Star-based high-precision positioning enhanced electric text star selection and broadcasting method based on greedy algorithm

Abstract

The application discloses a star-based high-precision positioning enhanced electric text star selection and broadcasting method based on a greedy algorithm, which comprises the following steps: calculating the user-satellite bidirectional visible relation matrix of user grid points and broadcasting satellites and to-be-broadcasting satellites; distributing each to-be-broadcasting satellite to be broadcast by at least one broadcasting satellite by maximizing the number of common visible users of the broadcasting satellite and the to-be-broadcasting satellite; diagnosing the coverage missing range of each to-be-broadcasting satellite, and realizing iterative optimization distribution by maximizing the common visible coverage gain between the to-be-broadcasting satellite and the broadcasting satellite; selecting the to-be-broadcasting satellite to fill the remaining capacity in combination with the number of visible user coverage, and then determining the broadcasting instruction list of each broadcasting satellite; and simulating the actual received to-be-broadcasting satellite correction value text set of global users according to the broadcasting instruction list and the user-satellite bidirectional visible relation matrix. Based on the method, the probability of broadcasting information repetition of the broadcasting satellite is reduced, and the reasonable utilization of the on-satellite uplink and downlink channel resources is ensured.

Description

Technical Field

[0001] This invention relates to the field of satellite navigation enhancement technology, and specifically to a satellite-based high-precision positioning enhancement message selection and broadcasting method based on a greedy algorithm. Background Technology

[0002] With the development of technologies such as Precise Point Positioning (PPP), broadcasting high-precision correction information from GNSS systems via geostationary orbit (GEO), inclined geosynchronous orbit (IGSO), and medium Earth orbit (MEO) satellites has become a key means of achieving wide-area real-time high-precision positioning services. Currently, the Galileo system, based on its existing constellation of over twenty MEO satellites, broadcasts high-precision correction information from both Galileo and GPS systems, providing high-precision real-time precise point positioning services (HAS) to users worldwide. Furthermore, the QZSS regional navigation augmentation system has also proposed its CLAS service. The CLAS service utilizes four IGSO satellites and one GEO satellite to achieve satellite-based broadcasting of high-precision augmentation information for a specific region.

[0003] Building high-precision global services relies heavily on MEO constellations for satellite-based broadcasting to achieve global Earth coverage. Similarly, LEO augmentation services require the broadcasting of high-precision corrections from medium- and high-Earth orbit (MEO) GNSS satellites via LEO satellites. For these services, the more GNSS satellites broadcasting via satellite, the better the positioning performance. However, the broadcasting capacity of a single MEO or LEO navigation satellite is limited, making it difficult to broadcast corrections from all GNSS satellites simultaneously. Furthermore, without a comprehensive and coordinated broadcasting strategy, different MEO / LEO satellites may broadcast a large amount of duplicate information, resulting in a significant waste of valuable satellite-to-ground transmission and reception resources. Summary of the Invention

[0004] To overcome the shortcomings of existing technologies, such as limited broadcast capacity of a single satellite and the potential for a large amount of duplicate information to be broadcast from different satellites, this invention provides a satellite-based high-precision positioning enhancement message selection and broadcasting method based on a greedy algorithm. Under the constraint of limited capacity of a single broadcasting satellite, a heuristic greedy algorithm is used to dynamically and intelligently allocate a suitable GNSS satellite correction broadcasting list to each broadcasting satellite. This aims to maximize the probability that global grid users can simultaneously receive corrections from all their visible GNSS satellites (i.e., achieve "complete coverage"), reduce the probability of duplicate broadcasting information, and ensure the rational utilization of satellite uplink and downlink transmission channel resources.

[0005] According to one aspect of the present invention, a satellite-based high-precision positioning enhancement message selection and broadcasting method based on a greedy algorithm is provided, comprising: acquiring a set of satellites to be broadcast and a set of broadcasting satellites with broadcasting capacity, and simulating the establishment of a global user grid set; calculating the two-way visibility relationship between user grid points and broadcasting satellites and satellites to be broadcasted, forming a user-satellite two-way visibility relationship matrix; performing initial allocation based on the user-satellite two-way visibility relationship matrix, including: allocating each satellite to be broadcasted to be broadcast by at least one broadcasting satellite by maximizing the number of users with common visibility between broadcasting satellites and satellites to be broadcasted; diagnosing the coverage gap of each satellite to be broadcasted based on the initial allocation result, and achieving iterative optimization allocation by maximizing the common visibility coverage gain between satellites to be broadcasted and broadcasting satellites; selecting satellites to be broadcasted to fill the remaining capacity based on the iterative optimization allocation result and the number of visible user coverage, thereby determining the broadcasting instruction list for each broadcasting satellite; and simulating the set of corrected satellite messages actually received by global users according to the broadcasting instruction list and the user-satellite two-way visibility relationship matrix.

[0006] Further, the bidirectional visibility relationship between user grid points and broadcasting satellites and satellites to be broadcasted is calculated to form a user-satellite bidirectional visibility relationship matrix. This includes: obtaining the spatial position coordinates of all user grid points and all satellites at the same epoch; the satellites include broadcasting satellites and satellites to be broadcasted; calculating the elevation angle between each user grid point and each satellite based on the spatial position coordinates of the user grid points and satellites; determining the visibility relationship between the user grid points and satellites based on the elevation angle between them, and generating corresponding visibility identifiers based on the visibility relationship; traversing all user grid points and all satellites, and generating a user-satellite bidirectional visibility relationship matrix based on the visibility identifiers of each user grid point and each satellite.

[0007] Furthermore, the criteria for determining the visibility relationship are as follows: when the elevation angle between the user grid point and the satellite is greater than a set threshold, it is determined that the user grid point can observe the satellite; otherwise, it is determined that the user grid point cannot observe the satellite.

[0008] Furthermore, by maximizing the number of users who share the same view between the broadcasting satellite and the satellite to be broadcasted, each satellite to be broadcast is allocated to be broadcast by at least one broadcasting satellite. This includes: for any satellite to be broadcasted, calculating the number of users who share the same view between the satellite to be broadcasted and each broadcasting satellite with broadcasting capacity; selecting the broadcasting satellite with the maximum number of users who share the same view with the satellite to be broadcasted, updating the used broadcasting capacity of the broadcasting satellite and adding the satellite to be broadcasted to its broadcasting list; repeating the above steps until all satellites to be broadcasted have been cycled through, thus obtaining a preliminary broadcasting list for each broadcasting satellite.

[0009] Furthermore, the coverage gap of each satellite to be broadcast is diagnosed, and iterative optimization allocation is achieved by maximizing the common-view coverage gain between the satellite to be broadcast and the broadcasting satellite. This includes: traversing all user grid points, diagnosing the missing satellites for each user grid point and constructing a global set of missing satellites; for each missing satellite, calculating the common-view coverage gain brought by allocating the missing satellite to each broadcasting satellite with broadcasting capacity that has not broadcasted the missing satellite; selecting the broadcasting satellite with the maximum common-view coverage gain, updating the used broadcasting capacity of the broadcasting satellite, and adding the missing satellite to its broadcasting list; repeating the above steps until a positive common-view coverage gain cannot be obtained, the global set of missing satellites is empty, there is no available broadcasting capacity, or the upper limit of the number of iterations is reached, to obtain an optimized broadcasting list for each broadcasting satellite.

[0010] Furthermore, by combining the number of visible user coverages, satellites to be broadcast are selected to fill the remaining capacity, thereby determining the broadcast instruction list for each broadcast satellite. This includes: traversing the allocated satellites to be broadcast in descending order of the total number of visible users to obtain the high-value satellites to be broadcast with the most current visible user coverage; finding broadcast satellites with broadcast capacity that have not yet been broadcast for the high-value satellites to be broadcast, and calculating the common-view coverage gain brought by allocating the high-value satellites to each of the broadcast satellites; selecting the broadcast satellite with the maximum common-view coverage gain, updating the used broadcast capacity of the broadcast satellite, and adding the high-value satellite to its broadcast list; repeating the above steps until there is no remaining broadcast capacity or no positive common-view coverage gain can be obtained, thus obtaining the broadcast instruction list for each broadcast satellite.

[0011] Furthermore, the global user grid set is established using an adaptive resolution grid strategy, including: in low and mid-latitude regions, a latitude and longitude interval of less than or equal to 10° is used; in high-latitude regions, a longitude interval of less than or equal to 30° is used, while maintaining a close latitude interval of less than or equal to 10°; no evaluation points are set in polar regions.

[0012] Furthermore, the method also includes: calculating core performance indicators by comparing the set of satellites to be broadcast visible to each user grid point with the actual set of corrected satellite messages to be broadcast.

[0013] According to one aspect of the present invention, a satellite-based high-precision positioning enhanced message satellite selection and broadcasting system based on a greedy algorithm is provided, implemented using the aforementioned greedy algorithm-based satellite-based high-precision positioning enhanced message satellite selection and broadcasting method, comprising: an ephemeris data processing module for acquiring a set of satellites to be broadcast and a set of broadcasting satellites with broadcasting capacity; a user grid modeling module for simulating and establishing a global user grid set; a visibility relationship calculation module for calculating the bidirectional visibility relationship between user grid points and broadcasting satellites and satellites to be broadcast, forming a user-satellite bidirectional visibility relationship matrix; and an initial allocation module for performing initial allocation based on the user-satellite bidirectional visibility relationship matrix, including: through the most... The system maximizes the number of users who share the same view between the broadcasting satellite and the satellite to be broadcasted, ensuring that each satellite to be broadcast is broadcast by at least one broadcasting satellite. An iterative optimization module diagnoses the coverage gaps of each satellite to be broadcasted based on the initial allocation results and achieves iterative optimization by maximizing the shared view coverage gain between the satellites to be broadcasted and the broadcasting satellite. A redundancy enhancement module selects satellites to be broadcasted to fill remaining capacity based on the iterative optimization allocation results and the number of visible user coverages, thereby determining the broadcast instruction list for each broadcasting satellite. A data reception simulation module simulates the set of corrected data messages from satellites to be broadcast that are actually received by global users, based on the broadcast instruction list and the user-satellite bidirectional visibility matrix.

[0014] According to one aspect of the present invention, a non-transitory computer-readable storage medium is provided, the non-transitory computer-readable storage medium storing computer instructions that cause the computer to execute the aforementioned satellite-based high-precision positioning enhancement message selection and broadcasting method based on a greedy algorithm.

[0015] The above technical solution designs a greedy optimization framework and proposes a three-stage optimization process combining initial coverage guarantee, iterative gap filling, and remaining capacity filling. In the initial coverage guarantee stage, satellites that can form the largest shared visible user group with each satellite are selected as its broadcasting satellites, and the output is an initial allocation scheme that meets the basic broadcasting coverage requirements. In the iterative gap filling stage, the remaining idle broadcasting capacity is used to fill in the gaps of missing satellites, maximizing the number of users with full coverage, and the output is an optimized allocation scheme after iterative gap filling. In the remaining capacity filling stage, the correction numbers of high-value satellites to be broadcast are reassigned to other broadcasting satellites that still have capacity and can serve the new user group. This operation increases the broadcasting redundancy path of key correction number information without reducing the already achieved coverage level.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0017] (1) The present invention enables efficient and intelligent selection of a group of GNSS satellites to be broadcast for each broadcasting satellite, and maximizes the completeness of message reception for global users and minimizes the duplication rate under the consideration of capacity constraints.

[0018] (2) This invention forms a coverage diagnosis and optimization driving mechanism for users by using a global gridded user simulation broadcast coverage index, realizes the mathematical mapping between broadcast resources and terminal service quality, and provides decision support for the design of technical parameters such as system broadcast capacity and related coverage performance indicators.

[0019] (3) This invention constructs a core quantitative evaluation index system such as satellite loss rate, epoch loss rate, and broadcast duplication rate, which can provide accurate measurement standards for algorithm performance comparison and parameter optimization.

[0020] (4) This invention is not only applicable to the application requirements of MEO satellite-based broadcasting of high-precision GNSS correction information, but can also be used for satellite-based broadcasting applications of subsequent low-orbit augmentation systems. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 A flowchart of a satellite-based high-precision positioning enhancement message selection and broadcasting method based on a greedy algorithm is provided for an embodiment of the present invention;

[0023] Figure 2 This is a schematic diagram illustrating the principle of a satellite-based high-precision positioning enhancement message selection and broadcasting system based on a greedy algorithm, provided as an embodiment of the present invention. Detailed Implementation

[0024] It should be noted that:

[0025] The terms “comprising” and “having”, and any variations thereof, in the specification, claims, and accompanying drawings of this invention are intended to cover a non-exclusive inclusion, such as a process, method, system, product, or apparatus that includes a series of steps or units, not necessarily limited to those explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices. The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be decomposed, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0027] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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, 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. In addition, the technical features of the various embodiments or individual embodiments provided by the present invention can be arbitrarily combined to form new technical solutions. Such combinations are not bound by the order of steps and / or structural composition patterns, but must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0028] Please refer to the appendix. Figure 1 This invention provides a satellite-based high-precision positioning enhancement message selection and broadcasting method based on a greedy algorithm. The greedy algorithm determines the satellites to be broadcast on each broadcasting satellite. For different broadcasting capacities and constellation settings (constellation includes broadcasting satellites and satellites to be broadcasted), the greedy algorithm dynamically adjusts the correction information of the satellites to be broadcast on each broadcasting satellite at each epoch, ensuring maximum ground coverage under full-load broadcasting conditions. To ensure uniform global sampling spatial distribution and accelerate simulation calculation speed, this invention employs an adaptive resolution grid strategy to simulate and establish a global user grid set. For example, low-latitude users are simulated using a 10° grid or denser, and high-latitude users using a 30° grid or denser. The specific satellites that a user can track are determined based on the geometric visibility relationship between the user grid points and all satellites, and the received set of satellite messages to be broadcast is determined based on the visible broadcasting satellite set. The spatiotemporal coverage performance of the broadcasting strategy is analyzed by comparing the observed set of satellite messages to be broadcast with the received set of messages.

[0029] The specific broadcast strategy algorithm is implemented based on a heuristic greedy algorithm. The design idea is to continuously approach the optimal solution that "maximizes user coverage" through multiple rounds of locally optimal selection under the constraint of global grid user visibility. Its core steps are as follows:

[0030] Step S1: Obtain the set of satellites to be broadcast and the set of broadcast satellites with broadcast capacity, and simulate the establishment of a global user grid set.

[0031] Step S1 aims to acquire and organize the initial input parameters for the satellite selection and broadcasting problem. These initial input parameters mainly include: the set of satellites to be broadcasted, the set of satellites to be broadcasted, the global user grid set, the coordinate set of all satellites to be broadcasted and the satellites to be broadcasted, and the broadcasting capacity constraint for each satellite. Both the satellites to be broadcasted and the satellites to be broadcasted are GNSS navigation satellites, including at least one of GPS, BDS, Galileo, GLONASS, or other low-Earth orbit navigation augmentation satellite systems. Step S1 specifically includes the following sub-steps:

[0032] Step S11: Establish the broadcast satellite set Collect the identifiers and spatial coordinates of all broadcasting satellites available for transmitting precision corrections, and initialize the remaining broadcasting capacity of each broadcasting satellite. The initial value is equal to its preset maximum broadcasting capacity.

[0033] Step S12: Establish the set of satellites to be broadcast Collect all satellites that need to be broadcast with precise corrections, including the satellite identifiers and their spatial coordinates.

[0034] Step S13: Establish a global user grid set Based on a preset adaptive resolution grid strategy, globally discrete user evaluation points are generated. Specifically, in the low-to-mid latitude region [-75°, 75°], a latitude-longitude interval of 10°×10° or denser (i.e., less than or equal to 10°) is used; in the high-latitude region [-85°, -75°] and [75°, 85°], the longitude interval is increased to 30° or denser (i.e., less than or equal to 30°), while the latitude interval remains at 10° or denser; no evaluation points are set in polar regions. Each user grid point is output. The three-dimensional spatial coordinates.

[0035] Step S14, Obtain the satellite coordinate set: Based on the precise ephemeris file, interpolate to obtain all broadcasting satellites at the current epoch. and all satellites to be broadcast The coordinates of the Earth-centered Earth-fixed system.

[0036] Step S15: Establish the allocation identifier set Define a two-dimensional identifier variable. Among them, i index broadcasts satellites. j indexes satellites to be broadcast .when The time indicates the broadcast of satellites Satellites to be broadcast will be released. The correction number; when The time indicates no broadcast. Initialize all .

[0037] Step S2 involves calculating the two-way visibility relationship between user grid points and broadcasting satellites and satellites to be broadcasted, forming a user-satellite two-way visibility matrix. This specifically includes the following steps:

[0038] Step S21, for the current user grid point This allows us to obtain the satellite's three-dimensional spatial coordinates, as well as the spatial position coordinates of all satellites at the same epoch. All satellites include both broadcasting satellites and satellites awaiting broadcast.

[0039] Step S22, calculate user grid points With each satellite Elevation angle between The specific calculation method is as follows: First, calculate the line-of-sight vector in the geocentric coordinate system based on the user's grid point coordinates and satellite coordinates, then transform it to the user's station-centered coordinate system. Next, calculate the angle between the line-of-sight vector and the horizontal plane, i.e., the elevation angle. .

[0040] Step S23, based on user grid points and satellite Elevation angle between Determine the visibility relationship between the two entities and generate corresponding visibility identifiers based on this relationship. The criteria for determining the visibility relationship are: if the elevation angle... Set a threshold (e.g., 5°) to determine the user's grid points. Observable satellites Record visual signage Otherwise, determine the user's grid point. Unable to observe satellites Record visual signage .

[0041] Step S24: Traverse all user grid points and all satellites, based on the visibility identifiers of each user grid point and each satellite. Generate a user-satellite two-way visual relationship matrix In this matrix, rows correspond to different users, and columns correspond to different satellites (broadcasting satellites are arranged first, followed by satellites to be broadcast). Matrix elements Indicates user grid points With satellite The visibility. Understandably, the final output is a user-satellite two-way visibility matrix. This will serve as the basis for input data in subsequent steps.

[0042] Step S3, performing initial allocation based on the user-satellite bidirectional visibility matrix, includes: maximizing the number of users who co-see the broadcasting satellite and the satellite to be broadcast, and allocating each satellite to be broadcast to be broadcast by at least one broadcasting satellite.

[0043] Step S3 aims to perform initial satellite selection and broadcast allocation. The goal of this stage is to ensure that the correction information for each satellite to be broadcast is broadcast by at least one broadcasting satellite. First, all satellites to be broadcast are sequentially traversed. For each satellite, under the premise of meeting capacity constraints, the broadcasting satellite that can simultaneously see the most users is selected as the broadcasting payload, thereby maximizing the potential coverage of a single satellite's correction information. After this stage, all correction information has been broadcast, but user coverage may not be optimal. Step S3 specifically includes the following steps:

[0044] Step S31, in the set of satellites to be broadcast Traverse all satellites to be broadcast For any satellite to be broadcast In a broadcasting satellite set that has not reached its broadcasting capacity limit In the middle, it traverses all broadcasting satellites with broadcasting capacity. .

[0045] Step S32, calculate the satellites to be broadcast. With each broadcasting satellite having broadcasting capacity Number of users who share the same view and ,in, Indicates satellites to be broadcast and broadcasting satellites The number of users who view each other's content For use in determining user grid points The broadcasting satellite can be observed Visible signage, For use in determining user grid points Satellites to be broadcast can be observed The visual signage. Understandably, and This means that the broadcasting satellite can be observed simultaneously. and satellites to be broadcast User grid points.

[0046] Step S33: Select satellites that match the satellite to be broadcast. Broadcasting satellite with the largest number of concurrent viewers Update and broadcast satellites Used broadcast capacity (satellites to be broadcast soon) (Increase the used broadcast capacity by 1), and add the satellite to be broadcast to the broadcast list of the broadcast satellites (i.e., set...). This indicates that the satellite is being broadcast. Satellites to be broadcast will be released. (Correction numbers). Furthermore, if satellite broadcasting... If the used broadcast capacity of a satellite reaches the preset broadcast capacity (i.e., the broadcast capacity is full), then it will be removed from the set of satellites that still have broadcast capacity. Removed from the middle.

[0047] Step S34: Repeat steps S31 to S33 until all satellites to be broadcast have been cycled through, and obtain a preliminary broadcast list for each broadcast satellite.

[0048] Step S4: Based on the initial allocation results, diagnose the coverage gap of each satellite to be broadcast, and achieve iterative optimization allocation by maximizing the common coverage gain between the satellite to be broadcast and the broadcasting satellite.

[0049] It should be noted that "missing satellites" refers to satellites that have not been broadcast by any broadcasting satellite, thus lacking correction data. Understandably, the Earth coverage range of a broadcasting satellite and a satellite to be broadcast differs; one satellite to be broadcast typically requires multiple broadcasting satellites to fully cover its coverage area. Although step S3 has already selected broadcasting satellites with the maximum number of users sharing the same field of view with each satellite to be broadcast for correction data broadcasting, there are still some user grid points that can only observe the satellite to be broadcast but not the broadcasting satellite (i.e., user grid points not covered by the satellite to be broadcast). These uncovered user grid points need to rely on other broadcasting satellites for coverage.

[0050] Step S4 aims to perform iterative coverage optimization through satellite selection. This stage involves iterative optimization, with the goal of utilizing remaining idle broadcast capacity to fill in gaps in satellite coverage and maximize the number of users with full coverage. Each iteration specifically includes the following steps:

[0051] Step S41, Coverage Diagnosis: Based on the initial allocation in the previous stage, traverse all user grid points. Calculate each user grid point Missing satellite list But it was not detected by any satellite. broadcast And establish a global set of missing satellites. .

[0052] Step S42, search for the optimal operation:

[0053] (1) In the global missing satellite set Traversing missing satellites Find all currently visible missing satellites. user set .

[0054] (2) Traverse the missing satellites that have broadcast capacity but have not broadcast the aforementioned satellites. broadcasting satellite and The calculation will include the missing satellites. Join the broadcasting satellite The common coverage gain (i.e., the number of new users covered) that a broadcast list can bring. Originally unable to receive missing satellites The correction number, but It can receive signals broadcast by satellite. Missing satellite broadcast number of corrections .

[0055] Step S43, Judgment and Execution:

[0056] (1) In all possible pairings ( , In the options, select the number of new users to cover. The largest pair of execution assignments, if multiple identical maximum gains exist, can be chosen by choice.

[0057] (2) Gain threshold judgment: if the maximum number of newly covered users is... If the value is greater than 0, then the allocation will be executed during satellite broadcasting. Add the missing satellite to the broadcast list (i.e., setting) ), and update the broadcast satellite The used broadcast capacity. If broadcasting satellites... If the broadcasting capacity of a satellite is full, it will be removed from the set of satellites that still have broadcasting capacity. Removed from the list. Subsequently, the missing satellite set for all relevant users was updated. and global missing satellite set .

[0058] Step S44, Termination Judgment: Repeat steps S41~S43. The optimization process terminates when any of the following preset termination conditions are met, resulting in an optimized broadcast list for each broadcasting satellite:

[0059] (1) Global missing satellite set It is an empty set.

[0060] (2) A collection of satellites with remaining broadcasting capacity It is an empty set.

[0061] (3) Maximum number of new users covered A value of 0 (meaning no positive co-sight coverage gain can be obtained) indicates that it is impossible to improve the coverage status of any user through a single allocation operation.

[0062] (4) The number of iterations reaches the preset limit to prevent getting stuck in an excessively long loop in extreme cases.

[0063] Step S5: Based on the iterative optimization allocation results, and combined with the number of visible user coverage, select satellites to be broadcast to fill the remaining capacity, and then determine the broadcast instruction list for each broadcast satellite.

[0064] Step S5 aims to fill remaining capacity and enhance broadcast diversity. That is, after achieving a local optimum in step S4, if there is still remaining capacity for broadcast satellites, high-value satellites with extensive visible user coverage are prioritized for filling remaining capacity, with the goal of enhancing system robustness. This achieves the goal of increasing broadcast redundancy paths by utilizing idle broadcast capacity. The specific steps are as follows:

[0065] Step S51: Traverse the assigned satellites to be broadcast. ,calculate Based on total visible users Sort in descending order to obtain the most valuable satellites currently available for broadcast to the most visible users.

[0066] Step S52, targeting the high-value satellites with the most current visual user coverage. The system traverses high-value satellites that still have broadcasting capacity but have not yet been broadcast. broadcasting satellite and Calculations will include high-value satellites awaiting broadcast. Join the broadcasting satellite The number of new users that a playlist can bring. Originally unable to receive high-value satellites awaiting broadcast. The correction number, but It can receive signals broadcast by satellite. Broadcasting high-value satellites awaiting broadcast number of corrections .

[0067] Step S53, in all possible pairings ( , In the options, select the number of new users to cover. The largest pair. If the maximum number of newly covered users... Then the allocation will be executed during satellite broadcasting. Add the aforementioned high-value satellite to the broadcast list. (i.e., setting) ), and update the broadcast satellite The used broadcast capacity. If broadcasting satellites... If the capacity is full, it will be removed from the set of satellites that still have broadcasting capacity. Removed from the middle.

[0068] Step S54: Repeat steps S51-S53 until there is no remaining broadcast capacity or positive common-view coverage gain cannot be obtained, thus obtaining a broadcast instruction list for each broadcasting satellite. Specifically, following the order in step S51, attempt to redistribute the correction values ​​of these high-value satellites to other broadcasting satellites that still have capacity and can serve the new user group. This operation increases the broadcast redundancy path for critical correction value information without reducing the already achieved coverage level.

[0069] Step S6: Based on the broadcast instruction list and the user-satellite two-way visibility matrix, simulate the set of corrected data messages actually received by global users.

[0070] In step S6, the broadcast instruction list and the user-satellite two-way visibility matrix are received to simulate the actual data reception of each user grid point globally at each simulation epoch. The simulation process determines the set of corrected satellite messages that a user can receive based on the set of broadcasting satellites visible to the user.

[0071] In some feasible embodiments, to facilitate the evaluation of broadcast performance, step S6 further includes:

[0072] By comparing the set of satellites to be broadcast that should be visible to each user grid point with the actual set of corrected satellite messages received, various core performance indicators are calculated. The calculation method for these core performance indicators is as follows:

[0073] (1) Satellite loss rate: For a given user grid point, the collection of satellite correction messages broadcast from all visible broadcasting satellites is as follows: The actual visible collection of satellites to be broadcast is ,like The satellite loss rate is then defined as: .

[0074] (2) Epoch Loss Rate: For a given user grid point, the number of epochs with a satellite loss rate of 0 over a period of time is _____. The total number of observed epochs is The epoch loss rate is: .

[0075] (3) System complete coverage: For time t, the number of users with a satellite loss rate of 0 is The number of users worldwide is The system's complete coverage rate is: , characterizing the global instantaneous coverage performance of epoch t.

[0076] Please refer to the appendix for details. Figure 2 Based on the same technical concept as the aforementioned embodiments, this invention also provides a satellite-based high-precision positioning enhancement message selection and broadcasting system based on a greedy algorithm. This system is data-driven at its core, and through standardized interfaces, it enables the collaborative work of three functional units: data preprocessing, intelligent decision-making, and simulation evaluation, forming a closed-loop optimization process of "input-decision-evaluation-feedback".

[0077] Data Receiving Unit. This unit is responsible for injecting, parsing, and modeling raw data, providing structured data support for subsequent decision-making and evaluation. Its specific functions include:

[0078] (1) Ephemeris Data Processing Module: Reads standard format precision ephemeris files (such as SP3) or broadcast ephemeris files or other files containing satellite coordinate time series, parses and interpolates to generate high-precision spatial position information of satellite systems such as BDS, GPS, and GAL at each simulation epoch, forming standardized satellite orbit coordinate data.

[0079] (2) User Grid Modeling Module: Based on preset adaptive resolution rules, it automatically generates global discrete user evaluation points. For example, a grid resolution of 10°×10° is used in the mid-to-low latitude region [-75°, 75°]; a longitude interval of 15° is used in the high latitude region [-85°, -75°] and [75°, 85°], while the latitude interval remains at 10°; and no evaluation points are set in the polar regions, thus effectively controlling the computational complexity while ensuring evaluation accuracy. The unit outputs the three-dimensional spatial coordinates of each user grid point.

[0080] (3) Visibility Relationship Calculation Module: Based on the spatial geometric relationship between the satellite and the user, calculate and generate a two-way visibility relationship matrix between the user and the satellite at each epoch. This matrix calculates the elevation angle between the satellite and the user and judges the visibility based on a preset cutoff elevation angle (e.g., 5°), which serves as the core input for subsequent optimization decisions.

[0081] Star Selection Decision Unit. As the intelligent core of this system, this unit receives the visibility relationship matrix and preset broadcast capacity parameters from the preprocessing unit, executes the multi-stage greedy optimization algorithm, and generates the optimal broadcast instruction list.

[0082] Its internal logic strictly follows a three-stage process and encapsulates the corresponding core decision-making modules:

[0083] (1) Initial Allocation Module. This module prioritizes ensuring that all satellites to be broadcast are broadcast by at least one satellite. It sequentially traverses the satellites to be broadcast and selects the satellite that can form the largest common visual user group with each satellite as its broadcasting satellite. The output of this module is an initial allocation scheme that meets the basic broadcast coverage requirements.

[0084] (2) Iterative Optimization Module. This module performs iterative optimization with the goal of maximizing user coverage. It identifies coverage gaps under the current allocation scheme through coverage diagnostics, identifying which users cannot receive certain visible correction information, and then constructs a global set of missing satellites. Subsequently, it performs an optimal operation search, traversing all possible combinations of missing satellites and satellites with available capacity, and uses coverage gain evaluation logic to accurately calculate the number of new covered users that can be added after allocating a missing satellite to another satellite. Based on the principle of local optima, the module selects the missing satellite-broadcasting satellite pair with the largest number of newly covered users for allocation and updates the system state. This process iterates until user coverage cannot be further improved through a single allocation (i.e., the maximum number of newly covered users is 0), all satellites are allocated, or the remaining broadcasting capacity is exhausted.

[0085] (3) Redundancy Enhancement Module. After achieving local optimal coverage, if there are still satellites with available capacity, this module initiates a filling process aimed at enhancing system robustness. It sorts the allocated satellites in descending order based on the total number of visible users, prioritizing the search for a second broadcast path for correction information that covers a wider user base. The module iterates through all combinations of high-value satellites and satellites with available capacity, selecting the combination that will bring the maximum number of newly covered users for allocation. This increases the broadcast redundancy of critical information without reducing the existing coverage rate, thereby improving the system's fault tolerance.

[0086] This unit ultimately outputs a structured list of broadcast instructions, clearly indicating the list of satellites that each broadcasting satellite needs to broadcast at each epoch.

[0087] Broadcast Evaluation Unit. This unit is responsible for performing closed-loop simulation verification and multi-dimensional performance evaluation of the broadcast scheme output by the satellite selection decision unit, forming a "decision-evaluation" feedback loop. Its specific functions include:

[0088] (1) Data reception simulation module: Receives the broadcast instruction list and visibility relation matrix, and simulates the actual data reception of each user grid point in the world at each simulation epoch. The simulation process determines the set of corrected data messages that can be received by the user based on the set of broadcasting satellites visible to the user.

[0089] (2) Coverage performance analysis module: By comparing the set of satellites that each user should be able to see with the set of corrected data messages actually received, the core performance indicators are calculated:

[0090] a. Satellite Loss Rate: Calculates the percentage of visible satellites that a single user has failed to receive in the current epoch.

[0091] b. Era Loss Rate: The percentage of epochs in which a single user has a satellite loss rate of 0 over a period of time.

[0092] c. System complete coverage rate: Calculated as the proportion of users with a satellite loss rate of 0 in the current epoch to the total number of global users, used to characterize the instantaneous global coverage performance of the system.

[0093] (3) Results Visualization Export Module: Transforms quantitative analysis results into intuitive charts, such as trend curves of performance changes with broadcast capacity and geographic heat maps of global coverage performance. At the same time, it supports the export of raw evaluation data, providing direct data basis for system parameter optimization and scheme comparison.

[0094] This system employs a pipelined workflow combining sequential and feedback mechanisms. The data receiving unit, acting as the starting point, streams processed satellite ephemeris, user grid, and visibility relationship data to the satellite selection decision unit. Based on this data, the decision unit runs the core optimization algorithm, generates a broadcast plan, and sends it to the broadcast evaluation unit. The evaluation unit independently simulates and evaluates the data using the raw data output from the preprocessing unit and the plan output from the decision unit, ultimately producing a coverage performance analysis report. This evaluation result can guide grid strategy adjustments in the data preprocessing unit or be directly fed back to the decision unit for algorithm parameter tuning, thus achieving closed-loop optimization of the system. This modular design allows for independent iteration and replacement of algorithm strategies, data sources, and evaluation methods, significantly improving the system's scalability and maintainability.

[0095] In summary, the present invention relates to the field of satellite navigation enhancement technology, specifically to a satellite selection and broadcasting method and system for broadcasting high-precision correction information of a Global Navigation Satellite System (GNSS), and more particularly to a method and system for optimizing broadcasting strategies based on a greedy algorithm to maximize global user coverage performance. The method includes: acquiring the set of GNSS satellites to be broadcast precision messages and the set of GNSS satellites available for satellite-based broadcasting; calculating the two-way visibility matrix between all user grid points and all satellites; performing initial allocation using a greedy algorithm, maximizing the number of users with shared visibility between broadcasting satellites and satellites to be broadcasted, and allocating each satellite to be broadcast to at least one satellite; performing optimized allocation using a greedy algorithm based on the initial allocation scheme, diagnosing the coverage gap of each satellite to be broadcasted, calculating its shared visibility coverage gain with broadcasting satellites with available capacity, and iteratively optimizing the allocation by selecting the maximum gain; performing remaining capacity filling, adding redundant broadcasting paths for high-value satellites to be broadcasted in the remaining idle broadcasting capacity, and determining the final broadcast list on each broadcasting satellite; simulating the set of corrected messages actually received by global users based on the broadcasting instruction list and the visibility relationship between users and satellites, and calculating indicators such as satellite loss rate, epoch loss rate, and system complete coverage rate to achieve a quantitative evaluation of broadcasting coverage performance. The system includes: a data receiving unit, a satellite selection decision unit, and a broadcasting evaluation unit.

[0096] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A satellite-based high-precision positioning enhancement message selection and broadcasting method based on a greedy algorithm, characterized in that, include: Obtain the set of satellites to be broadcast and the set of satellites with broadcasting capacity, and simulate the establishment of a global user grid set; Calculate the two-way visibility relationship between user grid points and broadcasting satellites and satellites to be broadcasted, and form a user-satellite two-way visibility relationship matrix; The initial allocation is performed based on the user-satellite bidirectional visibility matrix, including: maximizing the number of users who share the same view with the broadcasting satellite and the satellite to be broadcast, and allocating each satellite to be broadcast to be broadcast by at least one broadcasting satellite; specifically including: selecting the broadcasting satellite that has the maximum number of users who share the same view with the satellite to be broadcast, updating the used broadcasting capacity of the broadcasting satellite, and adding the satellite to be broadcast to its broadcasting list; Based on the initial allocation results, the coverage gap of each satellite to be broadcast is diagnosed, and the allocation is iteratively optimized by maximizing the common-view coverage gain between the satellites to be broadcast and the broadcasting satellites; specifically, this includes: in all possible pairings ( , In the process, select the pair with the largest number of newly covered users to perform the allocation. If there are multiple pairs with the same maximum gain, you can choose any one of them. In order to broadcast satellites, Missing satellites; Gain threshold determination: if the maximum number of newly covered users is... If the value is greater than 0, then the allocation is performed, the missing satellite is added to the broadcast list of broadcast satellites, and the used broadcast capacity of the broadcast satellites is updated; if the broadcast capacity of the broadcast satellite is full, then it is removed from the set of satellites with remaining broadcast capacity; subsequently, the missing satellite sets of all relevant users and the global missing satellite set are updated. Based on the iterative optimization allocation results, satellites to be broadcast are selected to fill the remaining capacity in combination with the number of visible users, thereby determining the broadcast instruction list for each broadcast satellite; specifically, this includes: traversing the allocated satellites to be broadcast in descending order of the total number of visible users to obtain the high-value satellites to be broadcast with the most current visible user coverage; Based on the broadcast instruction list and the user-satellite two-way visibility matrix, simulate the set of satellite correction messages actually received by global users.

2. The satellite-based high-precision positioning enhancement message selection and broadcasting method based on a greedy algorithm as described in claim 1, characterized in that, Calculate the two-way visibility relationship between user grid points and broadcasting satellites and satellites to be broadcasted, forming a user-satellite two-way visibility matrix, including: Obtain the spatial location coordinates of all user grid points and all satellites at the same epoch; the satellites include broadcasting satellites and satellites to be broadcasted. Based on the spatial coordinates of the user grid points and the satellites, calculate the elevation angle between each user grid point and each satellite. The visibility relationship between user grid points and satellites is determined based on their elevation angle, and corresponding visibility markers are generated based on this relationship. Traverse all user grid points and all satellites, and generate a user-satellite two-way visibility relationship matrix based on the visibility identifiers of each user grid point and each satellite.

3. The satellite-based high-precision positioning enhancement message selection and broadcasting method based on a greedy algorithm as described in claim 2, characterized in that, The criteria for determining the visibility relationship are as follows: when the elevation angle between the user grid point and the satellite is greater than a set threshold, the user grid point is determined to be able to observe the satellite; otherwise, the user grid point is determined to be unable to observe the satellite.

4. The satellite-based high-precision positioning enhancement message selection and broadcasting method based on a greedy algorithm as described in claim 1, characterized in that, By maximizing the number of users viewing both the broadcasting satellite and the satellite to be broadcast, each satellite to be broadcast is allocated to be broadcast by at least one broadcasting satellite, including: For any satellite to be broadcast, calculate the number of users who share the same view between the satellite to be broadcast and each broadcasting satellite with broadcasting capacity. Select the broadcasting satellite that has the largest number of users who can see the same satellite as the satellite to be broadcasted, update the used broadcasting capacity of the broadcasting satellite, and add the satellite to be broadcasted to its broadcasting list; Repeat the above steps until all satellites to be broadcast have been cycled through, resulting in a preliminary broadcast list for each satellite.

5. The satellite-based high-precision positioning enhancement message selection and broadcasting method based on a greedy algorithm as described in claim 1, characterized in that, Diagnose the coverage gaps of each satellite to be broadcast and iteratively optimize the allocation by maximizing the shared coverage gain between the satellites to be broadcast and the broadcasting satellites, including: Iterate through all user grid points, diagnose the missing satellites for each user grid point, and construct a global set of missing satellites. For each missing satellite, calculate the common-view coverage gain resulting from allocating the missing satellite to each broadcasting satellite with broadcasting capacity that has not broadcasted the missing satellite. Select the broadcasting satellite with the maximum common-view coverage gain, update the used broadcasting capacity of the broadcasting satellite, and add the missing satellite to its broadcasting list; Repeat the above steps until positive common-view coverage gain cannot be obtained, the global missing satellite set is empty, there is no available broadcast capacity, or the maximum number of iterations is reached, to obtain the optimized broadcast list for each broadcast satellite.

6. The satellite-based high-precision positioning enhancement message selection and broadcasting method based on a greedy algorithm as described in claim 1, characterized in that, Based on the number of visible user coverage, satellites to be broadcast are selected to fill the remaining capacity, thereby determining the broadcast instruction list for each broadcast satellite, including: The allocated satellites to be broadcast are traversed in descending order of total visible users to obtain the high-value satellites to be broadcast with the most current visible user coverage. Find broadcasting satellites with broadcasting capacity that have not yet broadcasted the high-value satellites to be broadcasted, and calculate the common view coverage gain brought about by allocating the high-value satellites to each of the broadcasting satellites; Select the broadcasting satellite with the maximum common-view coverage gain, update the used broadcasting capacity of the broadcasting satellite, and add the high-value satellite to be broadcast to its broadcasting list; Repeat the above steps until there is no remaining broadcast capacity or no positive common-view coverage gain can be obtained, to obtain a broadcast instruction list for each broadcasting satellite.

7. The satellite-based high-precision positioning enhancement message selection and broadcasting method based on a greedy algorithm as described in claim 1, characterized in that, The global user grid set is established using an adaptive resolution grid strategy, including: In low and mid-latitude regions, a latitude and longitude interval of less than or equal to 10° is used; in high-latitude regions, a longitude interval of less than or equal to 30° is used, while maintaining a close latitude interval of less than or equal to 10°; no evaluation points are set in polar regions.

8. The satellite-based high-precision positioning enhancement message selection and broadcasting method based on a greedy algorithm as described in claim 1, characterized in that, The method further includes: The core performance indicators are calculated by comparing the set of satellites to be broadcast that are visible to each user grid point with the set of corrected satellite messages actually received.

9. A satellite-based high-precision positioning enhancement message selection and broadcasting system based on a greedy algorithm, characterized in that, The method is implemented using a satellite-based high-precision positioning enhancement message selection and broadcasting method based on a greedy algorithm as described in any one of claims 1 to 8, comprising: The ephemeris data processing module is used to obtain the set of satellites to be broadcast and the set of satellites with broadcasting capacity; The user grid modeling module is used to simulate the creation of a global user grid set. The visibility relationship calculation module is used to calculate the two-way visibility relationship between user grid points and broadcasting satellites and satellites to be broadcasted, forming a user-satellite two-way visibility relationship matrix; The initial allocation module is used to perform initial allocation based on the user-satellite bidirectional visibility relationship matrix, including: by maximizing the number of users who co-see the broadcasting satellite and the satellite to be broadcasted, allocating each satellite to be broadcast to be broadcast by at least one broadcasting satellite; The iterative optimization module is used to diagnose the coverage gap of each satellite to be broadcast based on the initial allocation results, and to achieve iterative optimization allocation by maximizing the common-view coverage gain between the satellites to be broadcast and the broadcasting satellites; The redundancy enhancement module is used to select satellites to be broadcast based on the iterative optimization allocation results and the number of visible user coverages to fill the remaining capacity, thereby determining the broadcast instruction list for each broadcast satellite. The data receiving simulation module is used to simulate the set of corrected satellite messages actually received by global users based on the broadcast instruction list and the user-satellite two-way visibility matrix.

10. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores computer instructions that cause the computer to execute the satellite-based high-precision positioning enhancement message selection and broadcasting method based on a greedy algorithm as described in any one of claims 1 to 8.

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