Low-altitude aircraft air collision early warning method, device, equipment and medium

Abstract

The application provides a low-altitude aircraft in-air collision early warning method, device, equipment and medium. The method comprises collecting aircraft state information sequences of all aircrafts, the state information at least comprising three-dimensional position, flight speed and flight direction, and performing preprocessing, completing time synchronization calibration and unified coordinate system, and determining the confidence of three-dimensional position and flight speed according to the communication parameter confidence of the information collection equipment; according to a preset grid dynamic division rule, the airspace under the corresponding flight scene is dynamically gridded, and all aircraft state information is mapped to the corresponding grid; the real-time state information of the aircrafts in the same grid and adjacent grid is determined, the flight trajectory of the aircrafts in the future time is predicted by using a linear extrapolation method, and the predicted trajectory is error corrected through the confidence of the aircraft position and flight speed, so as to determine the closest meeting distance between the aircrafts, predict the collision time, and determine the collision risk.

Description

Technical Field

[0001] This invention relates to the field of low-altitude airspace flight safety and intelligent early warning, and in particular to a method, device, equipment and medium for early warning of collisions between low-altitude aircraft and other objects. Background Technology

[0002] With the rapid development of the low-altitude economy, the application scenarios of low-altitude aircraft such as drones and eVTOLs are becoming increasingly widespread. The number of aircraft in the 0-500 meter low-altitude airspace has increased significantly, and the characteristics of high-density, distributed, and random trajectories are becoming increasingly prominent, leading to a sharp increase in the risk of flight collisions and seriously threatening low-altitude flight safety. Existing collision warning technologies have obvious limitations and cannot meet the safety management needs of a large number of low-altitude aircraft. Specifically: existing low-altitude aircraft collision warning systems mostly use visual systems, which are affected by factors such as ambient light and obstruction, resulting in limited detection range and insufficient accuracy, and cannot achieve simultaneous management of multiple aircraft; civil aviation aircraft collision avoidance systems rely on airborne TACS transponder systems, which require aircraft to carry dedicated transponder equipment, resulting in high costs and poor adaptability, and cannot be applied to various small low-altitude aircraft or "black flight" targets. Therefore, neither of these existing systems can be widely promoted and applied.

[0003] The most similar existing solutions fall into two main categories: one is low-altitude aircraft collision warning based on vision systems, which uses cameras to collect aircraft image information, identify the aircraft's position, and assess the collision risk; the other is the civil aviation airborne TACS (Transponder Collision Avoidance System), which uses onboard transponders to exchange position information to achieve collision avoidance between civil aircraft. However, this system has the following problems: 1) Existing systems have poor adaptability and cannot be applied on a large scale; visual system solutions are affected by environmental factors such as lighting and occlusion, resulting in low detection accuracy and limited control range, and cannot achieve simultaneous early warning for multiple aircraft; civil aircraft collision avoidance relies on airborne TACS transponder systems, which require aircraft to be equipped with dedicated transponder equipment, resulting in high costs and incompatibility with low-altitude small aircraft and "black flight" targets. Neither type of system can be widely promoted and applied.

[0004] 2) Insufficient accuracy in acquiring status information and lack of quantification of measurement uncertainty; existing vision system solutions acquire low accuracy in acquiring aircraft status information and are susceptible to environmental interference leading to data distortion; although the airborne TACS response system has high accuracy, its coverage is limited and it does not consider the inaccuracy of positioning and speed measurements, lacking quantification of data reliability, all of which can easily lead to false or missed warnings.

[0005] 3) The early warning coverage is not comprehensive and there are blind spots in control; the visual system is limited by the detection range and there are obvious blind spots in control; the airborne TACS transponder system cannot cover "black flight" aircraft without transponder equipment. Neither of the two solutions can achieve full-area early warning coverage for low-altitude aircraft, making it difficult to ensure overall flight safety.

[0006] 4) Collision prediction efficiency is low and does not support large-scale targets. Existing solutions are mostly autonomous early warning at the aircraft end or local early warning by a single vision device. They do not adopt a centralized ground control mode, and cannot perform unified collision calculations for a large number of airborne aircraft. The calculation efficiency is low, the real-time performance is poor, and it cannot support synchronous early warning of large-scale, high-density airborne aircraft at low altitudes.

[0007] In view of this, there is an urgent need to provide an air collision warning method that can achieve accurate, real-time, and early warning of collision risks, take into account both compliance and the goal of "unauthorized flights", solve the problem that existing systems cannot be applied on a large scale, and ensure the safety of low-altitude flights. Summary of the Invention

[0008] To overcome the problems existing in the related technologies, this disclosure provides a method, device, equipment and medium for early warning of collisions between low-altitude aircraft and other objects, so as to solve the technical problems in the related technologies.

[0009] This specification provides one or more embodiments of a low-altitude aircraft in-flight collision warning method, including the following steps: Collect the sequence of aircraft status information for all aircraft. The status information includes at least three-dimensional position, flight speed and flight direction. After preprocessing, complete time synchronization calibration and coordinate system unification. Determine the confidence level of three-dimensional position and flight speed based on the confidence level of communication parameters of the information acquisition equipment. Based on the airspace range, flight scenario, and aircraft operation density, the corresponding preset grid dynamic division rules are determined, the airspace under the corresponding flight scenario is dynamically gridded, and all aircraft status information is mapped to the corresponding grid. The real-time status information of aircraft in the same and adjacent grids is determined, and the flight trajectory of the aircraft in the future time is predicted by linear extrapolation. Then, the predicted trajectory is corrected by the confidence of the aircraft position and flight speed to determine the nearest encounter distance between aircraft, predict the collision time, and determine the collision risk.

[0010] This specification provides one or more embodiments of a low-altitude aircraft in-flight collision warning device, comprising: The status information acquisition and processing module is used to acquire the sequence of aircraft status information of all aircraft. The status data includes at least three-dimensional position, flight speed and flight direction. After preprocessing, time synchronization calibration and unified coordinate system are completed. The confidence level of three-dimensional position and flight speed is determined according to the confidence level of communication parameters of information acquisition equipment. The airspace gridding module is used to determine the corresponding preset grid dynamic division rules based on the airspace range, flight scenario and aircraft operation density, dynamically grid the airspace under the corresponding flight scenario, and map all aircraft status information to the corresponding grid. The collision risk prediction module is used to determine the real-time status information of aircraft in the same grid and adjacent grids. It uses linear extrapolation to predict the flight trajectory of aircraft in the future. Then, it corrects the error of the predicted trajectory by the confidence level of the aircraft's position and flight speed to determine the nearest encounter distance between aircraft, predict the collision time, and determine the collision risk.

[0011] This specification provides one or more embodiments of a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the low-altitude aircraft in-flight collision warning method as described above.

[0012] This specification provides one or more embodiments of a computer-readable storage medium storing a computer program that, when executed by a processor, implements the low-altitude aircraft in-flight collision warning method as described above.

[0013] This disclosure provides a method, device, equipment, and medium for low-altitude vehicle collision early warning. Its advantages lie in the following: the system collects vehicle status data, preprocesses and optimizes the raw data, outputting not only core status information such as vehicle identity, position, and speed, but also quantifying the confidence levels of position and speed, accurately reflecting measurement inaccuracies, and providing reliable data support for centralized ground-based collision calculations. It also considers the status awareness of compliant and "black flight" targets, requires no dedicated equipment on the vehicle, is not limited by environmental factors, and can be widely applied, solving the core problem that existing systems cannot be used on a large scale. The system uses an equidistant grid method to dynamically divide the low-altitude airspace, with the grid size adaptable to the density of aircraft operations. Local collision prediction is achieved through "grid-vehicle" correlation. The system only calculates the collision risk of aircraft within a local grid, transforming global pairwise detection into local grid-based detection, significantly reducing computational load. This fundamentally solves the real-time early warning problem for large-scale airborne vehicles, further supporting the large-scale application of the system. It also takes into account the inaccuracies in the measurement of aircraft positioning and speed to implement corrective flight trajectory prediction, thereby accurately determining the collision risk between aircraft, ensuring the real-time nature and effectiveness of early warning, and adapting to the long-term operation needs of large-scale aircraft. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in one or more embodiments of this specification or in 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 only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 A flowchart illustrating a low-altitude vehicle in-flight collision warning method provided for one or more embodiments of this specification; Figure 2 A block diagram of a low-altitude aircraft in-flight collision warning device provided for one or more embodiments of this specification; Figure 3 This is a schematic diagram of the structure of a computer device provided for one or more embodiments of this specification. Detailed Implementation

[0016] To enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of this invention.

[0017] This invention relies on a ground control system to acquire real-time status information such as the identity, position, and speed of low-altitude aircraft. Combined with grid partitioning technology, it achieves large-scale aircraft collision risk prediction and sets scientific warning thresholds and early warning mechanisms to ensure the flight safety of low-altitude aircraft. This invention is a ground-based collision avoidance system, distinct from existing visual warning systems for low-altitude aircraft and airborne TACS (Traffic Alternate Channel Collision Avoidance System) for civil aviation aircraft. It effectively solves the problem of existing systems being unable to be applied on a large scale and is suitable for high-density operation scenarios of low-altitude aircraft such as UAVs and eVTOLs in the 0-500 meter low-altitude airspace. It falls within the technical scope of low-altitude flight safety protection and intelligent control. The invention will be described in detail below with reference to specific embodiments and accompanying drawings.

[0018] Method Implementation Examples According to embodiments of the present invention, a method for in-flight collision warning of low-altitude aircraft is provided, such as... Figure 1 The diagram shown is a flowchart of the low-altitude vehicle in-flight collision warning method, device, equipment, and medium provided in this embodiment. According to this embodiment, the low-altitude vehicle in-flight collision warning method, installed in a ground control system, is used to analyze and determine the collision risk of low-altitude airspace vehicles, and specifically includes the following steps: Step S1: Collect the sequence of aircraft status information for all aircraft. The status information includes at least three-dimensional position, flight speed and flight direction. After preprocessing, complete time synchronization calibration and coordinate system unification. Determine the confidence level of three-dimensional position and flight speed based on the confidence level of communication parameters of the information acquisition equipment.

[0019] Step S2: Based on the airspace range, flight scenario, and aircraft operating density, determine the corresponding preset grid dynamic division rules, dynamically grid the airspace under the corresponding flight scenario, and map all aircraft status information to the corresponding grid.

[0020] Step S3: Determine the real-time status information of aircraft in the same grid and adjacent grids, use linear extrapolation to predict the flight trajectory of aircraft in the future, and then correct the error of the predicted trajectory by the confidence of the aircraft position and flight speed to determine the nearest encounter distance between aircraft, predict the collision time, and determine the collision risk.

[0021] In this embodiment, the system collects aircraft status data, preprocesses and optimizes the raw data, and outputs not only core status information such as aircraft identity, position, and speed, but also quantifies the confidence levels of position and speed, accurately reflecting measurement inaccuracies and providing reliable data support for centralized ground-based collision calculations. It also considers compliance and the status awareness of "black flight" targets, requiring no dedicated equipment on the aircraft, is unaffected by environmental factors, and can be widely applied, solving the core problem of existing systems' inability to be used on a large scale. An equidistant grid method is used to dynamically divide the low-altitude airspace, with the grid size adaptable to the density of aircraft operations. Local collision prediction is achieved through "grid-aircraft" association. The system only calculates the collision risk of aircraft within a local grid, transforming global pairwise detection into local grid-based detection, significantly reducing computational load. This fundamentally solves the real-time warning problem for large-scale airborne aircraft, further supporting the large-scale application of the system. Simultaneously, the inaccuracies in aircraft positioning and speed measurement are considered to correct the predicted flight trajectory, thereby accurately determining the collision risk between aircraft, ensuring the real-time nature and effectiveness of the warning, and adapting to the long-term operational needs of large-scale aircraft.

[0022] In step S1 of this embodiment, the status information of all aircraft can be obtained in real time by receiving signals from low-altitude aircraft through a preset signal receiving module of the ground control system or ground detection equipment.

[0023] In one embodiment, the raw data of the acquired aircraft status information is preprocessed, including unifying the timestamp, the unified coordinate system (WGS84), and the data update frequency, removing outliers, filling in missing data, and completing time synchronization calibration. The system parses the data and outputs the core status information of each aircraft, including identity information, real-time three-dimensional position, flight speed, and flight direction. The identity information may include compliant aircraft registration information or "black flight" target identification. At the same time, the confidence level of position and speed is determined to quantify the inaccuracy of positioning and speed measurement, providing a reliable data foundation for centralized collision calculation of the ground control system.

[0024] This embodiment uses the 3σ principle to remove outliers from the aircraft's status information, as detailed below: Suppose that the state data sequence of a certain aircraft is as follows: Calculate the mean and standard deviation : ; ; Among them, if Then determine These are outliers and should be removed.

[0025] In one specific embodiment, the confidence levels of the positioning and velocity of each aircraft are determined based on the communication parameters of the information acquisition device. These communication parameters include the confidence levels of positioning device accuracy, signal strength, and data update frequency. The specific calculation of the confidence levels for three-dimensional position and flight velocity is as follows: ; in, For the confidence level of equipment accuracy. For signal strength confidence, To update the frequency confidence; The weights for each dimension and each communication parameter can be configured according to the actual scenario.

[0026] In this embodiment, since the flight scenarios of the aircraft may include urban core areas, suburbs, mountainous areas, etc., and the flight density of different scenarios is also different, this embodiment adapts and adjusts the grid division size in real time according to the flight scenario and the aircraft operation density to ensure that the calculation of invalid grids is reduced while taking into account the accuracy of local collision prediction, and supports the synchronous management and control of large-scale aircraft.

[0027] This embodiment determines the corresponding preset grid dynamic division rules based on the airspace range, flight scenario, and aircraft operation density. Specifically, the grid size is increased or decreased according to the flight scenario and aircraft operation density, or the grid is merged or split to achieve dynamic grid planning. For example, the grid size is set to 50m×50m in the urban core area where the aircraft density is high, and the grid size is set to 200m×200m in the suburbs where the aircraft density is low.

[0028] In one specific embodiment, the airspace can be divided into several independent grids according to equidistant latitude and longitude or planar coordinates using a grid method.

[0029] In this embodiment, for the gridded airspace, the ground control system maps the current status information of all aircraft to the current grid, realizing the construction of the "grid-aircraft" correlation, which lays the foundation for aircraft collision risk prediction. The following describes the process of constructing the "grid-aircraft" correlation using Cartesian coordinates as an example: The controlled airspace is defined as follows: , The grid side length is ,but: Number of grids: ,

[0030] aircraft The position is Its grid number is:

[0031] in, To round up, This is for rounding down.

[0032] To achieve dynamic airspace gridding, this embodiment also includes an airspace status monitoring and grid adjustment module. This module monitors the aircraft density in each grid and performs grid adjustments based on preset high and low aircraft density thresholds. The specific execution steps are as follows: Step A1: Obtain the original grid set, the number of aircraft in each grid, the density threshold, the basic grid side length, and create an empty new grid set NewGridSet; Step A2: Iterate through the number of aircraft in each grid. If the number of aircraft in the grid is greater than the density limit, proceed to step A3. If the number of aircraft in the grid is less than the density limit, proceed to step A4. If it is within the threshold range, do not perform any processing.

[0033] Step A3: Split the current grid according to a preset splitting rule; in a specific embodiment, the splitting rule may be to call a grid splitting function (e.g., the split_grid function) to evenly split the current grid into 4 equal-sized small grids, that is, small grids with a side length of L0 / 2, where L0 is the side length of the base grid.

[0034] Step A4: Merge the current grid with neighboring grids that have relatively fewer adjacent grids for the aircraft.

[0035] Step A5: Update the grid set.

[0036] In step S3 of this embodiment, the real-time status information of the aircraft in the same grid and adjacent grids is determined, and the flight trajectory of the aircraft in the future time is predicted by linear extrapolation. Then, the predicted trajectory is corrected for error by the confidence level of the aircraft's three-dimensional position and flight speed, as shown in the following formula: Set up an aircraft exist The three-dimensional position at time is Flight speed is Flight direction angle is ,but time( The original predicted location is: ; Combining location confidence Speed ​​confidence Perform prediction trajectory error correction, including correcting the predicted position and correcting the predicted position velocity; The corrected predicted location is as follows: ; in, This is the correction factor (default 1). This represents the maximum measurement error (determined by equipment performance).

[0037] The corrected prediction speed is as follows: ; in, The maximum allowable speed correction (which can be set based on acceleration limits or historical speed fluctuations). For velocity correction factor (which can be compared with position) (Same or independent adjustments).

[0038] In this embodiment, after error correction of the predicted trajectory, the closest encounter distance between the aircraft is calculated as follows: Set up an aircraft , The corrected predicted position is , Then at any time The spatial distance between the two aircraft is: ; right Differentiate and let Solving for the extreme points Then the predicted nearest encounter distance is: .

[0039] In this embodiment, when the system determines that an aircraft has a collision risk, it calculates the predicted collision time of the risky aircraft based on the corrected predicted trajectory. If the predicted collision time has a preset time threshold, the risk level is determined, and different levels of risk warnings are implemented to ensure that sufficient handling time is reserved. The ground control system pushes the aircraft's identity information, real-time status information, predicted collision location, predicted collision time, position and speed confidence level, and other information to the low-altitude control platform in a standardized structured data format. At the same time, it supports sending alarm commands to the airborne terminals of compliant aircraft.

[0040] Therefore, this embodiment also includes collision judgment and graded alarm steps. The collision time is determined based on the meeting distance between the two aircraft, and the risk level is determined based on the warning time threshold. Different levels of risk warnings are achieved. The control platform displays graded alarm information based on the collision risk level (combined with the nearest meeting distance and the predicted collision time), which facilitates rapid handling and obstacle avoidance by control personnel. The specific execution process is as follows.

[0041] Step B1, Calculation of predicted collision time: make Solve for the collision time The predicted collision time is: ; Step B2, Warning Trigger Determination: Let the warning time threshold be... (Default 20s), then: ; Risk level classification formula: Combined with the meeting distance and collision time The risk value is calculated using a weighted scoring method. And based on risk value Determine the current collision risk level, trigger the corresponding level alarm, and set the risk value. Calculate as follows: ; in, As weight; according to The values ​​are divided into the following 3 levels: Level 1 Alert (Extremely High Risk):

[0042] Level 2 Alert (Medium-High Risk):

[0043] Level 3 Alert (Low Risk): .

[0044] In this embodiment, the entire early warning process forms a closed loop. The ground control system updates the aircraft status data in real time, and the aircraft status and collision risk within the grid are continuously refreshed. If the aircraft adjusts its flight trajectory after the early warning, the ground control system recalculates and predicts the nearest encounter distance. If it is greater than the collision distance threshold, the early warning is automatically lifted, ensuring the real-time nature and effectiveness of the early warning.

[0045] The low-altitude vehicle in-flight collision warning method provided by this invention has the following beneficial effects: (1) It belongs to the ground collision avoidance system and can be applied on a large scale: Unlike the existing low-altitude aircraft visual warning system (which is greatly affected by ambient light and obstruction and cannot be controlled on a large scale) and the civil aviation airborne TACS response collision avoidance system (which depends on airborne equipment, is costly and has poor adaptability), the collision calculation is completed centrally by the ground control system. It does not require the aircraft to carry special equipment, is not limited by environmental factors, is compatible with various low-altitude aircraft, and can be promoted and applied on a large scale, solving the core pain points of the existing system.

[0046] (2) Accurate and comprehensive status information, taking into account measurement uncertainty: By centrally acquiring and preprocessing the aircraft status information through the ground control system, it can not only comprehensively acquire core status information such as aircraft identity, position, and speed, but also quantify the inaccuracy of positioning and speed measurement through confidence measurement, solve the problems of data distortion in existing vision systems and incomplete coverage of airborne TACS systems, provide reliable support for collision prediction, and at the same time take into account compliance and "black flight" targets, achieving full coverage.

[0047] (3) Adaptable to large-scale and high-density scenarios, with high real-time early warning: The airspace is divided by grid method. The ground control system only performs local collision prediction for aircraft in the same grid / adjacent grid, which greatly reduces the amount of computation. The computation efficiency increases linearly with the number of aircraft, which can support synchronous real-time early warning of large-scale and high-density aircraft in the air at low altitude, which meets the needs of low-altitude economic development.

[0048] (4) Collision judgment is scientific and reasonable, and the early warning accuracy is high: Combining the inaccuracy of positioning and speed measurement, the collision distance threshold is set as the closest encounter distance as the collision judgment threshold, which breaks through the limitations of traditional fixed distance judgment, reduces early warning misjudgment and missed judgment, and makes the collision risk judgment more in line with the actual low-altitude operation scenario, which is superior to the low-precision early warning of existing vision systems and the single judgment logic of airborne TACS systems.

[0049] (5) Closed-loop early warning is more intelligent and has strong adaptability to implementation: a closed-loop early warning system driven by ground control is constructed. After the trajectory changes, it is automatically re-judged and the early warning is lifted. At the same time, it adopts standardized data interface and mainstream communication protocol, which can be directly connected to existing low-altitude control equipment without large-scale modification. It is easy to implement and promote, further improving the feasibility of large-scale application.

[0050] Device Examples According to embodiments of the present invention, a low-altitude aircraft in-flight collision warning device is provided, such as... Figure 2 The diagram shown is a block diagram of a low-altitude aircraft in-flight collision warning device provided in this embodiment. According to an embodiment of the present invention, the low-altitude aircraft in-flight collision warning device includes: The status information acquisition and processing module 10 is used to acquire the sequence of aircraft status information of all aircraft. The status data includes at least three-dimensional position, flight speed and flight direction. After preprocessing, time synchronization calibration and unified coordinate system are completed. The confidence level of three-dimensional position and flight speed is determined according to the confidence level of communication parameters of information acquisition equipment.

[0051] The airspace meshing module 20 is used to determine the corresponding preset dynamic meshing rules based on the airspace range, flight scenario and aircraft operation density, dynamically mesh the airspace under the corresponding flight scenario, and map all aircraft status information to the corresponding mesh.

[0052] The collision risk prediction module 30 is used to determine the real-time status information of aircraft in the same grid and adjacent grids, use linear extrapolation to predict the flight trajectory of aircraft in the future, and then use the confidence of aircraft position and flight speed to correct the error of the predicted trajectory in order to determine the nearest encounter distance between aircraft, predict the collision time, and determine the collision risk.

[0053] In this embodiment, the system collects aircraft status data through signal reception or ground detection, preprocesses and optimizes the raw data, and outputs not only core status information such as aircraft identity, position, and speed, but also quantifies the confidence levels of position and speed, accurately reflecting measurement inaccuracies and providing reliable data support for centralized ground-based collision calculations. It also considers the status awareness of compliant and "black flight" targets, requiring no dedicated equipment on the aircraft, is unaffected by environmental factors, and can be widely deployed, solving the core problem of existing systems' inability to be applied on a large scale. The system dynamically divides the low-altitude airspace using an equidistant grid method, with grid size adaptable to aircraft operating density. Local collision prediction is achieved through "grid-aircraft" association; the system only calculates the collision risk of aircraft within a local grid, transforming global pairwise detection into local grid-based detection, significantly reducing computational load. This fundamentally solves the real-time warning problem for large-scale airborne aircraft, further supporting large-scale system applications. Simultaneously, it considers the measurement inaccuracies of aircraft positioning and speed to correct predicted flight trajectories, thereby accurately determining the collision risk between aircraft, ensuring the real-time effectiveness of warnings, and adapting to the long-term operational needs of large-scale aircraft.

[0054] In this embodiment, the confidence levels of the positioning and velocity of each aircraft are determined based on the communication parameters of the information acquisition equipment. These communication parameters include the confidence levels of positioning equipment accuracy, signal strength, and data update frequency. The specific calculations for the confidence levels of three-dimensional position and flight velocity are as follows: ; in, For the confidence level of equipment accuracy. For signal strength confidence, To update the frequency confidence; The weights for each dimension and each communication parameter can be configured according to the actual scenario.

[0055] In this embodiment, the airspace gridding module 20 determines the corresponding preset grid dynamic division rules based on the airspace range, flight scenario, and aircraft operating density. Specifically, it increases or decreases the grid size or uses a merging or splitting mechanism according to the flight scenario and aircraft operating density to achieve dynamic grid planning.

[0056] In this embodiment, the airspace meshing module 20 maps the current state information of all aircraft to the current mesh after dividing the airspace into meshes, realizing the construction of the "mesh-aircraft" association relationship, laying the foundation for aircraft collision risk prediction. The following uses Cartesian coordinates as an example to illustrate the process of constructing the "mesh-aircraft" association relationship: The controlled airspace is defined as follows: , The grid side length is ,but: Number of grids: ,

[0057] aircraft The position is Its grid number is:

[0058] in, To round up, This is for rounding down.

[0059] This embodiment also includes an airspace status monitoring and grid adjustment module, which monitors the aircraft density of each grid and performs grid adjustments based on preset high and low aircraft density thresholds. Specifically, it includes the following modules: The grid set construction submodule is used to obtain the original grid set, the number of aircraft in each grid, the density threshold, the basic grid side length, and to create an empty new grid set NewGridSet; The traversal submodule is used to traverse the number of aircraft in each grid. If the number of aircraft in a grid is greater than the density limit, it is fed back to the grid splitting submodule. Otherwise, the number of aircraft in a grid must be less than the density limit, and it is fed back to the grid merging submodule. If it is within the threshold range, no processing is performed.

[0060] The grid splitting submodule is used to split the current grid according to a preset splitting rule. In a specific embodiment, the splitting rule can be to call a grid splitting function (e.g., the split_grid function) to evenly split the current grid into 4 small grids of equal size, that is, small grids with a side length of L0 / 2, where L0 is the side length of the base grid.

[0061] The Mesh Merging submodule is used to merge the current mesh with neighboring meshes that have relatively fewer aircraft.

[0062] It also includes a collision detection and graded alarm module, which determines the collision time based on the distance between the two aircraft and the risk level based on the warning time threshold, enabling different levels of risk warnings. The control platform displays graded alarm information based on the collision risk level (combined with the nearest encounter distance and the predicted collision time), facilitating rapid response and obstacle avoidance by control personnel.

[0063] The embodiments of the present invention are device embodiments corresponding to the above method embodiments. The specific operations of each module processing step can be understood with reference to the description of the method embodiments, and will not be repeated here.

[0064] like Figure 3 As shown, the present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the low-altitude aircraft collision warning method described in the above embodiments.

[0065] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the low-altitude aircraft in-flight collision warning method described in the above embodiments.

[0066] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0067] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for apparatus or system embodiments, since they are basically similar to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. The apparatus and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0068] Furthermore, the functional modules in the various embodiments of this disclosure can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0069] 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. These modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and the contents not described in detail in the specification of the present invention are well known to those skilled in the art.

Claims

1. A method for in-flight collision warning of low-altitude aircraft, characterized in that, Includes the following steps: Collect the sequence of aircraft status information for all aircraft. The status information includes at least three-dimensional position, flight speed and flight direction. After preprocessing, complete time synchronization calibration and coordinate system unification. Determine the confidence level of three-dimensional position and flight speed based on the confidence level of communication parameters of the information acquisition equipment. Based on the airspace range, flight scenario, and aircraft operation density, the corresponding preset grid dynamic division rules are determined, the airspace under the corresponding flight scenario is dynamically gridded, and all aircraft status information is mapped to the corresponding grid. The real-time status information of aircraft in the same and adjacent grids is determined, and the flight trajectory of the aircraft in the future time is predicted by linear extrapolation. Then, the predicted trajectory is corrected by the confidence of the aircraft position and flight speed to determine the nearest encounter distance between aircraft, predict the collision time, and determine the collision risk.

2. The low-altitude vehicle in-flight collision warning method as described in claim 1, characterized in that, The specific steps for determining the confidence level of the three-dimensional position and flight speed based on the confidence level of the communication parameters of the information acquisition device are as follows: Confidence levels for the positioning accuracy, signal strength, and data update frequency of the data acquisition equipment; confidence levels for calculating the three-dimensional position and flight velocity: ； in, For the confidence level of equipment accuracy. For signal strength confidence, To update the frequency confidence; Weights for each dimension.

3. The low-altitude vehicle in-flight collision warning method as described in claim 1, characterized in that, The preset dynamic grid division rule specifically involves: increasing or decreasing the grid size based on the flight scenario and aircraft operating density; or Alternatively, by merging or splitting the grid.

4. The low-altitude vehicle in-flight collision warning method as described in claim 1, characterized in that, The specific steps for mapping all aircraft status information to the corresponding grid are as follows: The controlled airspace is defined as follows: , The grid side length is ,but: Number of grids: , aircraft The position is Its grid number is: in, To round up, This is for rounding down.

5. The low-altitude vehicle in-flight collision warning method as described in claim 1, characterized in that, It also includes collision detection and graded warning steps: determining the collision time based on the distance between the two aircraft, determining the risk level based on the warning time threshold, and realizing different levels of risk warning.

6. The low-altitude vehicle in-flight collision warning method as described in claim 5, characterized in that, The specific steps for determining the collision time based on the encounter distance between the two aircraft and determining the risk level based on the warning time threshold are as follows: Step B1, Calculation of predicted collision time: make Solve for the collision time The predicted collision time is: ； Step B2, Warning Trigger Determination: Let the warning time threshold be... ,but: ； Risk level classification formula: Combined with the meeting distance and collision time The risk value is calculated using a weighted scoring method. And based on risk value Determine the current collision risk level, trigger the corresponding level alarm, and set the risk value. Calculate as follows: ； in, As weight; according to Risk levels are determined by the value.

7. A low-altitude aircraft in-flight collision warning device, characterized in that, include: The status information acquisition and processing module is used to acquire the sequence of aircraft status information of all aircraft. The status data includes at least three-dimensional position, flight speed and flight direction. After preprocessing, time synchronization calibration and unified coordinate system are completed. The confidence level of three-dimensional position and flight speed is determined according to the confidence level of communication parameters of information acquisition equipment. The airspace gridding module is used to determine the corresponding preset grid dynamic division rules based on the airspace range, flight scenario and aircraft operation density, dynamically grid the airspace under the corresponding flight scenario, and map all aircraft status information to the corresponding grid. The collision risk prediction module is used to determine the real-time status information of aircraft in the same grid and adjacent grids. It uses linear extrapolation to predict the flight trajectory of aircraft in the future. Then, it corrects the error of the predicted trajectory by the confidence level of the aircraft's position and flight speed to determine the nearest encounter distance between aircraft, predict the collision time, and determine the collision risk.

8. The low-altitude aircraft in-flight collision warning device as described in claim 7, characterized in that, The preset dynamic grid division rule specifically involves: increasing or decreasing the grid size based on the flight scenario and aircraft operating density; or Alternatively, by merging or splitting the grid.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the low-altitude vehicle in-flight collision warning method as described in any one of claims 1 to 6.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the low-altitude vehicle in-flight collision warning method as described in any one of claims 1 to 6.

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