite configuration that maximized the fitness function was gradually found. Based on the optimization results of the genetic algorithm, the final LEO satellite configuration was determined. The LEO satellite configuration defines parameters such as the orbital altitude, orbital inclination, and phase configuration of each satellite.

[0123] The following are embodiments of a low-Earth orbit (LEO) satellite-based navigation processing system provided in this disclosure. This system and the LEO satellite-based navigation processing methods described above belong to the same inventive concept. For details not described in detail in the embodiments of the LEO satellite-based navigation processing system, please refer to the embodiments of the LEO satellite-based navigation processing methods described above.

[0124] like Figure 3 As shown, the data observation component acquires observation data based on ground monitoring stations, GNSS receivers carried by low-orbit satellites, and ground sensors;

[0125] The information processing component is used to perform orbit determination calculations and determine clock errors to generate navigation information.

[0126] The encoding navigation processing component is used to encode navigation information and upload it to low-Earth orbit satellites via ground data transmission stations or inter-satellite links. The low-Earth orbit satellites then broadcast the navigation information to ground terminals in real time via an information broadcasting module.

[0127] Ground terminals are used to receive navigation signals from low-Earth orbit satellites and GNSS satellites, track and demodulate the navigation signals, and extract navigation information.

[0128] The ground terminal in this embodiment can be a mobile terminal (MT), mobile station (MS), mobile unit (MU), wireless unit, remote unit, user agent, mobile client, etc. For example, the ground terminal can be a mobile phone, smart screen device, tablet computer, wearable device, digital camera, vehicle-mounted device, augmented reality (AR) device, virtual reality (VR) device, laptop computer, ultra-mobile personal computer (UMPC), netbook, personal digital assistant (PDA), laptop computer, etc. This application embodiment does not limit this.

[0129] The ground terminal may include a processor, which may include one or more processing units, such as a central processing unit (CPU), an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, memory, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural network processing unit (NPU). Different processing units may be independent devices or integrated into one or more processors.

[0130] The processor can serve as the nerve center and command center of the ground terminal. Based on the instruction opcode and timing signals, the processor generates operation control signals to control instruction fetching and execution.

[0131] The processor may also include memory for storing instructions and data. In some embodiments, the memory in the processor is a cache memory. This memory can store instructions or data that the processor has just used or that are used repeatedly. If the processor needs to use the instruction or data again, it can retrieve it directly from this memory. This avoids repeated accesses, reduces processor latency, and thus improves system efficiency.

[0132] The ground terminal may also include an external storage interface for connecting external storage cards, such as MicroSD cards, to expand the storage capacity of the ground terminal. The external storage card communicates with the processor through the external storage interface 120 to perform data storage.

[0133] The ground terminal's internal memory can be used to store computer-executable program code, which includes instructions. The processor executes various functional applications and data processing of the ground terminal by running the instructions stored in the internal memory. The internal memory can include a program storage area and a data storage area. The program storage area can store the operating system, at least one application program required for a given function, etc. The data storage area can store data created by the ground terminal during use (such as audio data, phonebook data, etc.). Furthermore, the internal memory can include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, universal flash storage (UFS), etc.

[0134] The wireless communication function of a ground terminal can be implemented through antennas, mobile communication modules, wireless communication modules, modem processors, and baseband processors.

[0135] Wireless communication modules can provide solutions for wireless communication applications on ground terminals, including wireless local area networks (WLANs) (such as wireless fidelity (Wi-Fi) networks), Bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), and infrared (IR) technologies.

[0136] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily 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 invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A navigation processing method based on low-Earth orbit satellites, characterized in that, The methods include: S101: Observational data is acquired based on ground monitoring stations, GNSS receivers carried by low-orbit satellites, and ground sensors; S102: Perform orbit determination calculations and determine clock errors to generate navigation information; The orbital parameters of low-Earth orbit satellites are determined based on dynamic models and numerical integration methods. The orbit determination solution uses a numerical integration method, combining observation data and dynamic models, to perform precise orbit determination for low-Earth orbit satellites; Based on the precise orbit determination results, short-term orbit predictions are made for low-Earth orbit satellites to meet real-time navigation requirements; Step S102 also includes: S1021: Processing observation data based on cycle slip detection and gross error removal; S1022: Obtain the position sequence and clock bias of navigation satellites and low-Earth orbit satellites based on navigation satellite broadcast ephemeris; S1023: Perform orbit integration based on the dynamic parameters of navigation satellites and low-Earth orbit satellites to obtain the initial orbit and state transition matrix; S1024: Configure the joint orbit determination method and set additional prior constraints on the parameters to be estimated. Use the least squares batch processing method to solve the parameters to be estimated by superimposing the normal equations of the epochs. S1025: Use dynamic parameter information to perform orbit integration on navigation satellites and low-Earth orbit satellites to obtain orbit and observation residuals; S1026: Perform observation residual test. After obtaining the post-test residual which is less than the preset residual threshold, perform double difference ambiguity fixation to obtain ambiguity fixation mark, and then perform parameter estimation with additional ambiguity fixation mark. S103: The navigation information is encoded and uploaded to the low-Earth orbit satellite via ground data transmission station or inter-satellite link; the low-Earth orbit satellite broadcasts the navigation information to the ground terminal in real time through the information broadcasting module. Among them, the navigation information format is configured according to the preset format; S104: The ground terminal receives navigation signals from low-orbit satellites and GNSS satellites, tracks and demodulates the navigation signals, and extracts navigation information. The method also includes: determining the number of orbital planes based on coverage requirements and the number of satellites; Define the number of low-Earth orbit satellites in each orbital plane to ensure the number of low-Earth orbit satellites in each orbital plane; By calculating the optimal phase factor, the relative positions of low-Earth orbit satellites within the constellation are determined to optimize inter-satellite links and signal coverage; Define the coverage area and orbital inclination; Establish a navigation optimization model for multi-target low-Earth orbit satellites; Set constraints on the number of satellites and the range of orbital parameters; By utilizing the global search capability of genetic algorithms, the optimal solution is found within the parameter space; The particle swarm optimization algorithm is used to optimize the navigation optimization model for multi-target low-Earth orbit satellites; adjustments are then made to the optimized navigation optimization model for multi-target low-Earth orbit satellites.

2. The navigation processing method based on low-Earth orbit satellites according to claim 1, characterized in that, In step S101, the observation data includes observation data of low-Earth orbit satellites from ground monitoring stations, observation data of inter-satellite links between low-Earth orbit satellites, and observation data of medium and high-Earth orbit navigation satellites.

3. The navigation processing method based on low-Earth orbit satellites according to claim 1, characterized in that, In step S1021, the Mw combination method is used to perform cycle slip detection on data from ground monitoring stations, GNSS receivers carried by low-orbit satellites, and ground sensors to obtain cycle slip detection results; Then, the GF combination method is used to perform secondary cycle slip detection on the cycle slip detection results to obtain the secondary cycle slip detection results.

4. The navigation processing method based on low-Earth orbit satellites according to claim 1, characterized in that, In step S101, a data communication link is established between the ground monitoring station, the low-orbit satellite, and the ground sensors; Ground monitoring stations are used to continuously observe low-Earth orbit satellites and collect data including pseudorange and carrier phase observations. The GNSS receiver continuously receives signals from medium and high orbit navigation satellites; It also includes a data processing center to receive and integrate all observation data.

5. The navigation processing method based on low-Earth orbit satellites according to claim 1, characterized in that, In this method, after completing the orbit determination calculation and clock error determination, the navigation information encoding stage begins; The orbit determination results, clock error information, and navigation parameters are encoded to form a standard navigation information format. After encoding, the navigation information will be uploaded to the low-Earth orbit satellite via ground data transmission stations or inter-satellite links; the information broadcasting module carried by the low-Earth orbit satellite is used to broadcast the navigation information to the ground terminal in real time.

6. The navigation processing method based on low-Earth orbit satellites according to claim 1, characterized in that, Step S104 further includes: the ground terminal tracks and demodulates the navigation signal, extracts the navigation information, and uses methods such as least squares or Kalman filtering to solve the navigation signal, thereby achieving positioning and time synchronization of the ground terminal.

7. A navigation processing system based on low-Earth orbit satellites, characterized in that, The system is used to implement the low-Earth orbit satellite-based navigation processing method as described in any one of claims 1 to 6; The data observation component acquires observation data based on ground monitoring stations, GNSS receivers carried by low-orbit satellites, and ground sensors; The information processing component is used to perform orbit determination calculations and determine clock errors to generate navigation information. The coded navigation processing component is used to encode navigation information and upload it to low-Earth orbit satellites via ground data transmission stations or inter-satellite links. Low-orbit satellites transmit navigation information to ground terminals in real time via their information broadcasting modules; Ground terminals are used to receive navigation signals from low-Earth orbit satellites and GNSS satellites, track and demodulate the navigation signals, and extract navigation information.

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