Low-altitude intelligent connection system design method based on three networks, one center and one platform

Abstract

The invention discloses a low-altitude intelligent connection system design method based on three networks, one center and one platform, relates to the technical field of flight equipment management and control, and solves the technical problem that an existing unmanned aerial vehicle management and control method is poor in effect when a large number of unmanned aerial vehicles and other related equipment are put into use. Comprising the following steps: constructing a low-altitude airway route network according to a live-action three-dimensional model and regional feature data; constructing a ground support facility network according to the ground service data; constructing a low-altitude intelligent information network according to the flight service data; constructing a region-level low-altitude flight data center according to the plurality of aviation flight data; constructing a region-level low-altitude management service platform of the target region; the area-level low-altitude management service platform is used for route planning before flight and monitoring and early warning in the flight process of each piece of flight equipment in a target area, and maintenance and guarantee after the flight is finished; when the unmanned aerial vehicle is used, the whole-process precise service can be provided, and then the use effect of flight equipment such as the unmanned aerial vehicle when the flight equipment is put into actual use and production is improved.

Description

Technical Field

[0001] The present application belongs to the field of flight equipment control technology, and relates to flight equipment control technology, specifically a design method for a low-altitude intelligent connection system based on three networks, one center and one platform. Background Art

[0002] The drone industry is currently in a stage of rapid development, with the market scale constantly expanding, technological progress and innovation accelerating, the industrial chain becoming increasingly mature, policy support and supervision gradually improving, and application scenarios and market demand increasing, showing vigorous vitality and huge development potential.

[0003] With the increase in the number of current drones and other flying equipment, the original airspace, routes, and related facilities are not well planned and cannot meet the current needs of drones; that is, the coordinated use of airspace resources is insufficient; low-altitude airspace classification and route demarcation are mostly based on traditional general aviation, and a comprehensive airspace assessment mechanism has not yet been established. The airspace supply cannot meet the growing demand for a large number of high-density low-altitude flight activities of unmanned aerial vehicles. The city-level intelligent information facilities are not perfect during the operation of drones. The currently planned and constructed intelligent information facilities such as VHF, ADS-B, and meteorological radar stations lack effective support for the flight of unmanned aerial vehicles in the city, and cannot provide flight monitoring, meteorological support, electromagnetic environment monitoring and other services, and do not have monitoring and countermeasure functions for non-cooperative aircraft. Insufficient low-altitude regulatory service means. At present, the regulatory services for low-altitude flights are mainly based on traditional general aviation aircraft. For unmanned aerial vehicles, there is a lack of effective and complete technical management and service means. The problems of "invisible, uncallable, and uncontrollable" and the difficulties and bottlenecks such as classification, sharing and exchange of flight data still exist. This results in poor results when drones and other related equipment are put into use. Therefore, a design method for a low-altitude intelligent connection system based on three networks, one center and one platform is needed. Summary of the invention

[0004] The present application aims to solve at least one of the technical problems existing in the prior art; to this end, the present application proposes a design method for a low-altitude intelligent connection system based on three networks, one center and one platform, which is used to solve the technical problem that the existing drone control methods are less effective when a large number of drones and other related equipment are put into use.

[0005] To achieve the above objectives, the first aspect of the present application provides a design method for a low-altitude intelligent connection system based on three networks, one center and one platform, including:

[0006] Acquire a real-life three-dimensional model and regional characteristic data of a target area, and construct a low-altitude airway route network based on the real-life three-dimensional model and the regional characteristic data; the low-altitude airway route network is used to plan the airspace of the target city and the route planning;

[0007] Acquire some ground service data of the target area, and construct a ground support facility network according to the ground service data; the ground support facility network is used to provide surface support for the flight equipment;

[0008] Acquire flight service data of the target area, and construct a low-altitude intelligent information network based on the flight service data; the low-altitude intelligent information network is used to provide monitoring and management services for flight equipment throughout the entire flight process;

[0009] Acquire a number of real-time aviation flight data of the target area, and build a regional low-altitude flight data center based on the a number of aviation flight data; the regional low-altitude flight center is used to record the aviation flight data in the area;

[0010] Thus, a regional-level low-altitude management service platform is constructed for the target area; the regional-level low-altitude management service platform is used for pre-flight route planning, in-flight monitoring and early warning, and post-flight maintenance and support of various flight equipment in the target area.

[0011] This application constructs a low-altitude route network through a real-life three-dimensional model and regional characteristic data in the target area; constructs a ground support facility network based on ground service data in the target area; constructs a low-altitude intelligent information network based on flight service data in the target area; constructs a regional low-altitude flight data center based on the various data generated above; and constructs a regional low-altitude management service platform based on the above functions; the regional low-altitude management service platform divides and analyzes the airspace in the target area and plans routes, as well as provides full-process monitoring, early warning, management and other services for drones and other flight equipment; enables drones and other flight equipment to provide full-process precise services when used in the corresponding areas, thereby improving the use effect of drones and other flight equipment when they are put into actual production.

[0012] Preferably, the step of constructing a low-altitude airway network based on the real-scene three-dimensional model and regional feature data includes:

[0013] Extract airspace type data, geographic information, population information and obstacle information from regional feature data;

[0014] Extract the flight airspace and control area from the airspace type data; divide the flight airspace and control area in the real-life 3D model; obtain the flyable area and no-fly area;

[0015] The flyable area is rasterized to obtain geographic information, population information and obstacle information of each grid; the geographic information, population information and obstacle information are input into a ground risk quantitative assessment model to obtain a ground risk score of the corresponding grid; the ground risk quantitative assessment model is obtained by training an artificial intelligence model;

[0016] The ground risk score of each grid is obtained in turn, and the ground risk score is marked in the flyable area to obtain a risk map of the target area; low-altitude airway routes are planned according to the ground risk score of each grid on the risk map; so as to form a low-altitude airway route network.

[0017] Preferably, the ground risk quantitative assessment model is obtained through artificial intelligence model training, including:

[0018] Obtaining geographic information, population information and obstacle information corresponding to a plurality of grids; and a ground risk score corresponding thereto; the ground risk score being generated according to the geographic information, population information and obstacle information;

[0019] Integrate geographic information, population information, obstacle information and corresponding ground risk scores into several groups of training data and test data, use the training data to train the artificial intelligence model, and use the test data to test the trained artificial intelligence model; specifically, input the geographic information, population information, and obstacle information in the test data into the trained artificial intelligence model to obtain a ground risk score; determine whether the difference between the ground risk score and the ground risk score recorded in the test data is within an acceptable range, if yes, proceed to the next group of test data for testing; if not, adjust the relevant parameters of the artificial intelligence and continue to use the current group of test data for testing; until the number of test data that pass the test reaches a set ratio; finally, a ground risk quantitative assessment model is obtained with geographic information, population information and obstacle information as input and a ground risk score as output; wherein the artificial intelligence model includes a BP neural network model and an RBF neural network model.

[0020] Preferably, the ground risk score is generated based on geographic information, population information and obstacle information, including:

[0021] Obtain the terrain type in the geographic information; the population number RS ​​and the population flow number LS in the corresponding period in the population information; the obstacle height in the obstacle information;

[0022] According to the terrain and geomorphology type, the corresponding terrain and geomorphology risk score DP is searched in the risk relationship lookup table; the risk relationship lookup table records the one-to-one correspondence between terrain and geomorphology types and terrain and geomorphology risk scores. The terrain and geomorphology risk score is the score given by experts based on the impact of the corresponding terrain and geomorphology type on the flight of low-altitude UAVs. The greater the impact, the higher the corresponding score. For example, if the terrain and geomorphology type is mountainous, its impact on the flight of low-altitude UAVs is greater, and its corresponding terrain and geomorphology risk score is set to be larger. For example, if the terrain and geomorphology type is plain, its impact on the flight of low-altitude UAVs is smaller, and its corresponding terrain and geomorphology risk score is set to be smaller;

[0023] Obtain the number of obstacles ZS whose obstacle heights are within the flight altitude range;

[0024] The ground risk score DFP for the corresponding period is calculated by the formula DFP=α1×DP+α2×exp((RS+LS) / RS)+α3×exp(ZS / ZZS); where ZZS is the total number of obstacles; α1, α2 and α3 are proportional coefficients, and the specific values ​​are set according to experience. The proportional coefficients are used to adjust the proportion of the influence of different items on the ground risk score.

[0025] Preferably, the building of a ground support facility network based on ground service data includes:

[0026] Obtain general airport information of several general airports and take-off and landing platform information of several take-off and landing platforms in ground service data;

[0027] Extract the airport type, airport location and airport function from the general airport information; determine whether the airport function includes the supply function;

[0028] If yes, determine whether the airport function includes ground service support function; if yes, set the corresponding general airport as a comprehensive support service point; if no, set the corresponding general airport as a supply support service point;

[0029] If not, the corresponding general airport will be set as a take-off and landing support service point;

[0030] Extract the take-off and landing platform information, including the type of take-off and landing platform, the location of the take-off and landing platform, and the function of the take-off and landing platform; determine whether the take-off and landing platform function includes the replenishment function;

[0031] If yes, determine whether the take-off and landing platform function includes ground service support function; if yes, set the corresponding take-off and landing platform as a comprehensive support service point; if no, set the corresponding take-off and landing platform as a supply support service point;

[0032] If not, the corresponding take-off and landing platform will be set as a take-off and landing support service point;

[0033] Obtain various comprehensive support service points, supply support service points and take-off and landing support service points, as well as their corresponding airport types or take-off and landing platform types, airport locations or take-off and landing platform locations; thereby constructing a ground support setting network.

[0034] Preferably, the step of constructing a low-altitude intelligent information network based on flight service data includes:

[0035] Extract monitoring equipment information, meteorological equipment information and radar equipment information from flight service data;

[0036] A monitoring service network, a positioning service network and a defense service network are established based on the monitoring equipment information and the radar equipment information; the monitoring service network is used to provide monitoring services to the corresponding flight equipment; the positioning service network is used to provide positioning services to the corresponding server; the defense service network is used to provide security defense services to the target area; a meteorological service network is established based on the meteorological equipment information; the meteorological service network is used to provide meteorological warning services to the corresponding flight equipment;

[0037] This will build a low-altitude intelligent information network.

[0038] Preferably, the step of constructing a regional low-altitude flight data center based on a number of aviation flight data includes:

[0039] Real-time acquisition of navigation data, meteorological data, intelligence data, airspace data, route data and flight data from a number of aviation flight data; thereby constructing a regional low-altitude flight data center corresponding to the target area; and storing real-time aviation flight data in the regional low-altitude flight data center corresponding to the target area.

[0040] Compared with the prior art, the beneficial effects of this application are:

[0041] 1. This application constructs a low-altitude route network through a real-life three-dimensional model and regional characteristic data in the target area; constructs a ground support facility network based on ground service data in the target area; constructs a low-altitude intelligent information network based on flight service data in the target area; constructs a regional low-altitude flight data center based on the various data generated above; and constructs a regional low-altitude management service platform based on the above functions; the regional low-altitude management service platform divides and analyzes the airspace in the target area and plans routes, as well as provides full-process monitoring, early warning, management and other services for drones and other flight equipment; enables drones and other flight equipment to provide full-process precise services when they are put into use in the corresponding area, thereby improving the use effect of drones and other flight equipment when they are put into actual production. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0043] Figure 1 This is a schematic diagram of the principles of the design method of the low-altitude intelligent connection system for this application. DETAILED DESCRIPTION

[0044] The technical solution of the present application will be described clearly and completely below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0045] See also Figure 1 The first embodiment of the present application provides a design method for a low-altitude intelligent connection system based on three networks, one center and one platform, including:

[0046] Acquire a real-life 3D model and regional feature data of the target area, wherein the real-life 3D model is a 3D model of the target area constructed based on buildings, topography, and landforms of the target area; the regional feature data is feature data such as airspace type data, geographic information, population information, and obstacle information of the corresponding target area; construct a low-altitude airway route network based on the real-life 3D model and the regional feature data; the low-altitude airway route network is used to plan the airspace of the target city and route planning;

[0047] Acquire some ground service data of the target area. The topographic aviation service facilities are the data of the flight equipment facilities that have been built, are about to be built, or are planned to be built in the target area, including the relevant data of the general airport and the take-off and landing platform and other related settings; construct a ground support facility network based on the ground service data; the ground support facility network is used to provide surface support for the flight equipment;

[0048] Acquire flight service data of the target area, where the flight service data refers to the equipment in the target area that performs monitoring, early warning and positioning functions on the flight equipment during the entire flight process, including monitoring equipment information, meteorological equipment information and radar equipment information; construct a low-altitude intelligent information network based on the flight service data; the low-altitude intelligent information network is used to provide monitoring and management services for the flight equipment during the entire flight process;

[0049] Acquire a number of real-time aviation flight data of the target area, the aviation flight data is the data generated by each flight of the flight equipment in the target area, including navigation data, meteorological data, intelligence data, airspace data, route data and flight data, etc.; construct a regional low-altitude flight data center based on the aviation flight data; the regional low-altitude flight center is used to record the aviation flight data in the area;

[0050] Thus, a regional-level low-altitude management service platform is constructed for the target area; the regional-level low-altitude management service platform is used for pre-flight route planning, in-flight monitoring and early warning, and post-flight maintenance and support of various flight equipment in the target area.

[0051] This embodiment constructs a low-altitude route network through a real-life three-dimensional model and regional characteristic data in the target area; constructs a ground support facility network based on ground service data in the target area; constructs a low-altitude intelligent information network based on flight service data in the target area; constructs a regional low-altitude flight data center based on the various data generated above; and constructs a regional low-altitude management service platform based on the above functions; the regional low-altitude management service platform divides and analyzes the airspace in the target area and plans routes, as well as provides full-process monitoring, early warning, management and other services for drones and other flight equipment; enables drones and other flight equipment to provide full-process precise services when used in the corresponding area, thereby improving the use effect of drones and other flight equipment when they are put into actual production.

[0052] Constructing a low-altitude air route network based on the real-life 3D model and regional feature data, including: extracting airspace type data, geographic information, population information and obstacle information from the regional feature data;

[0053] Extract the flight airspace and control area from the airspace type data; the flight airspace is the airspace specified in the target area that can be used for the flight of drones and other flying equipment, and the control area is the airspace specified in the target area that cannot be used for the flight of drones and other flying equipment; divide the flight airspace and control area in the real-life 3D model; obtain the flyable area and the no-fly area; the flyable area is the area where drones and other flying equipment can perform flight operations; the no-fly area is the area where drones and other flying equipment cannot perform flight operations;

[0054] The flyable area is rasterized to obtain the geographic information, population information and obstacle information of each grid; the geographic information, population information and obstacle information are input into the ground risk quantitative assessment model to obtain the ground risk score of the corresponding grid; the ground risk score is a score generated according to the regional characteristics corresponding to the grid area and used to evaluate the risk of the flight equipment in the corresponding grid during flight; when the ground risk score value is large, it means that the risk is greater when flying in the corresponding area; the ground risk quantitative assessment model is obtained by training an artificial intelligence model;

[0055] The ground risk score of each grid is obtained in turn, and the ground risk score is marked in the flyable area to obtain a risk map of the target area; the low-altitude airway route is planned according to the ground risk score of each grid on the risk map; specifically, the minimum value of the ground risk score of each grid in the area where the starting point and the target point pass through can be used as the route planning grid corresponding to the starting point and the target point, and the route is planned to form a low-altitude airway route network.

[0056] This embodiment conducts a multi-factor mechanism analysis through low-altitude complex environment characteristic data such as airspace type data, geographic information, population information, and obstacle information, constructs a quantitative assessment model and risk map of UAV ground risks, introduces risk cost improvement algorithm heuristics, designs multi-path planning strategies, and establishes weight evaluation rules for typical application scenarios to achieve efficient use of low-altitude airspace.

[0057] The ground risk quantitative assessment model is obtained through artificial intelligence model training, including: obtaining geographic information, population information and obstacle information corresponding to a number of grids; and the corresponding ground risk score; the ground risk score is generated according to the geographic information, population information and obstacle information;

[0058] Integrate geographic information, population information, obstacle information and corresponding ground risk scores into several groups of training data and test data, use the training data to train the artificial intelligence model, and use the test data to test the trained artificial intelligence model; specifically, input the geographic information, population information, and obstacle information in the test data into the trained artificial intelligence model to obtain a ground risk score; determine whether the difference between the ground risk score and the ground risk score recorded in the test data is within an acceptable range, if yes, proceed to the next group of test data for testing; if not, adjust the relevant parameters of the artificial intelligence and continue to use the current group of test data for testing; until the number of test data that pass the test reaches a set ratio; finally, obtain a ground risk quantitative assessment model with geographic information, population information and obstacle information as input and ground risk score as output; wherein the artificial intelligence model includes a BP neural network model and an RBF neural network model; this embodiment trains the artificial model so that when the platform is used in other areas, it can quickly evaluate each grid area to improve operation efficiency.

[0059] The ground risk score is generated based on geographic information, population information and obstacle information, including: obtaining the terrain type in the geographic information; the population number RS ​​and the population flow number LS in the corresponding time period in the population information. The population flow number in the corresponding time period indicates the population flow in the grid area during a set period. A positive population flow number indicates that the population in the area will increase during the period, such as the population flow in the office area during working hours; a negative population flow number indicates that the population in the area will decrease during the period, such as the population flow in the residential area during working hours; obstacle height in the obstacle information;

[0060] According to the terrain and geomorphology type, the corresponding terrain and geomorphology risk score DP is searched in the risk relationship lookup table; the risk relationship lookup table records the one-to-one correspondence between terrain and geomorphology types and terrain and geomorphology risk scores. The terrain and geomorphology risk score is the score given by experts based on the impact of the corresponding terrain and geomorphology type on the flight of low-altitude UAVs. The greater the impact, the higher the corresponding score. For example, if the terrain and geomorphology type is mountainous, its impact on the flight of low-altitude UAVs is greater, and its corresponding terrain and geomorphology risk score is set to be larger. For example, if the terrain and geomorphology type is plain, its impact on the flight of low-altitude UAVs is smaller, and its corresponding terrain and geomorphology risk score is set to be smaller;

[0061] Obtain the number of obstacles ZS whose obstacle heights are within the flight altitude range;

[0062] The ground risk score DFP for the corresponding period is calculated by the formula DFP=α1×DP+α2×exp((RS+LS) / RS)+α3×exp(ZS / ZZS); where ZZS is the total number of obstacles; α1, α2 and α3 are proportional coefficients, and the specific values ​​are set according to experience. The proportional coefficients are used to adjust the proportion of the influence of different items on the ground risk score.

[0063] This embodiment calculates the ground risk coefficient corresponding to the geographic information, population information and obstacle information through the above formula; the more complex the terrain and ground conditions in the area, the greater the risk of the flight equipment during flight, and the larger the ground risk score is set; when there are more people in the area, the probability and severity of danger caused by abnormal crashes of flight equipment and the like are greater, and the larger the ground risk score is set; the more obstacles there are within the risk altitude range, the greater the risk during flight; the larger the ground risk score is set; the above formula is used to reasonably score each area, which is convenient for subsequent route planning.

[0064] Constructing a ground support facility network according to ground service data includes: obtaining general airport information of several general airports and landing platform information of several landing platforms in the ground service data; the general airport information includes airport type, airport location, airport function and other airport information, the airport type includes Class A general airport and Class B general airport, etc., and the airport function includes parking function, supply function and ground service support function and other related ground service functions; the landing platform information includes landing platform type, landing platform location and landing platform function and other information about the landing platform, the landing platform type includes small landing platform for unmanned aerial vehicles, medium-sized landing field, large landing hub, eVTOL landing field and helicopter landing platform, etc.; the landing platform function includes parking function, supply function and ground service support function and other related ground service functions; the parking function is that the corresponding general airport or landing platform can be used for take-off and parking of flight equipment; the supply function is that the corresponding general airport or landing platform can be used for energy supply and material supply of flight equipment; the ground service support function is that the corresponding general airport or landing platform can provide some technical functions such as maintenance and inspection of flight equipment;

[0065] Extract the airport type, airport location and airport function from the general airport information; determine whether the airport function includes the supply function;

[0066] If yes, determine whether the airport function includes ground service support function; if yes, set the corresponding general airport as a comprehensive support service point; if no, set the corresponding general airport as a supply support service point;

[0067] If not, the corresponding general airport will be set as a take-off and landing support service point;

[0068] Extract the take-off and landing platform information, including the type of take-off and landing platform, the location of the take-off and landing platform, and the function of the take-off and landing platform; determine whether the take-off and landing platform function includes the replenishment function;

[0069] If yes, determine whether the take-off and landing platform function includes ground service support function; if yes, set the corresponding take-off and landing platform as a comprehensive support service point; if no, set the corresponding take-off and landing platform as a supply support service point;

[0070] If not, the corresponding take-off and landing platform will be set as a take-off and landing support service point;

[0071] Obtain various comprehensive support service points, supply support service points and take-off and landing support service points, as well as their corresponding airport types or take-off and landing platform types, airport locations or take-off and landing platform locations; thereby constructing a ground support setting network.

[0072] This embodiment obtains general airport information of several general airports and take-off and landing platform information of several take-off and landing platforms in the target area, analyzes the functions of each general airport and take-off and landing platform, classifies the general airports and take-off and landing platforms, and sets them as corresponding ground support service points; the ground support service points include comprehensive support service points, supply support service points and take-off and landing support service points; then a ground support setting network is constructed according to the location and type of each ground support service point; in order to meet the support needs of low-altitude aircraft in the target area, unified scheduling of drone take-off and landing and energy replenishment is realized.

[0073] Constructing a low-altitude intelligent information network based on flight service data includes: extracting monitoring equipment information, meteorological equipment information and radar equipment information from the flight service data; the monitoring equipment information includes monitoring equipment type, monitoring equipment location and monitoring equipment function; the monitoring equipment type includes ground monitoring equipment and satellite monitoring equipment; the monitoring equipment function includes monitoring function, positioning function and communication function, etc.; the meteorological equipment information includes meteorological equipment location and meteorological equipment function, and the meteorological equipment function includes meteorological monitoring function and meteorological forecasting function, etc.; the radar equipment information includes radar equipment location and radar equipment function; the radar equipment function includes interference function, interception function, strike function and detection function, etc.;

[0074] A monitoring service network, a positioning service network and a defense service network are established based on the monitoring equipment information and the radar equipment information; the monitoring service network is used to provide monitoring services to the corresponding flight equipment; the positioning service network is used to provide positioning services to the corresponding server; the defense service network is used to provide security defense services to the target area; a meteorological service network is established based on the meteorological equipment information; the meteorological service network is used to provide meteorological warning services to the corresponding flight equipment; thereby constructing a low-altitude intelligent information network.

[0075] This embodiment obtains information from a number of monitoring equipment, meteorological equipment, and radar equipment in the target area, and thereby constructs a low-altitude intelligent information network to improve the communication, navigation, surveillance, and environmental perception capabilities of general aviation flights, achieve full coverage of general aviation route perception and communication, and enhance the capabilities of self-perception, accurate prediction, intelligent planning, route optimization, coordinated sharing, risk identification, and special service processing of aircraft situations in a panoramic, full-domain, and full-dimensional manner; based on the existing video surveillance, dedicated network, and other infrastructure built by the Skynet Project and the Xueliang Project, carry out ADS-B, 5G / 6G, satellite communications, and Beidou Digital Communications. Through the integration and application of new technologies such as data chain, we will develop a satellite-ground integrated perception information network based on the city's dedicated video network, optimize the city's low-altitude communication network, ensure the interconnection of low-altitude flight data, and achieve full coverage of low-altitude communication and surveillance on air routes; enhance the management capabilities of cooperative aircraft and the counter-attack capabilities of non-cooperative aircraft, support the construction of key defense projects in controlled areas and major events, deploy multi-source detection systems such as radar, radio detection, and optoelectronic detection, as well as counter-attack systems such as interference, deception, interception, and attack, and build ground-based, vehicle-mounted, ball-mounted, and airborne integrated air-to-ground drone defense systems to provide support for the supervision of non-cooperative aircraft.

[0076] A regional low-altitude flight data center is built based on a number of aviation flight data, including:

[0077] Real-time acquisition of navigation data, meteorological data, intelligence data, airspace data, route data and flight data from a number of aviation flight data; thereby constructing a regional low-altitude flight data center corresponding to the target area; and storing real-time aviation flight data in the regional low-altitude flight data center corresponding to the target area.

[0078] This embodiment builds a regional low-altitude flight data center to store the real-time acquired aviation flight data in the corresponding regional low-altitude flight data center; it is conducive to the realization of low-altitude big data management mechanism, standard specifications and security assurance system, the realization of data full life cycle management, the construction of a low-altitude data base, the realization of regional low-altitude data catalog compilation, supply and demand docking, aggregation and integration, sharing and opening, synchronization of data catalogs, and support for on-demand calls.

[0079] In this embodiment, the target area can be a province or city-level area, and the area divided by other experts is obtained; a regional low-altitude supervision service platform is constructed, and based on big data real-time analysis, parallel computing and other technologies, a massive amount of low-altitude flight navigation data, meteorological data, intelligence data, airspace data, route data and flight data are shared, counted, displayed, traced and other services are provided, and airspace and route application, flight plan declaration, aviation intelligence, meteorological support, air traffic risk identification and warning, identification and disposal of non-cooperative aircraft, aircraft and personnel management and other services are provided to low-altitude aircraft users, and the interconnection with the stationed military aviation control department, civil aviation air traffic management department, industry competent department, municipal management department and other systems is supported. Functions such as flight situation awareness, flight supervision, early warning center and emergency command are realized, and low-altitude flight services are applied in advance, monitored during the process, and supervised after the process is completed; so as to realize the full process supervision of flight equipment, and then prepare for the production and use of a large number of flight equipment, so as to ensure the effect when a large number of flight equipment are put into production and use.

[0080] Part of the data in the above formula is calculated by removing the dimension and taking its numerical value. The formula is a formula closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0081] How this application works:

[0082] This application constructs a low-altitude route network through a real-life three-dimensional model and regional characteristic data in the target area; constructs a ground support facility network based on ground service data in the target area; constructs a low-altitude intelligent information network based on flight service data in the target area; constructs a regional low-altitude flight data center based on the various data generated above; and constructs a regional low-altitude management service platform based on the above functions; the regional low-altitude management service platform divides and analyzes the airspace in the target area and plans routes, as well as provides full-process monitoring, early warning, management and other services for drones and other flight equipment; enables drones and other flight equipment to provide full-process precise services when used in the corresponding areas, thereby improving the use effect of drones and other flight equipment when they are put into actual production.

[0083] The above embodiments are only used to illustrate the technical method of the present application and are not intended to limit it. Although the present application has been described in detail with reference to the preferred embodiments, a person of ordinary skill in the art should understand that the technical method of the present application may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present application.

Claims

1. A design method for a low-altitude intelligent connection system based on three networks, one center and one platform, characterized in that: include: Obtain the real-life 3D model and regional feature data of the target area, and construct a low-altitude airway network based on the real-life 3D model and regional feature data; The low-altitude airway route network is used to plan the airspace of the target city and the route planning; Acquire some ground service data of the target area, and construct a ground support facility network according to the ground service data; the ground support facility network is used to provide surface support for the flight equipment; Acquire flight service data of the target area, and construct a low-altitude intelligent information network based on the flight service data; the low-altitude intelligent information network is used to provide monitoring and management services for flight equipment throughout the entire flight process; Acquire a number of real-time aviation flight data of the target area, and build a regional low-altitude flight data center based on the a number of aviation flight data; the regional low-altitude flight center is used to record the aviation flight data in the area; Construct a regional low-altitude management service platform for the target area; the regional low-altitude management service platform is used for pre-flight route planning, in-flight monitoring and early warning, and post-flight maintenance and support for each flight equipment in the target area.

2. The design method of low-altitude intelligent connection system based on three networks, one center and one platform according to claim 1 is characterized in that: The method of constructing a low-altitude airway network based on the real-scene three-dimensional model and regional feature data includes: Extract airspace type data, geographic information, population information and obstacle information from regional feature data; Extract the flight airspace and control area from the airspace type data; divide the flight airspace and control area in the real-life 3D model; obtain the flyable area and no-fly area; The flyable area is rasterized to obtain geographic information, population information and obstacle information of each grid; the geographic information, population information and obstacle information are input into a ground risk quantitative assessment model to obtain a ground risk score of the corresponding grid; the ground risk quantitative assessment model is obtained by training an artificial intelligence model; The ground risk score of each grid is obtained in turn, and the ground risk score is marked in the flyable area to obtain a risk map of the target area; low-altitude airway routes are planned according to the ground risk score of each grid on the risk map; so as to form a low-altitude airway route network.

3. The design method of low-altitude intelligent connection system based on three networks, one center and one platform according to claim 2 is characterized in that: The ground risk quantitative assessment model is obtained through artificial intelligence model training, including: Obtaining geographic information, population information and obstacle information corresponding to a plurality of grids; and a ground risk score corresponding thereto; the ground risk score being generated according to the geographic information, population information and obstacle information; Integrate geographic information, population information, obstacle information and corresponding ground risk scores into several groups of training data and test data, use the training data to train the artificial intelligence model, and use the test data to test the trained artificial intelligence model; finally, a ground risk quantitative assessment model is obtained with geographic information, population information and obstacle information as input and ground risk score as output.

4. The design method of low-altitude intelligent connection system based on three networks, one center and one platform according to claim 3 is characterized in that: The ground risk score is generated based on geographic information, population information and obstacle information, including: Obtain the terrain type in the geographic information; the population number RS ​​and the population flow number LS in the corresponding period in the population information; the obstacle height in the obstacle information; According to the terrain and geomorphology type, find the corresponding terrain and geomorphology risk score DP in the risk relationship lookup table; Obtain the number of obstacles ZS whose obstacle heights are within the flight altitude range; The ground risk score DFP for the corresponding period is calculated by the formula DFP=α1×DP+α2×exp((RS+LS) / RS)+α3×exp(ZS / ZZS); where ZZS is the total number of obstacles; α1, α2 and α3 are proportional coefficients.

5. The design method of low-altitude intelligent connection system based on three networks, one center and one platform according to claim 1 is characterized in that: The ground support facility network is constructed according to the ground service data, including: Obtain general airport information of several general airports and take-off and landing platform information of several take-off and landing platforms in ground service data; Extract the airport type, airport location and airport function from the general airport information; determine whether the airport function includes the supply function; If yes, determine whether the airport function includes ground service support function; if yes, set the corresponding general airport as a comprehensive support service point; if no, set the corresponding general airport as a supply support service point; If not, the corresponding general airport will be set as a take-off and landing support service point; Extract the take-off and landing platform information, including the type of take-off and landing platform, the location of the take-off and landing platform, and the function of the take-off and landing platform; determine whether the take-off and landing platform function includes the replenishment function; If yes, determine whether the take-off and landing platform function includes ground service support function; if yes, set the corresponding take-off and landing platform as a comprehensive support service point; if no, set the corresponding take-off and landing platform as a supply support service point; If not, the corresponding take-off and landing platform will be set as a take-off and landing support service point; Obtain various comprehensive support service points, supply support service points and take-off and landing support service points, as well as their corresponding airport types or take-off and landing platform types, airport locations or take-off and landing platform locations; and build a ground support setting network.

6. The design method of low-altitude intelligent connection system based on three networks, one center and one platform according to claim 1 is characterized in that: The low-altitude intelligent information network is constructed based on flight service data, including: Extract monitoring equipment information, meteorological equipment information and radar equipment information from flight service data; A monitoring service network, a positioning service network and a defense service network are established based on the monitoring equipment information and the radar equipment information; the monitoring service network is used to provide monitoring services to the corresponding flight equipment; the positioning service network is used to provide positioning services to the corresponding server; the defense service network is used to provide security defense services to the target area; a meteorological service network is established based on the meteorological equipment information; the meteorological service network is used to provide meteorological warning services to the corresponding flight equipment; and a low-altitude intelligent information network is constructed.

7. The design method of low-altitude intelligent connection system based on three networks, one center and one platform according to claim 1 is characterized in that: The regional low-altitude flight data center is constructed based on a number of aviation flight data, including: Real-time acquisition of aviation data, meteorological data, intelligence data, airspace data, etc. data, route data and flight data; thereby building a regional low-altitude flight data center corresponding to the target area; The real-time aviation flight data is stored in the regional low-altitude flight data center corresponding to the target area.

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