Electronic fence positioning method and system for low-altitude flight control

Abstract

The present invention discloses an electronic fence positioning method and system for low-altitude flight control, and belongs to the field of data analysis technology. The embodiment of the present application realizes the basis for refined management of low-altitude flight by constructing a low-altitude flight fence space and setting quantitative characteristics of flight warning. Obtaining electronic fence monitoring routes and their spatiotemporal cross-sensing data to determine the local control area helps to accurately focus on airspace with different functions and risks and improve control efficiency. Determining the alarm data of different monitoring routes based on the quantitative characteristics of flight warnings, and considering the differences in tasks of different routes in the same area, it can adapt to complex and diverse flight scenarios and reduce misjudgments. Determining the monitoring risk decision characteristics and controlling the flight in response to the trigger conditions can timely and targetedly handle abnormal situations of low-altitude aircraft, effectively ensure the safety and order of low-altitude flights, and avoid potential threats to specific areas (such as airports, event venues, etc.).

Description

Technical Field

[0001] The embodiments of the present application belong to the field of data analysis technology, and specifically relate to an electronic fence positioning method and system applied to low-altitude flight control. Background Art

[0002] With the widespread use of low-altitude aircraft (such as drones), ensuring the safety of low-altitude flights while protecting their legitimate flight rights has become an urgent problem to be solved. The traditional low-altitude flight control method is relatively extensive and lacks consideration of the characteristics of different regions and the diversity of flight missions. For example, in special areas such as airports and urban activity venues, the management of low-altitude aircraft cannot be simply generalized. The lack of refined airspace division and quantitative flight status early warning mechanism makes it difficult to accurately judge whether the aircraft is in a dangerous state, which can easily lead to misjudgment or untimely response to potential dangers.

[0003] In addition, in modern low-altitude flight management, the technical background that the high-precision electronic map module and electronic fence used in the flight control system of the aircraft belong to the same flight cloud control management platform is also of great significance. The high-precision electronic map module can provide accurate geographic location information for the aircraft, which is the basis for achieving accurate flight. The electronic fence is an important means to ensure the safety of a specific area. Unifying the two in the flight cloud control management platform helps to achieve data integration and sharing. Under the traditional control method, the two may operate independently and cannot effectively cooperate, resulting in difficulty in fully utilizing the data advantages of the high-precision electronic map module to optimize the function of the electronic fence in low-altitude flight management, thereby affecting the effective control of low-altitude flight. For example, without such a unified platform, the electronic fence may not be able to accurately adjust the boundaries and control strategies based on the terrain, obstacles and other information in the high-precision electronic map, and thus cannot make accurate and timely response measures when facing complex low-altitude flight situations. Summary of the invention

[0004] The embodiments of the present application provide an electronic fence positioning method and system for low-altitude flight control, which can solve or partially solve the technical problems involved in the above-mentioned background technology.

[0005] An embodiment of the present application provides an electronic fence positioning method for low-altitude flight control, which is applied to an electronic fence positioning system. The method includes: constructing a plurality of low-altitude flight fence spaces to be monitored and setting a plurality of flight warning quantitative features; obtaining a plurality of electronic fence monitoring routes used for implementing flight monitoring and time-space cross-perception data between the electronic fence monitoring routes, and determining at least two local flight tracking and control areas based on the time-space cross-perception data; determining the monitoring and warning data of each electronic fence monitoring route in the at least two local flight tracking and control areas based on the plurality of flight warning quantitative features; there are differences in the monitoring and warning data of the electronic fence monitoring routes in different route tasks in the same local flight tracking and control area; in response to a low-altitude aircraft triggering an electronic fence positioning and tracking condition, determining the monitoring risk decision feature corresponding to the low-altitude aircraft based on the monitoring and warning data of the low-altitude aircraft; and performing flight control processing on the low-altitude aircraft using the monitoring risk decision feature.

[0006] An embodiment of the present application provides an electronic fence positioning system, comprising at least one processor and a memory; the memory stores computer-executable instructions; the at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor executes the above method.

[0007] An embodiment of the present application provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the above method are implemented.

[0008] In the embodiment of the present application, by constructing a low-altitude flight fence space and setting quantitative characteristics of flight warnings, a refined management basis for low-altitude flight is implemented. Obtaining electronic fence monitoring routes and their spatiotemporal cross-sensing data to determine local control areas helps to accurately focus on airspace with different functions and risks and improve control efficiency. Determining the alarm data for different monitoring routes based on the quantitative characteristics of flight warnings, and considering the differences in missions for different routes in the same area, it can adapt to complex and diverse flight scenarios and reduce misjudgments. Determining the monitoring risk decision characteristics and controlling the flight in response to the trigger conditions can handle abnormal situations of low-altitude aircraft in a timely and targeted manner, effectively ensuring the safety and order of low-altitude flights, and avoiding potential threats to specific areas (such as airports, event venues, etc.). BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 A flowchart of an electronic fence positioning method for low-altitude flight control provided in an embodiment of the present application.

[0010] Figure 2 A schematic diagram of the structure of an electronic fence positioning system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0011] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of them. Based on the embodiments in the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the embodiments of the present application.

[0012] The terms "first", "second", etc. in the embodiments of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally a class, and the number of objects is not limited. For example, the first object can be one or more. In addition, in the embodiments of the present application, "and / or" represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0013] Figure 1 A method for positioning an electronic fence for low-altitude flight control is shown, which is applied to an electronic fence positioning system. The method includes the following steps 110 to 140.

[0014] Step 110: The electronic fence positioning system constructs a number of low-altitude flight fence spaces to be monitored and sets a number of flight warning quantitative features.

[0015] In this application, the electronic fence positioning system needs to consider a variety of factors when constructing the low-altitude flight fence space to be monitored. First of all, it is crucial to determine the geographical scope. For example, for low-altitude flight control in an urban area, the electronic fence positioning system may designate the entire city’s built-up area or a specific functional area (such as a 10-kilometer radius around the airport, a large event venue and its surrounding area with a 3-kilometer radius, etc.) as a low-altitude flight fence space to be monitored.

[0016] In the construction of three-dimensional space, in addition to the horizontal geographical scope, the vertical height range also needs to be clarified. For example, for the control of civil drones, low-altitude flight may be defined as an altitude range of 100 to 1,000 meters above the ground. The determination of this altitude range may be based on a comprehensive consideration of factors such as drone performance, potential risk altitude (such as avoiding affecting normal air route altitudes), and urban building heights.

[0017] In terms of spatial shape, the space of the low-altitude flight fence to be monitored may be a regular geometric shape, such as a circle (a circular area with a radius of 10 kilometers centered on a key facility, such as the center of an airport runway) or a rectangle (covering a large industrial park, a rectangular area of ​​5 kilometers long and 3 kilometers wide), or it may be an irregular shape, such as a complex shape space that fits the actual terrain based on the geographical features of the city (mountains, rivers, etc.) and special areas (such as the irregular boundaries of military restricted areas).

[0018] Furthermore, the flight warning quantitative characteristics are key indicators for quantitatively assessing the risk of low-altitude flights. Among them, an important quantitative characteristic is the speed of the aircraft. For example, the speed thresholds of different types of aircraft are set. If it is a small civilian drone, the normal flight speed is generally between 10-50 meters per second. When its speed is detected to exceed 60 meters per second, it may be regarded as an abnormal situation and trigger an early warning.

[0019] The altitude change rate of the aircraft is also a key quantitative feature. For example, under normal flight conditions, the altitude of the drone changes relatively smoothly, and the altitude change rate is within ±5 meters per second. If the altitude change rate is detected to suddenly reach ±10 meters per second or more, this may indicate that the aircraft has abnormal control or encountered an emergency (such as strong airflow interference or failure), and the electronic fence positioning system will use this as an important early warning quantitative feature.

[0020] The distance between the aircraft and the geo-fence boundary is a quantitative feature that directly affects whether there is an intrusion risk. Set a distance threshold, such as when the aircraft is less than 500 meters from the geo-fence boundary, the system begins to increase the warning level. As the distance decreases further, such as less than 100 meters, the warning level will reach the highest level, which may trigger direct control measures.

[0021] In addition, the angle between the aircraft's heading and key areas within the electronic fence (such as the direction of the airport runway, the direction of military facilities, etc.) can also be used as a quantitative feature. If the angle is within ±30° and the aircraft is approaching, the system will give a corresponding warning, because this may mean that the aircraft has a potential intrusion risk.

[0022] Step 120: The electronic fence positioning system obtains the spatiotemporal cross-sensing data of a plurality of electronic fence monitoring routes and the electronic fence monitoring routes for implementing flight monitoring, and determines at least two local flight tracking control areas based on the spatiotemporal cross-sensing data.

[0023] Next, the electronic fence positioning system obtains the electronic fence monitoring route and time-space cross-perception data to determine the local flight tracking and control area.

[0024] The electronic fence monitoring route in the electronic fence positioning system is a path planning for effective monitoring of low-altitude flights. For a large low-altitude flight fence space to be monitored, such as an area containing multiple airports and city centers, multiple electronic fence monitoring routes may be planned. These routes may be determined based on geographical layout and flight traffic distribution. For example, around the airport, the monitoring route may be set along the extension line in the direction of the runway and within a certain range perpendicular to the runway. For example, at an airport with a runway length of 3 kilometers, its monitoring route extends 2 kilometers on both sides of the runway and is distributed in a grid pattern within a width of 1 kilometer to ensure comprehensive monitoring of aircraft entering and leaving the airspace around the airport.

[0025] In the city center, monitoring routes may be planned along passages between major high-rise buildings, over large parks, etc., to accommodate possible flight paths of drones in the city. For example, three parallel monitoring routes are set up over a large park in the city that is 1 km wide and 5 km long, with each route spaced 500 meters apart, to monitor drones operating in the area.

[0026] In addition, the spatiotemporal cross-sensing data is obtained through a variety of positioning technologies and sensors. For example, the high-precision GPS positioning technology combined with the auxiliary positioning of the ground base station is used to obtain the position information (longitude, latitude and altitude) of the aircraft every 1 second. In the time dimension, the flight trajectory is formed by continuous positioning data points. At the same time, in the spatial dimension, there will be cross-sensing areas between different monitoring routes. For example, two adjacent monitoring routes, Route A and Route B, will have overlapping parts in a certain area. When the aircraft enters the overlapping area from Route A and then enters Route B, the system will record the relevant data of this spatiotemporal intersection, including the aircraft's speed, direction, time of entering and leaving the intersection area, etc.

[0027] In addition to positioning data, photoelectric and thermal imaging technologies are also used to obtain time-space cross-sensing data. For example, in a monitoring area, the 360-degree panoramic detection system performs scanning imaging every 5 seconds. When the aircraft moves between different monitoring routes, through the analysis of continuous imaging data, the spatial position of the aircraft at different times and its dynamic changes relative to the monitoring route can be obtained, such as the direction from which the aircraft approaches or leaves the intersection area.

[0028] On the basis of the above, according to the spatial-temporal intersection perception data, the electronic fence positioning system determines the local flight tracking control area. For example, in the electronic fence monitoring area around an airport, according to the distribution of monitoring routes and the spatial-temporal intersection of aircraft between routes, the 3 km range at both ends of the airport runway and the 1.5 km range on both sides of the runway are divided into a local flight tracking control area. This is because the activities of aircraft in this area are closely related to the take-off and landing safety of the airport, and it is a key monitoring area.

[0029] Around large-scale event venues in cities (such as a stadium with a radius of 2 kilometers), based on the monitoring routes and the aircraft's spatiotemporal cross-sensing data, the airspace above the stadium with a radius of 1 kilometer and an altitude of 200-500 meters is divided into a local flight tracking and control area. In this area, the activities of aircraft may affect the safety and order of the event and require key tracking and control.

[0030] Step 130: The electronic fence positioning system determines the monitoring and warning data of each electronic fence monitoring route in the at least two local flight tracking and control areas based on the several flight warning quantitative characteristics; there are differences in the monitoring and warning data of the electronic fence monitoring routes in different route tasks in the same local flight tracking and control area.

[0031] In this step, the electronic fence positioning system determines the monitoring warning data based on the flight warning quantitative characteristics.

[0032] In the local flight tracking and control area around the airport, the monitoring and alarm data settings for the electronic fence monitoring route are relatively strict. Taking the distance between the aircraft and the electronic fence boundary as an example, when the aircraft is less than 100 meters away from the electronic fence boundary near the runway, the monitoring and alarm data will trigger the highest level of alarm, which may cause the system to directly send a forced return instruction to the aircraft or notify ground security personnel to intervene.

[0033] In the local flight tracking control area of ​​a large urban event venue, the monitoring and warning data of the aircraft's altitude change rate will be different. For example, under normal circumstances, the aircraft's altitude change rate in this area is allowed to be ±3 meters / second. If this threshold is exceeded, such as reaching ±5 meters / second, the monitoring and warning data will trigger an intermediate alarm, and the system will send a warning message to the aircraft operator, prompting him to adjust the flight status.

[0034] Regarding the speed of the aircraft, in the monitoring routes around the airport, if the aircraft speed exceeds the normal range (such as a small civilian drone exceeding 30 meters per second near the runway area), the monitoring alarm data will trigger a high-level alarm. In the monitoring routes in the general area of ​​the city, the speed threshold may be set to 40 meters per second, and only when the speed exceeds this will the corresponding level of alarm be triggered.

[0035] Furthermore, in the local flight tracking and control area around the airport, different route missions have different monitoring and warning data requirements. For example, for the electronic fence monitoring route specifically used to monitor the airport approach channel, the angle between the aircraft's heading and the channel direction is a key monitoring and warning data indicator. If the angle is within ±10° and the aircraft is approaching the approach channel, a high-level alarm will be triggered because it may cause serious interference to the aircraft about to land or take off.

[0036] For other electronic fence monitoring routes around the airport that are used to monitor the safety of the surrounding airspace, the relationship between the aircraft's altitude and the airport's airspace altitude limit is more important. For example, the airport's airspace altitude limit is 800 meters. When the aircraft's altitude exceeds 700 meters in the monitoring route area, the monitoring alarm data will trigger a corresponding alarm to remind the aircraft to lower its altitude.

[0037] In the local flight tracking control area of ​​a large urban event venue, the horizontal position accuracy of the aircraft is required to be higher for the electronic fence monitoring route close to the stage performance area. If the aircraft deviates from the set route in the horizontal direction by more than 10 meters, the monitoring alarm data will trigger a higher level of alarm to prevent the aircraft from accidentally entering the performance area. For the monitoring route far away from the performance area, the horizontal position deviation threshold may be set to 20 meters to trigger an alarm.

[0038] Step 140: In response to the low-altitude aircraft triggering the electronic fence positioning and tracking condition, the electronic fence positioning system determines the monitoring risk decision feature corresponding to the low-altitude aircraft based on the monitoring alarm data of the low-altitude aircraft; and uses the monitoring risk decision feature to perform flight control processing on the low-altitude aircraft.

[0039] It is understandable that when a low-altitude aircraft triggers the electronic fence positioning and tracking conditions, for example, when the aircraft enters an area within 100 meters of the electronic fence boundary near the airport runway, the electronic fence positioning system determines the monitoring risk decision features based on the previously set monitoring alarm data. At this time, the monitoring risk decision features may include high risk level, intrusion direction (such as approaching from the side of the runway), aircraft type (for example, the aircraft signal is identified as a small civilian drone), etc.

[0040] If the altitude change rate of an aircraft suddenly reaches ±10 m / s and exceeds the set threshold within the local flight tracking and control area of ​​a large urban event venue, the monitoring risk decision features may include medium risk level, abnormal altitude change, the current position of the aircraft (determined by positioning technology to be above the center of the event venue), etc.

[0041] Based on the above, according to the monitoring risk decision-making characteristics, the electronic fence positioning system implements flight control processing. For small civilian drones that are judged to be high-risk near airport runways, the system may take a variety of control measures. First, an emergency stop command is sent to the operator of the drone through a wireless communication link. If the operator does not respond within a certain period of time (such as 10 seconds), the system will activate the jamming device to interfere with the communication and navigation signals of the drone, causing it to land or lose control (under the premise of legality, compliance and ensuring safety).

[0042] At large-scale urban event venues, if the aircraft is judged to be of medium risk, the system will first send a warning message to the operator and adjust the monitoring frequency, for example, from positioning once every 5 seconds to once every 1 second, and pay close attention to the subsequent status of the aircraft. If the aircraft continues to remain in an abnormal state, such as the altitude change rate continues to increase, the system may limit the flight range of the aircraft to a smaller area (such as a circular area with a radius of 50 meters centered on the current position) until it resumes normal flight status or lands.

[0043] It can be seen that this application realizes the basis for refined management of low-altitude flight by constructing low-altitude flight fence space and setting quantitative characteristics of flight warning. Obtaining electronic fence monitoring routes and their spatiotemporal cross-perception data to determine local control areas helps to accurately focus on airspace with different functions and risks and improve control efficiency. Determining the warning data of different monitoring routes based on the quantitative characteristics of flight warnings, and considering the differences in missions of different routes in the same area, it can adapt to complex and diverse flight scenarios and reduce misjudgments. Determining the monitoring risk decision characteristics and controlling the flight in response to the trigger conditions can promptly and specifically handle abnormal situations of low-altitude aircraft, effectively ensure the safety and order of low-altitude flights, and avoid potential threats to specific areas (such as airports, event venues, etc.).

[0044] To facilitate understanding of the above technical solution, a complete application scenario example is used below to introduce and explain it.

[0045] During an international air show in a large city, strict flight control is required in the surrounding low-altitude airspace to ensure the smooth progress of the air show and airspace safety.

[0046] First, construct the low-altitude flight fence space to be monitored and set the quantitative characteristics of flight warning. The airspace with a radius of 10 kilometers and an altitude from the ground to 1,000 meters is designated as the low-altitude flight fence space to be monitored, with the air show venue as the center. The quantitative characteristics of flight warning are set as follows: In terms of speed, the normal speed range of ordinary civil drones is set to 10-50 meters / second, and if it exceeds 60 meters / second, it is considered abnormal; the altitude change rate is normal within ±5 meters / second, and an alarm is issued if it exceeds ±10 meters / second; the alarm starts when the distance to the fence boundary is less than 500 meters, and it is high risk when it is less than 100 meters.

[0047] Next, obtain the electronic fence monitoring routes and time-space cross perception data to determine the local flight tracking control area. Plan multiple electronic fence monitoring routes, such as setting a route every 1 km in the direction of the runway extension and vertical direction. Use high-precision positioning technology (GPS, Beidou satellite navigation system and ground wireless positioning technology) to obtain aircraft position information every 1 second, and use the 360-degree panoramic detection system combined with optoelectronic and thermal imaging technology to scan and image every 5 seconds to obtain time-space cross perception data between routes. Based on these data, the area of ​​3 km at both ends of the main runway of the air show, 2 km on both sides, and 500 meters above the ground is determined as a local flight tracking control area, and the airspace with a radius of 2 km and an altitude of 300-800 meters above the audience area is determined as another local flight tracking control area.

[0048] Then, the monitoring and warning data is determined based on the quantitative characteristics of the flight warning. In the local flight tracking and control area of ​​the main runway, for the electronic fence monitoring route close to the runway, when the angle between the aircraft and the runway is within ±10° and close, a high-level warning is triggered; and in the local flight tracking and control area above the audience area, when the aircraft altitude deviates from the range of 300-800 meters, the corresponding warning is triggered.

[0049] When a low-altitude aircraft triggers the electronic fence positioning and tracking conditions, such as a drone entering the local flight tracking control area of ​​the main runway and being less than 100 meters away from the runway, its monitoring risk decision characteristics are determined to be high risk, the intrusion direction is perpendicular to the runway, and the aircraft type is a small civilian drone based on its monitoring alarm data. Using these monitoring risk decision characteristics, the system sends an emergency stop command through 5G-A synaesthesia technology. If there is no response within 10 seconds, after positioning using sensor technology (infrared sensor, microwave sensor), the security personnel are coordinated with big data and cloud platforms to conduct visual confirmation and take further measures, such as activating interference equipment to prevent it from interfering with the flight performances at the air show. Throughout the process, multiple technologies work together to ensure the safe management of low-altitude airspace.

[0050] In a low-altitude airspace management scenario in a large city, the high-precision electronic map module and electronic fence used by the aircraft's flight control system belong to a flight cloud control management platform. The following is another application scenario description.

[0051] There are many areas in the city that need to be protected and managed, such as airports, large-scale event venues, and important government facilities. First, construct several low-altitude flight fence spaces to be monitored and set several flight warning quantitative features. For example, taking the area around the airport as an example, the airspace with a radius of 10 kilometers around the airport runway and an altitude from the ground to 1,500 meters is defined as a low-altitude flight fence space to be monitored. The flight warning quantitative features include the speed of the aircraft. The normal speed of civil drones is set between 10-50 meters / second. If it exceeds 60 meters / second, it is considered abnormal; the altitude change rate is normal within ±5 meters / second, and it is considered abnormal if it exceeds ±10 meters / second; the warning starts when the distance from the fence boundary is less than 500 meters, and it is high risk when it is less than 100 meters.

[0052] Then, the spatiotemporal cross perception data between several electronic fence monitoring routes and electronic fence monitoring routes used for flight monitoring are obtained, and at least two local flight tracking control areas are determined based on the spatiotemporal cross perception data. The flight cloud control management platform uses a high-precision electronic map module to plan the electronic fence monitoring routes, which cover the entire low-altitude flight fence space to be monitored. For example, a main monitoring route is set in the direction of the airport runway, and an auxiliary monitoring route is set in the direction perpendicular to the runway. The location information is sent to the flight cloud control management platform every 1 second through the positioning system on the aircraft (such as GPS, Beidou, etc.), and the spatiotemporal cross perception data between the electronic fence monitoring routes is obtained in combination with the detection data of optoelectronic and thermal imaging technology. If it is found that the aircraft traffic between two routes is large and the spatial distance is close, the airspace near them is determined as a local flight tracking control area, such as the airspace within 3 kilometers at both ends of the runway and within 2 kilometers on both sides of the runway is determined as a local flight tracking control area; the area around the airport far away from the runway, mainly where logistics drones are active, is determined as another local flight tracking control area.

[0053] Then, the monitoring and warning data of each electronic fence monitoring route in the at least two local flight tracking and control areas are determined based on the several flight warning quantitative characteristics, and the monitoring and warning data of the electronic fence monitoring routes in different route tasks in the same local flight tracking and control area are different. In the local flight tracking and control area near the runway, for the electronic fence monitoring route directly facing the runway, since the invasion of the aircraft will pose a serious threat to the take-off and landing of the aircraft, when the angle between the aircraft and the runway is within ±10° and close, regardless of whether the speed is normal, a high-level alarm is triggered; and for the electronic fence monitoring route that assists in monitoring the safety of the airspace around the runway, the alarm is triggered only when the aircraft altitude exceeds 1000 meters (the preset altitude limit in this area). In the local flight tracking and control area where logistics drones are active frequently, the main focus is on the aircraft speed and load. If the speed exceeds 50 meters / second or the load exceeds the preset value (set according to different types of drones), an alarm is triggered.

[0054] When a low-altitude aircraft triggers the electronic fence positioning and tracking conditions, the monitoring risk decision features corresponding to the low-altitude aircraft are determined based on the monitoring alarm data of the low-altitude aircraft, and the low-altitude aircraft is subjected to flight control processing using the monitoring risk decision features. For example, a civilian UAV triggers the electronic fence positioning and tracking conditions within ±10° and close to the runway in a local flight tracking and control area close to the runway. The flight cloud control management platform determines that its monitoring risk decision features are high risk, the intrusion direction is toward the runway, and the aircraft type is a small civilian UAV, etc. based on the previously set monitoring alarm data. Then, these monitoring risk decision features are used to perform flight control processing on the UAV, such as sending an emergency stop command to the UAV flight control system through wireless communication. If the UAV does not respond, the flight cloud control management platform can combine the high-precision electronic map module information to command nearby security UAVs to intercept or guide ground security personnel to intervene to ensure the safety of the airport airspace. During the entire process, the high-precision electronic map module and electronic fence used in the aircraft's flight control system are all part of a flight cloud control management platform, making data interaction faster and more accurate, thereby improving the efficiency and safety of the entire low-altitude flight management.

[0055] In an optional embodiment, determining at least two local flight tracking control areas based on the spatiotemporal cross-perception data includes: generating an original global flight tracking control area based on the spatiotemporal cross-perception data between the electronic fence monitoring routes, wherein each electronic fence monitoring route is a control unit area in the original global flight tracking control area, and there is spatiotemporal cross-perception data between two electronic fence monitoring routes associated with the path pointer in the original global flight tracking control area; and processing the original global flight tracking control area through a set regional clustering model to obtain at least two local flight tracking control areas.

[0056] In low-altitude airspace management, it is of key significance to determine at least two local flight tracking and control areas based on spatio-temporal cross-perception data.

[0057] First, the original global flight tracking control area is generated based on the spatiotemporal cross-sensing data between the electronic fence monitoring routes. The electronic fence monitoring routes play an important role in the control of the entire low-altitude airspace. These routes are planned and determined through a variety of technical means. For example, in the air show scenario mentioned earlier, many electronic fence monitoring routes were planned based on the geographical environment around the air show venue, aviation activity needs, and safety considerations. Using high-precision positioning technology (such as GPS can provide positioning data accurate to meters per second, the Beidou satellite navigation system also has similar high-precision positioning capabilities, and ground wireless positioning technology supplements positioning accuracy in local areas), optoelectronic and thermal imaging technology (the 360-degree panoramic detection system scans and images every 5 seconds, which contains the location and trajectory information of the aircraft), and other technical means, the spatiotemporal cross-sensing data between the electronic fence monitoring routes are obtained. These data include information such as the position, speed, direction, and time of the aircraft when switching between different routes.

[0058] Each electronic fence monitoring route becomes a control unit area in the original global flight tracking control area, which means that each route represents a relatively independent area that is connected to other routes in the overall control system. For example, the monitoring route on the extension of the main runway of the air show and the monitoring route in the vertical direction will generate time-space cross-sensing data when the aircraft crosses from one direction to another. These data indicate the correlation between the two routes. There is time-space cross-sensing data between the two electronic fence monitoring routes associated with the path pointer in the original global flight tracking control area. The path pointer can be understood as a logical connection, which marks the possible transfer path of the aircraft between the two routes. For example, when an aircraft flies from a route close to the audience area to a route near the main runway, the two routes are connected through the path pointer, and the time-space cross-sensing data between them records various status information of the aircraft during this transfer process.

[0059] Then, the original global flight tracking control area is processed by the set regional clustering model to obtain at least two local flight tracking control areas. The regional clustering model is an algorithm-based analysis tool that can divide the original global flight tracking control area according to pre-set rules. For example, when setting the parameters of the regional clustering model, factors such as the spatial distance relationship between routes, the flow distribution of aircraft between routes, and the risk level corresponding to different routes can be considered. Taking the air show as an example, from the perspective of spatial distance relationship, if the distance between two routes is within 500 meters, it may be regarded as having a high correlation in the clustering model; from the perspective of aircraft flow distribution, if the transfer frequency of aircraft between two routes is high (for example, more than 10 aircraft transfer from one route to another per hour), then these two routes will tend to be classified into the same category in the clustering model; from the perspective of risk level, the risk level of routes close to the main runway is higher, and other high-risk routes around the main runway may be clustered together.

[0060] Specifically, for example, in the air show scenario, there are 10 electronic fence monitoring routes in the original global flight tracking control area. Through the analysis of spatiotemporal cross-sensing data, it is found that the frequency of aircraft transfers between routes 1, 2, and 3 is high, and they are close (the average distance is about 300 meters), and they are all related to the main performance area of ​​the air show (the risk level is high), then the regional clustering model may divide these three routes and their corresponding airspace into a local flight tracking control area. Routes 4, 5, and 6 may be relatively far away from the first three routes in space (the average distance is more than 1 kilometer), the flow of aircraft between these three routes is relatively low (the number of transfers per hour is less than 5), and they mainly cover the surrounding airspace of the audience area (the risk level is relatively low), then these three routes and their airspace will be clustered into another local flight tracking control area. In this way, the regional clustering model can reasonably divide the original global flight tracking control area according to multiple factors, and obtain at least two local flight tracking control areas, each of which has its own unique control needs and characteristics.

[0061] Applying the above embodiments, firstly, from the perspective of precise control, by analyzing the spatiotemporal cross-sensing data in detail, different local areas can be accurately divided, so that the control of each area is more targeted. For example, in the air show scenario, the control requirements and risk factors over the main runway area and the audience area are very different. This division method allows managers to more accurately formulate different control strategies for different areas, such as setting stricter aircraft speed and height limits in the main runway area (speed limit within 30 meters / second, height limit below 500 meters), while it can be relatively loose over the audience area (speed limit within 50 meters / second, height limit below 800 meters). Secondly, from the perspective of resource allocation, monitoring resources can be reasonably allocated according to the characteristics of different areas. For example, for the local flight tracking control area of ​​the main runway with large aircraft traffic and high risk, more high-precision positioning equipment (such as increasing the density of GPS and Beidou positioning base stations) and sensors (such as increasing the number of infrared sensors and microwave sensors) can be invested, while for the local flight tracking control area over the audience area, resource investment can be appropriately reduced. Furthermore, in terms of improving efficiency, this division method helps to quickly identify and handle abnormal situations in different areas. When an aircraft behaves abnormally in a local area, managers can quickly respond based on the characteristics and control strategies of the area, reducing the time cost of searching and judging in the entire global area. In short, this technical solution for determining local flight tracking and control areas provides important technical support for efficient, accurate and safe management of low-altitude airspace.

[0062] In a next preferred embodiment, the monitoring warning data of each electronic fence monitoring route in the at least two local flight tracking and control areas is determined based on the several flight warning quantitative characteristics, including: summarizing the control unit area in the u-th local flight tracking and control area into a first control unit area cluster and a second control unit area cluster, wherein the first control unit area cluster and the second control unit area cluster do not have the same control unit area, and the number of control unit areas in the first control unit area cluster and the second control unit area cluster is the same; constructing reversible path characteristics of the first control unit area cluster and the second control unit area cluster, wherein the first control unit area cluster and the second control unit area cluster are A first control unit area in a control unit area cluster corresponds one to one with a second control unit area in a second control unit area cluster; a trend simulation is performed on the plurality of flight warning quantitative characteristics to obtain a plurality of trend simulation description labels; a trend simulation description label corresponding to each first control unit area is determined from the plurality of trend simulation description labels; monitoring and alarm data corresponding to each first control unit area is determined based on the trend simulation description label corresponding to each first control unit area; a state inversion is performed on the monitoring and alarm data corresponding to each first control unit area to obtain monitoring and alarm data of the second control unit area corresponding to each first control unit area.

[0063] In the technical solution for low-altitude airspace management, determining the monitoring and warning data of each electronic fence monitoring route in at least two local flight tracking and control areas based on a number of flight warning quantitative characteristics is a complex and critical link.

[0064] First, the control unit areas in the u-th local flight tracking and control area are summarized into the first control unit area cluster and the second control unit area cluster. It is required here that there are no identical control unit areas in the first control unit area cluster and the second control unit area cluster, and the number of control unit areas in the two is the same. The purpose of this operation is to reasonably group the local flight tracking and control areas for more detailed analysis and processing later. For example, in a specific local flight tracking and control area, if there are 10 control unit areas, they can be evenly divided into two clusters, each containing 5 control unit areas. This division method helps to analyze and manage the control unit areas from different angles, and improve the accuracy and efficiency of management.

[0065] Then, the reversible path characteristics of the first control unit area cluster and the second control unit area cluster are constructed. Among them, the first control unit area in the first control unit area cluster corresponds to the second control unit area in the second control unit area cluster. The reversible path feature can be understood as a logical association relationship, which reflects the connection between the corresponding control unit areas in the two clusters. From an algorithmic point of view, this relationship can be represented by constructing a mapping function. For example, the control unit areas in the first control unit area cluster are represented by the set A={a1, a2, a3,...}, and the control unit areas in the second control unit area cluster are represented by the set B={b1, b2, b3,...}, then the reversible path feature can be represented by a mapping function f, so that f(ai)=bi and f-1(bi)=ai, where f-1 represents the inverse function of f. The construction of this reversible path feature is helpful for two-way information transmission and association analysis in subsequent analysis.

[0066] Then, trend simulation is performed on several flight warning quantitative features to obtain several trend simulation description labels. Flight warning quantitative features include multiple aspects, such as the speed of the aircraft, the rate of change of altitude, and the distance from the boundary of the electronic fence. Taking the speed of the aircraft as an example, for example, within a period of time (such as 10 minutes), the speed data of the aircraft is collected every 1 minute to obtain a speed data sequence {v1, v2, v3, ..., v10}. A linear regression algorithm can be used for trend simulation. Let the linear regression equation be y=kx+b, where x represents time (here the sequence number of the collected data can be used as the value of x, such as x=1, 2, 3, ...), y represents speed, k is the slope, and b is the intercept. The values ​​of k and b are calculated by the least squares method and other algorithms. According to the positive and negative and size of k, the trend simulation description label of the speed can be obtained, such as "the speed rises rapidly" (when k>0 and the absolute value of k is large), "the speed is basically stable" (when k is close to 0) or "the speed decreases" (when k<0). Similar methods are used to perform trend simulation on other flight warning quantitative characteristics such as altitude change rate and distance from the electronic fence boundary to obtain corresponding trend simulation description labels.

[0067] Determine the trend simulation description label corresponding to each first control unit area from a number of trend simulation description labels. This step needs to be matched based on the actual flight data of the aircraft in each first control unit area and the trend simulation description label obtained previously. For example, for a first control unit area, if the trend simulation description label of the speed of the aircraft in the area is "speed rises rapidly", the trend simulation description label of the altitude change rate is "altitude stable", and the trend simulation description label of the distance from the electronic fence boundary is "distance gradually decreases", then these labels are determined as the trend simulation description labels corresponding to the first control unit area.

[0068] The monitoring alarm data corresponding to each first control unit area is determined according to the trend simulation description label corresponding to each first control unit area. This process requires the establishment of an alarm data determination rule. For example, when the speed trend simulation description label is "speed increases rapidly" and the speed exceeds the preset speed threshold (such as the preset speed upper limit in this area is 30 meters / second, the actual speed rises to 35 meters / second and the trend is rapid increase), the trend simulation description label of the altitude change rate is "altitude stable" (altitude stability is normal in this area and no additional alarm is triggered), and the trend simulation description label of the distance to the electronic fence boundary is "distance gradually decreases" and the distance is less than the preset distance threshold (such as the preset distance threshold is 500 meters, and the actual distance decreases to 400 meters), then it can be determined that the monitoring alarm data corresponding to the first control unit area is "medium-level alarm", which may trigger a warning message to be sent to the aircraft to remind the operator to adjust the flight status.

[0069] Finally, the monitoring and alarm data corresponding to each first control unit area are state inverted to obtain the monitoring and alarm data of the second control unit area corresponding to each first control unit area. The state inversion is based on the reversible path characteristics of the first control unit area cluster and the second control unit area cluster constructed previously. Since there is a one-to-one correspondence between the first control unit area and the second control unit area, the monitoring and alarm data of the second control unit area can be obtained by state inversion based on the monitoring and alarm data of the first control unit area through a certain algorithm. For example, if the monitoring and alarm data of the first control unit area is a "medium level alarm", according to the reversible path characteristics and the pre-set state inversion rules (which may be rules set according to the correlation and similarity of the aircraft behavior between the two areas), it can be obtained that the corresponding monitoring and alarm data of the second control unit area is also a "medium level alarm".

[0070] With this design, from the perspective of accuracy, by simulating trends and conducting detailed analysis on the quantitative characteristics of flight warnings, the monitoring and warning data can be determined more accurately, reducing the possibility of misjudgment. For example, the warning level can be accurately judged based on the specific speed, altitude and distance trends to avoid erroneous warning judgments due to data at a single moment. In terms of management efficiency, by dividing the control unit area into two clusters and constructing reversible path features, after determining the monitoring and warning data of one cluster, the monitoring and warning data of another cluster can be obtained through state inversion, reducing the amount of calculation and management complexity. For example, when dealing with a large number of control unit areas, there is no need to perform a complex warning data determination process for each area separately, which improves the overall management efficiency. At the same time, this method helps to grasp the flight status within the local flight tracking control area as a whole, and better ensure the safety management of low-altitude airspace.

[0071] Further, the method of summarizing the control unit areas in the u-th local flight tracking and control area into the first control unit area cluster and the second control unit area cluster includes: obtaining the control unit area statistical value in the u-th local flight tracking and control area, wherein u is an integer greater than or equal to 1 and less than or equal to P, P is the statistical value of the local flight tracking and control area, and P is an integer greater than 1; in response to the control unit area statistical value being a first type of value, equally dividing the control unit areas in the u-th local flight tracking and control area into the first control unit area cluster and the second control unit area cluster; in response to the control unit area statistical value being a second type of value, arbitrarily selecting a target control unit area from the u-th local flight tracking and control area; and equally dividing the remaining control unit areas in the u-th local flight tracking and control area except the target control unit area into the first control unit area cluster and the second control unit area cluster.

[0072] In the further elaboration of the technical solution for low-altitude airspace management, grouping the control unit areas in the u-th local flight tracking control area into the first control unit area cluster and the second control unit area cluster is an important part with specific logic and operation procedures.

[0073] First, obtain the statistical value of the control unit area in the u-th local flight tracking control area. Here u is an integer within a specific range, and the value range of u is greater than or equal to 1 and less than or equal to P, where P represents the statistical value of the local flight tracking control area, and P is an integer greater than 1. This means that there are multiple (P) local flight tracking control areas in the entire low-altitude airspace management system, and the electronic fence positioning system is currently focusing on the u-th area. For example, if P=5, it means that there are a total of 5 local flight tracking control areas. When u=3, the electronic fence positioning system is performing relevant operations on the third local flight tracking control area.

[0074] When the statistical value of the control unit area is the first type of value, the control unit area in the u-th local flight tracking control area is evenly divided into the first control unit area cluster and the second control unit area cluster. The so-called first type of value here can be a predefined value that meets specific conditions. For example, if the first type of value is defined as an even number, for example, the statistical value of the control unit area in the u-th local flight tracking control area is 10 (satisfying the condition that the first type of value is an even number), then these 10 control unit areas are evenly distributed to the first control unit area cluster and the second control unit area cluster, that is, each cluster contains 5 control unit areas. From an algorithmic point of view, assuming that the statistical value of the control unit area is n (in this example n=10), the number of control unit areas contained in the first control unit area cluster is m1=n / 2=10 / 2=5, and the number of control unit areas contained in the second control unit area cluster is also equal to 5.

[0075] When the statistical value of the control unit area is a second-class value, select any target control unit area from the u-th local flight tracking control area. The second-class value here is also a pre-defined value type that is different from the first-class value. For example, if the second-class value is defined as an odd number, for example, the statistical value of the control unit area in the u-th local flight tracking control area is 9 (satisfying the condition that the second-class value is an odd number). At this time, select any one of the 9 control unit areas as the target control unit area, such as selecting the 3rd control unit area as the target control unit area.

[0076] Then, the remaining control unit areas except the target control unit area in the u-th local flight tracking control area are evenly divided into the first control unit area cluster and the second control unit area cluster. In the above example, after removing the third control unit area, there are 8 control unit areas left. These 8 control unit areas are evenly distributed into two clusters, and the number of control unit areas contained in each cluster is 8 / 2=4. From the algorithm point of view, let the statistical value of the control unit area be n (here n=9), and the target control unit area be k (here k=3), then the number of remaining control unit areas n'=n-1=9-1=8. The number of control unit areas contained in the first control unit area cluster is m1=n' / 2=8 / 2=4, and the number of control unit areas contained in the second control unit area cluster is m2, which is also equal to 4.

[0077] From the perspective of balance, when the statistical value of the control unit area is the first type of value (such as an even number), the control unit area is evenly distributed to two clusters, so that the two clusters are balanced in terms of control resource allocation and subsequent analysis and calculation. For example, when calculating monitoring and alarm data and other operations, the processing scale of the two clusters is the same, which helps to improve processing efficiency. When the statistical value of the control unit area is the second type of value (such as an odd number), by excluding a target control unit area and then evenly dividing the remaining area, the two clusters are kept as close in scale as possible to reduce the management imbalance caused by the difference in the number of regions. In terms of flexibility, this method of performing different operations according to different statistical values ​​of the control unit area can adapt to different local flight tracking control area structures. Whether the number of control unit areas in the area is an even number or an odd number, the regional clusters can be effectively divided, which provides a stable foundation for subsequent operations such as constructing reversible path features and determining monitoring and alarm data, thereby contributing to the effective implementation of the overall low-altitude airspace management plan and the improvement of management efficiency.

[0078] In other preferred embodiments, determining the monitoring and alarm data corresponding to each first control unit area based on the trend simulation description label corresponding to each first control unit area includes: obtaining X flight warning quantitative features included in the trend simulation description label corresponding to the vth first control unit area, X is an integer greater than 1, v is an integer greater than or equal to 1 and less than or equal to Q, Q is a statistical value of the first control unit area, and Q is an integer greater than 1; determining the 1st to Xth flight warning quantitative features in the trend simulation description label corresponding to the vth first control unit area as the monitoring and alarm weights for associating the 1st to Xth low-altitude flight fence spaces to be monitored to the vth first control unit area.

[0079] Based on this, the monitoring and alarm data corresponding to each first control unit area are state inverted to obtain the monitoring and alarm data of the second control unit area corresponding to each first control unit area, including: according to the monitoring and alarm data corresponding to the vth first control unit area, the 1st to Xth low-altitude flight fence spaces to be monitored are sorted in ascending order of monitoring and alarm weights to obtain the sorted X low-altitude flight fence spaces to be monitored; the X flight warning quantitative features are sorted in descending order to obtain the sorted X flight warning quantitative features; the sorted 1st to Xth flight warning quantitative features are determined as the monitoring and alarm weights for associating the sorted 1st to Xth low-altitude flight fence spaces to be monitored to the vth second control unit area corresponding to the vth first control unit area.

[0080] In the in-depth explanation of the low-altitude airspace management technical solution, there is a specific operating procedure and logical basis for determining the monitoring alarm data corresponding to each first control unit area based on the trend simulation description label corresponding to each first control unit area.

[0081] First, obtain the X flight warning quantitative features included in the trend simulation description label corresponding to the vth first control unit area. Here, v is an integer within a specific range, and its value range is greater than or equal to 1 and less than or equal to Q, where Q is the statistical value of the first control unit area, and Q is greater than 1. For example, if Q=5, it means that there are 5 first control unit areas. When v=3, the electronic fence positioning system focuses on the third first control unit area. X is an integer greater than 1. For example, X=3 means that the trend simulation description label corresponding to this vth first control unit area contains 3 flight warning quantitative features, such as the three flight warning quantitative features of aircraft speed, altitude change rate, and distance from the electronic fence boundary.

[0082] The 1st to Xth flight warning quantitative features in the trend simulation description label corresponding to the vth first control unit area are determined as the monitoring warning weights for associating the 1st to Xth low-altitude flight fence space to be monitored to the vth first control unit area. For example, for the third first control unit area mentioned above (v=3), for example, the three flight warning quantitative features are aircraft speed (expressed by v_s), altitude change rate (expressed by v_h), and distance from the electronic fence boundary (expressed by v_d). If under a specific algorithm or rule, the weight of the aircraft speed v_s is determined to be 0.3, the weight of the altitude change rate v_h is 0.2, and the weight of the distance from the electronic fence boundary v_d is 0.5. This means that when determining the monitoring warning data of the third first control unit area, the flight warning quantitative feature of the distance from the electronic fence boundary has the greatest influence on the monitoring warning data, followed by the aircraft speed, and the altitude change rate is relatively the smallest.

[0083] Based on this, when the monitoring and alarm data corresponding to each first control unit area is state inverted to obtain the monitoring and alarm data of the second control unit area corresponding to each first control unit area, there are a series of operations. According to the monitoring and alarm data corresponding to the vth first control unit area, the 1st to Xth low-altitude flight fence spaces to be monitored are sorted in ascending order of monitoring and alarm weights to obtain the sorted X low-altitude flight fence spaces to be monitored. Continuing with the above example, if the monitoring and alarm data corresponding to the third first control unit area (v=3) is a certain state (for example, a medium-risk state), the low-altitude flight fence spaces to be monitored are sorted in ascending order according to the previously determined weights (0.2, 0.3, 0.5). For example, the low-altitude flight fence spaces to be monitored are S1, S2, and S3, respectively, and the corresponding weights are 0.2, 0.3, and 0.5, respectively, then the sorted order is S1, S2, and S3.

[0084] Next, the X flight warning quantitative features are sorted in descending order to obtain the sorted X flight warning quantitative features. In the previous example, the three flight warning quantitative features (aircraft speed v_s, altitude change rate v_h, distance from the electronic fence boundary v_d) are sorted in descending order according to the previously set weights (0.3, 0.2, 0.5) to v_d, v_s, and v_h.

[0085] Finally, the sorted 1st to Xth flight warning quantitative features are determined as the monitoring and warning weights of associating the sorted 1st to Xth low-altitude flight fence spaces to be monitored to the vth second control unit area corresponding to the vth first control unit area. In this example, for the third second control unit area corresponding to the third first control unit area, the distance v_d from the electronic fence boundary becomes the monitoring and warning weight associated with S1, the aircraft speed v_s becomes the monitoring and warning weight associated with S2, and the altitude change rate v_h becomes the monitoring and warning weight associated with S3.

[0086] Based on the above embodiments, from the perspective of accuracy, by assigning weights to different flight warning quantitative features, and determining monitoring warning data and performing state inversion based on these weights, the actual risk status of each control unit area can be more accurately reflected. For example, according to the difference in importance of different flight warning quantitative features in different areas (such as the distance from the electronic fence boundary is more critical in some areas, while the speed of the aircraft is more critical in other areas), the warning level can be accurately judged to avoid misjudgments caused by simple and unified standards. From the perspective of relevance, the low-altitude flight fence space to be monitored is associated with the flight warning quantitative features through weights, and a close logical connection is established whether in the first control unit area or the second control unit area, so that the entire low-altitude airspace management system has coherence and consistency between different areas, which helps to improve overall management efficiency and safety.

[0087] In an alternative technical solution, the monitoring warning data of each electronic fence monitoring route in the at least two local flight tracking and control areas is determined based on the several flight warning quantitative characteristics, including: performing area marking processing on the at least two local flight tracking and control areas, and obtaining corresponding local flight tracking and control areas after at least two area markings, wherein the control limitation levels of two control unit areas associated with a path pointer in the local flight tracking and control area after area marking are different; obtaining the cumulative value W of the unit area limitation level in the local flight tracking and control area after the qth area marking, wherein q is an integer greater than or equal to 1 and less than or equal to P, P is a statistical value of the local flight tracking and control area, and P is greater than 1. integer; performing trend simulation on the plurality of flight warning quantitative features to obtain a plurality of trend simulation description labels; when W is a first-category value, obtaining 0.5*W trend simulation description labels from the plurality of trend simulation description labels; performing state inversion on the 0.5*W trend simulation description labels to obtain 0.5*W trend state inversion description labels; associating the 0.5*W trend simulation description labels and the 0.5*W trend state inversion description labels to W control unit areas of control limit levels, wherein a control unit area of ​​a control limit level corresponds to one trend simulation description label; determining the monitoring alarm data of each electronic fence monitoring route according to the trend simulation description label corresponding to each control unit area.

[0088] On the basis of this technical solution, the monitoring and alarm data of each electronic fence monitoring route in the at least two local flight tracking and control areas are determined, including: when W is a second-category value, obtaining 0.5*(W+1) trend simulation description tags from the plurality of trend simulation description tags; performing state inversion on 0.5*(W-1) trend simulation description tags among the 0.5*(W+1) trend simulation description tags to obtain 0.5*(W-1) trend state inversion description tags; associating the 0.5*(W+1) trend simulation description tags and the 0.5*(W-1) trend state inversion description tags to W control unit areas of control limit levels, wherein a control unit area of ​​a control limit level corresponds to one trend simulation description tag; and determining the monitoring and alarm data of each electronic fence monitoring route according to the trend simulation description tags corresponding to each control unit area.

[0089] In the description of the technical solution for low-altitude airspace management, this replaceable technical solution has unique logic and operation procedures for the key link of determining the monitoring and warning data of each electronic fence monitoring route in at least two local flight tracking and control areas based on a number of flight warning quantitative characteristics.

[0090] First, at least two local flight tracking and control areas are marked, and corresponding local flight tracking and control areas after at least two area markings are obtained. In the local flight tracking and control area after area marking, the control limit levels of two control unit areas associated with a path pointer are different. This setting helps to distinguish the control strictness or characteristics of different control unit areas, and lays the foundation for determining monitoring alarm data according to different situations in the future.

[0091] Then, the cumulative value W of the unit area restriction level in the local flight tracking and control area after the qth area is marked is obtained, where the value range of q is greater than or equal to 1 and less than or equal to P, where P is the statistical value of the local flight tracking and control area and P is greater than 1. For example, if P=3, it means there are 3 local flight tracking and control areas. When q=2, the electronic fence positioning system focuses on the cumulative value W of the unit area restriction level in the local flight tracking and control area after the second area is marked.

[0092] Then, trend simulation is performed on several flight warning quantitative features to obtain several trend simulation description labels. Flight warning quantitative features may include aircraft speed, altitude change rate, distance from the electronic fence boundary, etc. Taking aircraft speed as an example, if a series of speed data at time points are collected, such as the speeds at 10 time points are [v1, v2, v3, ..., v10], a linear regression algorithm can be used for trend simulation. Assume that the linear relationship between speed and time is v=mt+b (where v is speed, t is time, m is slope, and b is intercept), calculate the values ​​of m and b by the least squares method, and determine the trend simulation description label of speed according to the positive and negative and size of m, such as "speed rises faster" when m>0 and is larger, "speed is basically stable" when m is close to 0, and "speed decreases" when m<0. Similar algorithms are used to obtain the respective trend simulation description labels for other flight warning quantitative features.

[0093] When W is a first-class numerical value, 0.5*W trend simulation description labels are obtained from several trend simulation description labels. For example, if W=10 (satisfying the first-class numerical condition), 0.5*10=5 trend simulation description labels are obtained. Then, these 0.5*W trend simulation description labels are state inverted to obtain 0.5*W trend state inversion description labels. State inversion can be performed according to a pre-set logical relationship or algorithm. For example, for the trend simulation description label of speed "speed rises faster", if the state inversion rule is to reverse the speed trend, the trend state inversion description label after state inversion may be "speed decreases".

[0094] Then associate 0.5*W trend simulation description tags and 0.5*W trend state inversion description tags to the control unit areas of W control limit levels, and one control unit area of ​​one control limit level corresponds to one trend simulation description tag. For example, the control limit levels from low to high are L1, L2, ..., L10 (W=10), and 5 trend simulation description tags and 5 trend state inversion description tags correspond to the control unit areas of these 10 control limit levels in a certain order. For example, the trend simulation description tag "speed rises faster" is associated with the control unit area of ​​the control limit level L3.

[0095] Finally, the monitoring alarm data of each electronic fence monitoring route is determined based on the trend simulation description label corresponding to each control unit area. The determination rule can be based on predefined standards. For example, if the trend simulation description label associated with the control unit area is "speed rises quickly" and the current speed has approached or exceeded the preset speed limit, the monitoring alarm data of the electronic fence monitoring route corresponding to the control unit area is determined to be "high risk alarm", which may trigger the sending of an emergency stop command or other control measures to the aircraft.

[0096] When W is a second-class value, 0.5*(W+1) trend simulation description tags are obtained from several trend simulation description tags. For example, if W=9 (satisfying the second-class value condition), 0.5*(9+1)=5 trend simulation description tags are obtained. 0.5*(W-1) trend simulation description tags among these 0.5*(W+1) trend simulation description tags are state inverted to obtain 0.5*(W-1) trend state inversion description tags. That is, 0.5*(9-1)=4 trend simulation description tags are state inverted.

[0097] 0.5*(W+1) trend simulation description tags and 0.5*(W-1) trend state inversion description tags are associated with W control unit areas of control limit levels. Similarly, one control unit area of ​​one control limit level corresponds to one trend simulation description tag. Finally, the monitoring alarm data of each electronic fence monitoring route is determined based on the trend simulation description tags corresponding to each control unit area. The specific determination method is similar to when W is the first type of value.

[0098] It can be seen that from the perspective of accuracy, by adopting different trend simulation description label selection and state inversion methods according to different W values ​​(cumulative values ​​of unit area limit levels), the characteristic differences of different local flight tracking and control areas can be taken into account more carefully, so as to more accurately determine the monitoring and warning data. For example, different W values ​​reflect the overall situation of different areas in terms of control limit levels. Adjusting the method of determining monitoring and warning data according to this difference can avoid a one-size-fits-all judgment method and reduce the possibility of misjudgment. From the perspective of flexibility, this method of performing different operations according to different W values ​​can adapt to various complex low-altitude airspace structures and control requirements. Regardless of the type of local flight tracking and control area, the monitoring and warning data can be reasonably determined based on this scheme, which improves the adaptability of the entire low-altitude airspace management system to different situations and helps to ensure the safety and orderly management of low-altitude airspace.

[0099] In some exemplary embodiments, in response to a low-altitude aircraft triggering an electronic fence positioning and tracking condition, determining a monitoring risk decision feature corresponding to the low-altitude aircraft based on the monitoring alarm data of the low-altitude aircraft includes: in response to a low-altitude aircraft triggering an electronic fence positioning and tracking condition, obtaining a decision reference factor, wherein the value range of the decision reference factor is [0, 1]; determining a monitoring risk decision quadrant corresponding to each low-altitude flight fence space to be monitored based on the monitoring alarm data of the low-altitude aircraft; and determining the monitoring risk decision feature corresponding to the low-altitude aircraft based on the low-altitude flight fence space to be monitored corresponding to the monitoring risk decision quadrant where the decision reference factor is located.

[0100] In the in-depth explanation of the low-altitude airspace management technical solution, there is a rigorous operating procedure and logical relationship for the core link of responding to low-altitude aircraft triggering electronic fence positioning and tracking conditions, and determining the corresponding monitoring risk decision-making characteristics of the low-altitude aircraft based on the monitoring and alarm data of the low-altitude aircraft.

[0101] First, in response to the low-altitude aircraft triggering the electronic fence positioning and tracking conditions, a decision reference factor is obtained, and the value range of this decision reference factor is [0, 1]. This decision reference factor is a quantitative value that comprehensively reflects multiple factors, such as the historical flight data of the aircraft, the degree of compliance of the current flight status with the preset standards, and other factors. For example, the aircraft has slightly deviated from the route 3 times in the past 10 flights. In the current flight, the decision reference factor value is 0.3 based on the degree of deviation from the normal flight trajectory, speed stability, and other factors.

[0102] Determine the monitoring risk decision quadrants corresponding to each low-altitude flight fence space to be monitored based on the monitoring and warning data of low-altitude aircraft. The monitoring and warning data includes multiple aspects, such as the comparison of the aircraft's speed, altitude, distance from the boundary of the electronic fence, etc. with the preset standard values. Taking the aircraft speed as an example, if in a low-altitude flight fence space to be monitored, the preset normal speed range is 10 - 50 m / s, and the aircraft speed is 60 m / s, this constitutes a piece of monitoring and warning data in terms of speed. For example, the electronic fence positioning system uses the three main monitoring and warning data of the aircraft's speed, altitude, and distance from the boundary of the electronic fence as coordinate axes to construct a three-dimensional space. Each coordinate axis is divided into different intervals according to different risk levels, thereby dividing multiple monitoring risk decision quadrants. For example, the area where the speed is greater than 50 m / s, the altitude is higher than 10% of the preset upper limit, and the distance from the boundary of the electronic fence is less than 500 m can be divided into the first quadrant with high risk; the area where the speed is within the normal range, the altitude is within the normal range, but the distance from the boundary of the electronic fence is less than 1000 m can be divided into the second quadrant with medium risk, etc.

[0103] Based on the low-altitude flight fence space to be monitored corresponding to the monitoring risk decision quadrant where the decision reference factor is located, determine the monitoring risk decision characteristics corresponding to the low-altitude aircraft. Continuing with the above example, if the decision reference factor is 0.3 and this value falls within the low-altitude flight fence space to be monitored corresponding to the second quadrant with medium risk, then the monitoring risk decision characteristics corresponding to the low-altitude aircraft may include characteristics such as "medium risk level", "relatively close distance to the fence boundary but normal speed and altitude", etc. The specific determination of the monitoring risk decision characteristics can also be based on more predefined rules. For example, when in this quadrant and the corresponding low-altitude flight fence space to be monitored, if the type of the aircraft is a small civilian drone, then the monitoring risk decision characteristics may also include characteristics such as "higher maneuverability but vulnerable to interference" for the type of the aircraft.

[0104] From an algorithm perspective, for example, for the three monitoring and warning data of speed v, altitude h, and distance d from the boundary of the electronic fence, the electronic fence positioning system sets the following division rules to determine the quadrant:

[0105] For speed, when v > v_max (v_max is the preset maximum speed), the risk value r_v of the speed dimension = 1; when v_min <= v <= v_max (v_min is the preset minimum speed), r_v = 0; when v < v_min, r_v = 0.5.

[0106] For height, when h > h_max (where h_max is the preset maximum height), the risk value r_h in the height dimension is 1; when h_min <= h <= h_max (where h_min is the preset minimum height), r_h = 0; when h < h_min, r_h = 0.5.

[0107] For distance, when d < d_min (where d_min is the preset minimum distance), the risk value r_d in the distance dimension is 1; when d >= d_min, r_d = 0.

[0108] Then, a monitoring risk decision quadrant is determined through an exemplary weighted average formula: Q = (a * r_v + b * r_h + c * r_d), where a, b, and c are weight coefficients and a + b + c = 1. For example, if a = 0.4, b = 0.3, and c = 0.3, the quadrant is determined according to the interval where the calculated Q value lies.

[0109] Designed in this way, by comprehensively considering the decision reference factors and the monitoring risk decision quadrant constructed based on the monitoring alarm data to determine the monitoring risk decision characteristics, the risk status of low-altitude aircraft can be evaluated more accurately. For example, different decision reference factor values combined with the monitoring risk decision quadrant can distinguish different degrees of risk in detail, avoiding simply making judgments based on single alarm data. From the perspective of adaptability, this method can adapt to various types of aircraft and different flight scenarios. Whether it is drones with different performances or in different low-altitude airspace environments, the monitoring risk decision characteristics can be accurately determined according to this solution, thus providing a reliable basis for subsequent effective flight control processing and helping to improve the safety and rationality of low-altitude airspace management.

[0110] In some expandable embodiments, the method further includes: receiving a flight control network access application sent by a first flight control device corresponding to a first electronic fence monitoring route, where the flight control network access application includes the index of a first extended route to be networked and the index of a second electronic fence monitoring route; according to the index of the first extended route and the index of the second electronic fence monitoring route, sending a first response message to a second flight control device corresponding to the second electronic fence monitoring route, where the first response message carries the index of the first electronic fence monitoring route and the index of the first extended route; based on the selected second electronic fence monitoring route and the first extended route, adjusting the electronic fence control strategies of the first electronic fence monitoring route and the second electronic fence monitoring route.

[0111] In the further expansion and elaboration of the low-altitude airspace management technical solution, the method involved in this expandable embodiment has a complex and rigorous logical process.

[0112] First, receive the flight control network access application sent by the first flight control device corresponding to the first electronic fence monitoring route. The flight control network access application here contains important information, namely the index of the first extended route to be connected to the network and the index of the second electronic fence monitoring route. For example, the first electronic fence monitoring route that the first flight control device is responsible for may cover a specific airspace range. With the change of flight demand or the adjustment of airspace management, it is necessary to add the newly planned first extended route to the control network, and this extended route has some relationship with the second electronic fence monitoring route, so these two indexes are clearly stated in the flight control network access application.

[0113] According to the index of the first extended route and the index of the second electronic fence monitoring route, a first response message is sent to the second flight control device corresponding to the second electronic fence monitoring route. This first response message carries the index of the first electronic fence monitoring route and the index of the first extended route. The significance of this step is to establish a bridge of information communication and coordination between different flight control devices. For example, the first flight control device and the second flight control device may respectively control different but adjacent or related airspace areas. Through this information transmission, the second flight control device can know the relevant information of the first electronic fence monitoring route and the first extended route that is about to be connected to the network, so as to prepare for subsequent strategy adjustments.

[0114] In terms of specific algorithm operations, for example, the index of the first extended route is I1, the index of the second electronic fence monitoring route is I2, and the index of the first electronic fence monitoring route is I3. The association relationship between such indexes can be represented by an exemplary mapping function F. For example, F(I1, I2)=(I3, I1), which indicates that the indexes of the first electronic fence monitoring route and the first extended route to be carried in the first response information are determined according to the indexes of the first extended route and the second electronic fence monitoring route.

[0115] Based on the selected second electronic fence monitoring route and the first extended route, adjust the electronic fence control strategy of the first electronic fence monitoring route and the second electronic fence monitoring route. The screening process here may involve the consideration of multiple factors. For example, from the perspective of airspace safety, it is necessary to consider factors such as the obstacle distribution and surrounding aircraft traffic in the airspace where the first extended route and the second electronic fence monitoring route are located. In terms of control efficiency, it is necessary to evaluate the impact of the new route layout on the overall monitoring and management costs.

[0116] Taking the distribution of airspace obstacles as an example, if the airspace where the first extended route is located has many high-rise buildings (for example, the number of high-rise buildings is N, and when N>10, it is considered to be a large number), and the second electronic fence monitoring route is close to an airport (a highly sensitive area), then when adjusting the electronic fence control strategy, the height limit of the aircraft in these areas needs to be reset. For example, the original height limit of the airspace where the first electronic fence monitoring route is located is H1 (such as 500 meters-1000 meters). Due to the addition of the first extended route and its association with the second electronic fence monitoring route, the new height limit may be adjusted to H2 (such as 400 meters-800 meters).

[0117] From the perspective of aircraft traffic, if the aircraft traffic near the second electronic fence monitoring route is large (for example, the average number of aircraft passing per hour is M, and when M>50, it is considered that the traffic is large), the addition of the first extended route may change the aircraft traffic distribution. At this time, a traffic adjustment formula can be used to replan the control strategy. Suppose the original traffic distribution ratio is P1 (for example, the first electronic fence monitoring route accounts for 40% of the total traffic, and the second electronic fence monitoring route accounts for 60% of the total traffic), and the adjusted traffic distribution ratio is P2.

[0118] For example, if the basis for adjustment is based on the airspace capacity of the two routes (the airspace capacity of the first electronic fence monitoring route is C1, and the airspace capacity of the second electronic fence monitoring route is C2) and the impact factor α of the newly added first extended route on the traffic (for example, α=0.2, indicating that the first extended route will attract 20% of the traffic), the adjusted traffic distribution ratio can be calculated by the following formula:

[0119] For the first electronic fence monitoring route: P21=(P11*C1) / (C1+C2+α*(C1+C2));

[0120] For the second electronic fence monitoring route: P22 = (P12*C2) / (C1+C2+α*(C1+C2)).

[0121] Among them, P11 and P12 are the traffic allocation ratios of the first electronic fence monitoring route and the second electronic fence monitoring route before adjustment, and P21 and P22 are the traffic allocation ratios after adjustment.

[0122] This design allows flight control equipment to send flight control network access applications and corresponding responses and strategy adjustment mechanisms, which can flexibly adapt to the changing flight needs and route layout adjustments in low-altitude airspace. For example, when a new flight mission or aircraft type requires a specific route expansion, it is convenient to access the network and adjust the control strategy. From a collaborative perspective, this information interaction and strategy adjustment between different flight control devices helps to improve the collaborative working ability of the entire low-altitude airspace management system. The electronic fence monitoring routes in different areas can be coordinated and controlled according to their mutual connections and new route conditions, avoiding the management method of each doing its own thing and improving the overall efficiency and safety of airspace management. At the same time, by comprehensively considering multiple factors (such as airspace obstacles, aircraft traffic, etc.) for strategy adjustment, the special needs of different airspace areas can be met more accurately, further improving the scientificity and rationality of low-altitude airspace management.

[0123] In some other expandable embodiments, the method also includes: receiving flight control authentication information sent by the first flight control device corresponding to the first electronic fence monitoring route, the flight control authentication information including the index of the second extended route to be authenticated and the index of the third electronic fence monitoring route; based on the index of the second extended route and the index of the third electronic fence monitoring route, sending a second response information to the route monitoring middle station system corresponding to the third electronic fence monitoring route, the second response information carrying the index of the first electronic fence monitoring route and the index of the second extended route; when obtaining the route authentication pass prompt feedback from the route monitoring middle station system, sending the route recommendation information corresponding to the second extended route to the first flight control device; if the cross-simulation label of the first electronic fence monitoring route and the second extended route is a collaborative route label, adjusting the electronic fence control strategy of the first electronic fence monitoring route and the second electronic fence monitoring route.

[0124] In this embodiment, first, the flight control authentication information sent by the first flight control device corresponding to the first electronic fence monitoring route is received. This flight control authentication information includes the index of the second extended route to be authenticated and the index of the third electronic fence monitoring route. This indicates that the first flight control device sends an authentication request to the system for a second extended route to be authenticated and its association with the third electronic fence monitoring route in a specific low-altitude airspace management scenario. For example, the first electronic fence monitoring route that the first flight control device is responsible for may be set around a specific area (such as a large event venue in a city). With the development of the flight mission, it is necessary to authenticate the newly planned second extended route, and there is a certain logical connection between the extended route and the third electronic fence monitoring route, so these two indexes are explicitly included in the flight control authentication information.

[0125] According to the index of the second extended route and the index of the third electronic fence monitoring route, a second response message is sent to the route monitoring middle station system corresponding to the third electronic fence monitoring route. The second response message carries the index of the first electronic fence monitoring route and the index of the second extended route. The significance of this step is to establish an information transmission link between the first flight control device, the third electronic fence monitoring route and the route monitoring middle station system. For example, the index of the second extended route is I2, the index of the third electronic fence monitoring route is I3, and the index of the first electronic fence monitoring route is I1. Through an information mapping function M, M (I2, I3) = (I1, I2), the content in the second response message is determined. This process helps the route monitoring middle station system to obtain other route information related to the extended route to be authenticated, so as to perform accurate authentication evaluation.

[0126] When the route certification is passed from the route monitoring center system, the route recommendation information corresponding to the second extended route is sent to the first flight control device. The route recommendation information may contain a variety of content, such as suggestions on the second extended route in terms of flight altitude, speed limit, and avoidance rules with other routes. From an algorithmic point of view, for example, for the determination of the flight altitude limit of the second extended route, taking into account the average altitude H_avg of the surrounding airspace (for example, H_avg = 500 meters), and the highest obstacle height H_obstacle in the area (for example, H_obstacle = 200 meters), as well as the average flight altitude H_other of other aircraft around the route (for example, H_other = 300 meters), an exemplary formula can be used to determine the recommended lower limit H_min and upper limit H_max of the flight altitude:

[0127] H_min=H_avg-H_obstacle+50 (50 meters here is a safety margin);

[0128] H_max=H_avg+(H_other-H_avg)*0.8(0.8 here is an adjustment factor, which means appropriate increase based on the average flight altitude).

[0129] If the cross-simulation tag of the first electronic fence monitoring route and the second extended route is a collaborative route tag, the electronic fence control strategy of the first electronic fence monitoring route and the second electronic fence monitoring route is adjusted. The cross-simulation tag reflects the relationship between the two routes in the airspace. For example, when the cross-simulation tags of two routes are collaborative route tags, it means that they have a cooperative or complementary relationship in the flight mission.

[0130] When adjusting the electronic fence control strategy, multiple factors need to be considered. From the perspective of aircraft traffic, if the original aircraft traffic of the first electronic fence monitoring route is F1 (for example, the number of aircraft passing through per hour is 30 flights), and the estimated aircraft traffic in the airspace where the second extended route is located is F2 (for example, 20 flights are expected to pass through per hour), the control strategy of the two routes can be replanned based on a traffic allocation adjustment formula. Assuming the total airspace capacity is C (for example, C = 100 flights / hour capacity), the adjusted traffic allocation ratio P1' of the first electronic fence monitoring route and the traffic allocation ratio P2' of the second extended route can be calculated by the following formula:

[0131] P1'=F1*C / (F1+F2);

[0132] P2'=F2*C / (F1+F2).

[0133] From the perspective of airspace safety, if the safety risk coefficient of the airspace where the first electronic fence monitoring route is located is R1 (for example, it is 0.6 based on a comprehensive assessment of obstacles and meteorological conditions in the airspace, and the value range is 0-1, the higher the value, the higher the risk), and the safety risk coefficient of the airspace where the second extended route is located is R2 (for example, 0.4), then when adjusting the control strategy, some safety parameters can be reset according to a risk balance formula. For example, for the warning distance D of the electronic fence (indicates how close the aircraft is to the electronic fence when the alarm is issued), assuming that the warning distance of the original first electronic fence monitoring route is D1 (for example, 500 meters), and the warning distance of the original second extended route is D2 (for example, 800 meters), the adjusted warning distances D1' and D2' can be calculated by the following formula:

[0134] D1'=D1*(1-R2 / (R1+R2));

[0135] D2'=D2*(1-R1 / (R1+R2)).

[0136] In this way, through the sending and replying of flight control authentication information and the authentication process of the route monitoring middle system, it can be ensured that the newly expanded route meets the safety requirements of airspace management. For example, the provisions on flight altitude and other aspects in the route recommendation information are based on a detailed analysis of the surrounding airspace environment, which helps to avoid collisions between aircraft and obstacles or other aircraft. From the perspective of coordination, the control strategy adjustment made when the cross-simulation label of the first electronic fence monitoring route and the second extended route is a coordinated route label is conducive to improving the utilization efficiency of airspace resources. By reasonably adjusting the aircraft flow distribution ratio and safety parameters, the two routes can work better together, reduce mutual interference, and improve the operating efficiency and safety of the entire low-altitude airspace management system. At the same time, this strategy adjustment based on multiple factors (such as aircraft flow, airspace safety risks, etc.) makes the control strategy more scientific and accurate, and adapts to different airspace management needs.

[0137] Further, Figure 2 Schematic diagram of the structure of an electronic fence positioning system 200 provided in an embodiment of the present application. Figure 2 The electronic fence positioning system 200 shown includes a processor 210, and the processor 210 can call and run a computer program from a memory to implement the method in the embodiment of the present application.

[0138] Alternatively, if Figure 2 As shown, the electronic fence positioning system 200 may further include a memory 230. The processor 210 may call and run a computer program from the memory 230 to implement the method in the embodiment of the present application.

[0139] The memory 230 may be a separate device independent of the processor 210 , or may be integrated into the processor 210 .

[0140] Alternatively, if Figure 2 As shown, the electronic fence positioning system 200 may further include a transceiver 220, and the processor 210 may control the transceiver 220 to interact with other devices, specifically, to send information or data to other devices, or to receive information or data sent by other devices.

[0141] Optionally, the electronic fence positioning system 200 can implement the corresponding processes corresponding to the storage engine or components in the storage engine (such as a processing module) or a device deployed with a storage engine in each method of the embodiments of the present application. For the sake of brevity, they are not repeated here.

[0142] It should be understood that the processor of the embodiment of the present application may be an integrated circuit chip with signal processing capabilities.

[0143] It is understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memory. It should be noted that the memory of the systems and methods described herein is intended to include but is not limited to suitable types of memory.

[0144] Based on the above, a readable storage medium is provided, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the above method are implemented.

[0145] It should be noted that, in this article, the term "includes", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "including one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be noted that the scope of the method and device in the embodiment of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0146] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), including a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the embodiment of the present application.

[0147] The embodiments of the embodiments of the present application are described above in conjunction with the accompanying drawings, but the embodiments of the present application are not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the embodiments of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the embodiments of the present application and the scope of protection of the embodiments of the present application, all of which are within the protection of the embodiments of the present application.

Claims

1. An electronic fence positioning method applied to low-altitude flight control, characterized in that: The method is applied to an electronic fence positioning system, and the method comprises: Construct a number of low-altitude flight fence spaces to be monitored and set a number of flight warning quantitative features; Acquire a plurality of electronic fence monitoring routes and spatiotemporal cross perception data between the electronic fence monitoring routes for implementing flight monitoring, and determine at least two local flight tracking control areas based on the spatiotemporal cross perception data; Determine monitoring and warning data of each electronic fence monitoring route in the at least two local flight tracking and control areas according to the plurality of flight warning quantitative characteristics; there are differences in monitoring and warning data of electronic fence monitoring routes in different route tasks in the same local flight tracking and control area; In response to a low-altitude aircraft triggering an electronic fence positioning and tracking condition, a monitoring risk decision feature corresponding to the low-altitude aircraft is determined based on the monitoring alarm data of the low-altitude aircraft; and the low-altitude aircraft is subjected to flight control processing using the monitoring risk decision feature.

2. The method according to claim 1, characterized in that The determining of at least two local flight tracking control areas based on the spatiotemporal cross perception data includes: Generate an original global flight tracking control area based on the spatiotemporal cross perception data between the electronic fence monitoring routes, wherein each electronic fence monitoring route is each control unit area in the original global flight tracking control area, and there is spatiotemporal cross perception data between two electronic fence monitoring routes associated with the path pointer in the original global flight tracking control area; The original global flight tracking and control area is processed by a set regional clustering model to obtain at least two local flight tracking and control areas.

3. The method according to claim 1, characterized in that The step of determining the monitoring warning data of each electronic fence monitoring route in the at least two local flight tracking and control areas based on the plurality of flight warning quantitative characteristics includes: Summarize the control unit areas in the u-th local flight tracking control area into a first control unit area cluster and a second control unit area cluster, wherein the first control unit area cluster and the second control unit area cluster do not have the same control unit areas, and the first control unit area cluster and the second control unit area cluster have the same number of control unit areas; Constructing reversible path features of the first control unit area cluster and the second control unit area cluster, wherein the first control unit area in the first control unit area cluster corresponds one to one with the second control unit area in the second control unit area cluster; Performing trend simulation on the plurality of flight warning quantitative features to obtain a plurality of trend simulation description labels; Determine the trend simulation description label corresponding to each first control unit area from the plurality of trend simulation description labels; Determine the monitoring alarm data corresponding to each first control unit area according to the trend simulation description label corresponding to each first control unit area; State inversion is performed on the monitoring and alarm data corresponding to each of the first control unit areas to obtain monitoring and alarm data of the second control unit areas corresponding to each of the first control unit areas.

4. The method as claimed in claim 3, characterized in that The step of classifying the control unit areas in the u-th local flight tracking control area into a first control unit area cluster and a second control unit area cluster comprises: Obtaining the statistical value of the control unit area in the u-th local flight tracking control area, where u is an integer greater than or equal to 1 and less than or equal to P, P is the statistical value of the local flight tracking control area, and P is an integer greater than 1; In response to the control unit area statistical value being a first type of value, the control unit area in the u-th local flight tracking control area is evenly divided into a first control unit area cluster and a second control unit area cluster; In response to the control unit area statistical value being a second type of value, arbitrarily selecting a target control unit area from the u-th local flight tracking control area; The remaining control unit areas except the target control unit area in the u-th local flight tracking control area are equally divided into a first control unit area cluster and a second control unit area cluster.

5. The method as claimed in claim 3, characterized in that The determining the monitoring alarm data corresponding to each first control unit area according to the trend simulation description tag corresponding to each first control unit area includes: Get the X flight warning quantitative features included in the trend simulation description label corresponding to the vth first control unit area, where X is an integer greater than 1, v is an integer greater than or equal to 1 and less than or equal to Q, Q is the statistical value of the first control unit area, and Q is an integer greater than 1; The 1st to Xth flight warning quantitative features in the trend simulation description label corresponding to the vth first control unit area are determined as the monitoring warning weights for associating the 1st to Xth low-altitude flight fence spaces to be monitored to the vth first control unit area.

6. The method as claimed in claim 5, characterized in that The performing state inversion on the monitoring and alarm data corresponding to each of the first control unit areas to obtain the monitoring and alarm data of the second control unit areas corresponding to each of the first control unit areas includes: According to the monitoring alarm data corresponding to the vth first control unit area, the 1st to Xth low-altitude flight fence spaces to be monitored are sorted in ascending order of monitoring alarm weights to obtain the sorted X low-altitude flight fence spaces to be monitored; Arrange the X flight warning quantitative features in descending order to obtain the arranged X flight warning quantitative features; The sorted 1st to Xth flight warning quantitative features are determined as the monitoring warning weights of associating the sorted 1st to Xth low-altitude flight fence spaces to be monitored to the vth second control unit area corresponding to the vth first control unit area.

7. The method according to claim 1, characterized in that The step of determining the monitoring warning data of each electronic fence monitoring route in the at least two local flight tracking and control areas based on the plurality of flight warning quantitative characteristics includes: Performing area marking processing on the at least two local flight tracking and control areas, and correspondingly obtaining at least two local flight tracking and control areas after area marking, wherein two control unit areas associated with a path pointer in the local flight tracking and control areas after area marking have different control limitation levels; Obtain the cumulative value W of the unit area restriction level in the local flight tracking control area after the qth area is marked, where q is an integer greater than or equal to 1 and less than or equal to P, P is the statistical value of the local flight tracking control area, and P is an integer greater than 1; Performing trend simulation on the plurality of flight warning quantitative features to obtain a plurality of trend simulation description labels; When W is a first type of value, 0.5*W trend simulation description labels are obtained from the plurality of trend simulation description labels; Performing state inversion on the 0.5*W trend simulation description labels to obtain 0.5*W trend state inversion description labels; Associating the 0.5*W trend simulation description tags and the 0.5*W trend state inversion description tags to the control unit areas of W control limit levels, wherein one control unit area of ​​one control limit level corresponds to one trend simulation description tag; The monitoring alarm data of each electronic fence monitoring route is determined according to the trend simulation description label corresponding to each control unit area.

8. The method as claimed in claim 7, characterized in that The step of determining the monitoring alarm data of each electronic fence monitoring route in the at least two local flight tracking and control areas includes: When W is a second type of value, 0.5*(W+1) trend simulation description labels are obtained from the plurality of trend simulation description labels; Performing state inversion on 0.5*(W-1) trend simulation description labels among the 0.5*(W+1) trend simulation description labels to obtain 0.5*(W-1) trend state inversion description labels; Associating the 0.5*(W+1) trend simulation description tags and the 0.5*(W-1) trend state inversion description tags to the control unit areas of W control limit levels, wherein one control unit area of ​​one control limit level corresponds to one trend simulation description tag; The monitoring alarm data of each electronic fence monitoring route is determined according to the trend simulation description label corresponding to each control unit area.

9. The method according to claim 1, characterized in that In response to the low-altitude aircraft triggering the electronic fence positioning and tracking condition, determining the monitoring risk decision feature corresponding to the low-altitude aircraft according to the monitoring alarm data of the low-altitude aircraft, including: In response to the low-altitude aircraft triggering the electronic fence positioning and tracking condition, obtaining a decision reference factor, wherein the value interval of the decision reference factor is [0, 1]; Determine the monitoring risk decision quadrant corresponding to each low-altitude flight fence space to be monitored based on the monitoring warning data of the low-altitude aircraft; Based on the low-altitude flight fence space to be monitored corresponding to the monitoring risk decision quadrant where the decision reference factor is located, the monitoring risk decision characteristics corresponding to the low-altitude aircraft are determined.

10. An electronic fence positioning system, characterized in that: The method comprises at least one processor and a memory; the memory stores computer-executable instructions; the at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor executes the method according to any one of claims 1 to 9.

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