Low-altitude UAV detection and early warning method and device based on situation sharing

Abstract

The present invention provides a low-altitude UAV detection and early warning method and device based on situation sharing, which belongs to the field of air traffic management and flight supervision information technology. A fence space geometric model is established based on the collected sensitive airspace range data; active and passive multi-source joint detection and UTM‑ATM interoperability technology are used to effectively distinguish between legal and illegal UAVs; a comprehensive quantitative evaluation method for operation risk is established to conduct UAV threat level evaluation based on operation risk and trigger early warning alarms; a unified low-altitude air traffic panoramic situation view is constructed to realize situation sharing of airspace users. The present invention can effectively identify the legality of UAV flight activities; for illegal UAV activities, a comprehensive quantitative evaluation system for operation risk is established, and users are warned in time; real-time detection and analysis of UAVs in low-altitude airspace / alarm is realized, and security threats to other airspace users caused by illegal UAV intrusion are effectively prevented, and the requirements for low-altitude airspace situation sharing and continuous safety and stability are met.

Description

Technical Field

[0001] The present invention relates to the field of air traffic management and flight supervision information technology, and in particular to a low-altitude unmanned aerial vehicle detection and early warning method and device based on situation sharing. Background Art

[0002] In recent years, driven by technological advances in batteries, power, and other fields, the application scenarios and performance of civil drones have been greatly expanded and improved, and have gradually penetrated into the entire industry from logistics, emergency rescue, agriculture, forestry, animal husbandry, and fishery. According to statistics, nearly 99.9% of drones currently fly at altitudes below 1000m (inclusive), mainly using low-altitude airspace. Since the management of low-altitude drones is still in the exploratory stage, and the operating threshold of low-altitude drones is low and the flight control technology is still imperfect, the problem of "black flying" without registration and approval has occurred frequently, which has seriously affected the low-altitude flight order and public safety. In order to ensure the normal operation of air traffic activities, it is urgent to strengthen the identification and supervision of low-altitude drones.

[0003] However, low-altitude drones are usually small in size, low in altitude, flexible in operation, and difficult to predict. The detection distance and detection probability of traditional single-type detection methods are greatly limited, and targets may be missed. In addition, low-altitude airspace is an activity space where multiple types of airspace users, such as general aviation, unmanned aviation, and transport aviation (take-off and landing phase), involve multiple stakeholders, such as the civil aviation air traffic management system (Air Traffic Management, ATM) deployed in controlled airspace and the unmanned aircraft traffic management system (Unmanned Aircraft Systems Traffic Management, UTM) deployed in uncontrolled airspace. The risk of flight conflicts between multiple aircraft is high and the operation situation is complex. How to accurately identify and assess the risks of drones operating illegally in the airspace, issue timely warnings to the surrounding aircraft affected by them, and ensure that low-altitude airspace users have a comprehensive and unified perception and assessment of the complex situation in the airspace is a research difficulty in the field of air traffic management. Summary of the invention

[0004] The purpose of the present invention is to provide a low-altitude UAV detection and early warning method and device based on situation sharing, which can effectively realize the identification and supervision of low-altitude UAVs and the collaborative situation sharing of low-altitude airspace users, ensuring the continuous safety and stability of the low-altitude airspace, so as to solve at least one technical problem existing in the above-mentioned background technology.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] On the one hand, the present invention provides a low-altitude UAV detection and early warning method based on situation sharing, comprising the following steps:

[0007] Predefine low-altitude sensitive areas and establish a fence space geometry model based on the collected sensitive airspace range data. Among them, sensitive airspace specifically involves airport airspace protection areas (10 kilometers on both sides of the airport runway centerline and 20 kilometers at both ends of the runway), key sensitive units (such as military control areas), densely populated areas, etc. The airspace data includes latitude and longitude data, restricted altitude, restricted time and other information;

[0008] Active and passive multi-source joint detection and UTM-ATM interoperability technology are used to effectively distinguish between legal and illegal drones. UAV surveillance information is obtained through comprehensive detection of multiple interconnected active detection radars, wireless detection and positioning equipment, and optoelectronic detection systems, and compared with the information of authorized aircraft from the ATM and UTM systems to identify the legality of drone flight activities;

[0009] Conduct drone threat level assessment based on operational risk and trigger early warning alarms. Establish a comprehensive quantitative assessment method for operational risk based on factors such as drone weight, flight altitude interval, relative track convergence rate, and conflict intensity. Divide drone operational risk levels into three levels: low, medium, and high, and issue early warnings for drones with medium and high operational risks;

[0010] Realize the situation sharing of airspace users and build a unified panoramic view of low-altitude air traffic situation. Use air traffic information service broadcast and other means to send warning information to ATM and UTM related airspace users, assist users in obtaining comprehensive and clear air traffic information, and enhance the situation awareness of the operating airspace.

[0011] In a second aspect, the present invention provides a low-altitude UAV detection and early warning device based on situation sharing, including an airspace pre-definition module, a detection and identification module, a risk assessment module, and a situation sharing module; wherein:

[0012] The airspace pre-definition module is used to implement the fence space geometry modeling of low-altitude sensitive airspace, wherein the sensitive airspace includes airport clearance protection areas, key sensitive units, densely populated areas, etc., and the space geometry model includes polygonal and sector-shaped fences;

[0013] The detection and identification module is used to jointly identify the flight activities of unmanned aerial vehicles that are not authorized by the ATM / UTM system, and obtain the position and identification information of the unmanned aerial vehicle by using active detection radar, wireless detection and positioning equipment, and photoelectric detection system multi-source detection technology to determine whether its flight activities are authorized by the ATM and UTM systems;

[0014] The risk assessment module is used to achieve a comprehensive quantitative assessment of the risk of illegal UAV operation (including UAV weight, flight altitude interval, track relative convergence rate and conflict intensity), and to issue early warnings for UAVs with medium or high operating risks;

[0015] The situation sharing module is used to realize collaborative situation sharing among airspace users, ensure that ATM and UTM related airspace users obtain early warning information in a timely manner, and improve the perception ability of low-altitude airspace operation situation.

[0016] In a third aspect, the present invention provides a non-transitory computer-readable storage medium, which is used to store computer instructions. When the computer instructions are executed by a processor, the low-altitude UAV detection and early warning method based on situation sharing as described above is implemented.

[0017] In a fourth aspect, the present invention provides a computer program product, including a computer program, which, when running on one or more processors, is used to implement the low-altitude UAV detection and early warning method based on situation sharing as described above.

[0018] In a fifth aspect, the present invention provides an electronic device comprising: a processor, a memory and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory so that the electronic device executes instructions for implementing the low-altitude UAV detection and early warning method based on situation sharing as described above.

[0019] The beneficial effects of the present invention are as follows: by predefining low-altitude sensitive areas, spatial geometric modeling of sensitive airspace fences is realized, and then on the basis of UTM-ATM system interoperability, the UAV monitoring information obtained by active and passive multi-source joint detection equipment is used to effectively identify the legality of UAV flight activities; for UAVs with illegal activities, a comprehensive quantitative evaluation system for operation risks including UAV weight, flight altitude interval, track relative convergence rate and conflict intensity is established, and with the help of situation sharing means such as air traffic information service broadcasting, airspace users around medium and high-level operation risk UAVs are warned in time; real-time detection and analysis and warning / alarm of UAVs in low-altitude airspace are realized, effectively preventing the security threat of illegal UAV intrusion to other airspace users, and meeting the needs of low-altitude airspace situation sharing and continuous safety and stability.

[0020] Additional advantages of the present invention will be more clearly presented in the following description or learned through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0022] Figure 1 This is a flow chart of a low-altitude UAV detection and early warning method based on situation sharing described in an embodiment of the present invention.

[0023] Figure 2 The present invention is a flowchart of the legitimacy identification of UAV flight activities using active and passive multi-source joint detection and UTM-ATM interoperability technology as described in an embodiment of the present invention.

[0024] Figure 3 Schematic diagram of a radar target area determination window according to an embodiment of the present invention.

[0025] Figure 4 This is a process diagram of drone threat level assessment and early warning based on operational risk according to an embodiment of the present invention.

[0026] Figure 5 This is a structural diagram of the low-altitude UAV detection and early warning device based on situation sharing implemented in the present invention. DETAILED DESCRIPTION

[0027] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The embodiments described below by the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be interpreted as limiting the present invention.

[0028] It should be understood by those skilled in the art that unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those skilled in the art to which this invention belongs.

[0029] Those skilled in the art will appreciate that, unless otherwise stated, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements and / or groups thereof.

[0030] To facilitate understanding of the present invention, the present invention is further explained below with reference to specific embodiments in conjunction with the accompanying drawings, and the specific embodiments do not constitute a limitation on the embodiments of the present invention.

[0031] Those skilled in the art should understand that the drawings are merely schematic diagrams of embodiments, and the components in the drawings are not necessarily necessary for implementing the present invention.

[0032] Example 1

[0033] In this embodiment 1, a low-altitude UAV detection and early warning system based on situation sharing is first provided, including: an airspace pre-definition module, which is used to establish a fence space geometry model based on the collected sensitive airspace range data; a detection and identification module, which is used to effectively distinguish between legal and illegal UAVs by using active and passive multi-source joint detection and UTM-ATM interoperability technology; a risk assessment module, which is used to establish a comprehensive quantitative assessment method for operational risks, conduct UAV threat level assessment based on operational risks, and trigger early warning alarms; a situation sharing module, which is used to build a unified low-altitude air traffic panoramic situation view to realize situation sharing among airspace users.

[0034] In this embodiment 1, the above-mentioned system is used to implement a low-altitude UAV detection and early warning method based on situation sharing, including: using the airspace pre-definition module to establish a fence space geometry model based on the collected sensitive airspace range data; using the detection and identification module to use active and passive multi-source joint detection and UTM-ATM interoperability technology to effectively distinguish between legal and illegal UAVs; using the risk assessment module to establish a comprehensive quantitative assessment method for operational risks, conduct UAV threat level assessment based on operational risks, and trigger early warning alarms; using the situation sharing module to build a unified low-altitude air traffic panoramic situation view to achieve situation sharing among airspace users.

[0035] A fence space geometry model is established based on the collected sensitive airspace range data, including: collecting low-altitude sensitive airspace latitude and longitude data, restricted height, and restricted time information; based on the collected airspace data, a corresponding polygonal fence space geometry model or a sector-shaped fence space geometry model is established; wherein the polygonal fence space geometry model is composed of a cube composed of bottom and top surfaces at different altitudes, and the bottom and top surfaces are both closed space areas composed of N spatial points on the same plane; the sector-shaped fence space geometry model is composed of a cube composed of sector-shaped bottom and top surfaces at different altitudes, and the bottom and top surfaces are both closed space areas composed of the sector origin, sector radius, and sector start and end azimuths on the same plane.

[0036] Using active and passive multi-source joint detection and UTM-ATM interoperability technology, legal and illegal drones can be effectively distinguished, including:

[0037] Collect multi-source surveillance information of sensitive airspace in real time;

[0038] Intelligently identify the flying targets in the airspace based on the collected multi-source surveillance information, remove the low-altitude airspace clutter interference and separate the suspicious flying targets based on the radar image obtained by the active radar's all-round airspace scanning;

[0039] After the radar finds a suspicious flying target at a long distance, it operates the imaging angle of the optoelectronic device to lock the target, uses the optical image processing method to identify and confirm the flying target, and determines the specific attributes of the flying target;

[0040] For flying targets whose photoelectric detection target attributes are drones, radio monitoring technology is used to confirm their identities one by one, and the drone is identified and located by monitoring the drone remote control or image transmission signals in the corresponding directions to obtain the drone's identification information.

[0041] By making full use of the information sharing and data interaction between the ATM in low-altitude controlled airspace and the UTM communication gateway in uncontrolled airspace, we can compare and judge whether the monitored drone activities are legal; if the drone flight mission does not obtain ATM, UTM approval permission or does not match the time and space scope of the suitable airspace in the flight application data, it will be deemed as an illegal drone, otherwise it will be a legal drone.

[0042] Based on the radar image obtained by the active radar's all-round airspace scanning, the low-altitude airspace clutter interference is removed and suspicious flying targets are separated, including:

[0043]

[0044] Where D(i,j,k) is the k-th frame image of the coordinate (i,j) to be detected in L out ×L out and L in ×L in The average gray value of the pixels in the shadow area, L out , L in are the outer and inner rectangular frame sizes, M out 、M in They represent the sum of the grayscale values ​​of the pixels in the outer and inner rectangular boxes respectively, and the calculation formula is:

[0045]

[0046] Where G(·) is the gray value of the original radar image pixel, when D(i,j,k) satisfies the following judgment formula:

[0047]

[0048] Where S is the set threshold. When D(i,j,k)>S, it is considered that the detection target can effectively reflect the active radar electromagnetic waves due to its material, structure and other factors, and it appears as a bright area with a large grayscale in the image. Therefore, it is judged that the pixel belongs to the flying target, otherwise it is a clutter pixel.

[0049] Conduct drone threat level assessment based on operational risk and trigger early warning alarms, including: continuous dynamic tracking of detected illegal drones, analysis of moving targets based on accumulated tracking data, and updating of illegal drone situation information; combined with surrounding airspace user situation information provided by ATM and UTM, conduct a comprehensive quantitative assessment of illegal drone operation risks, calculate and weighted score risk assessment indicators including drone weight, flight altitude interval, relative track convergence rate, and conflict intensity.

[0050] Build a unified panoramic view of low-altitude air traffic situation to achieve situation sharing among airspace users, including: determine the corresponding risk areas and affected aircraft, use air traffic information service broadcasts to promptly issue safety warnings to ATM and UTM-related airspace users affected by illegal drone operations and guide them to avoid them, and use a visual interface to display the air traffic situation in the airspace operated by the user's airborne terminal.

[0051] Example 2

[0052] In this embodiment 2, a low-altitude UAV detection and early warning method based on situation sharing is proposed. Based on the air traffic control data provided by the ATM and UTM systems, the idea of ​​active and passive joint detection of multi-source detection equipment is utilized to carry out threat level assessment based on operational risks, to achieve accurate and timely warnings for illegal flying UAVs, and to enhance the situation awareness capabilities of low-altitude airspace users.

[0053] Low-altitude drone detection and early warning refers to timely warning of potential threats caused by illegal drones based on air traffic control data provided by ATM and UTM systems and drone monitoring information provided by multi-source detection equipment. The identification and supervision of low-altitude drones is an important means to ensure the continued safety and stability of low-altitude airspace. Through the sharing of drone early warning information, low-altitude airspace users can obtain comprehensive and clear air traffic information and achieve accurate perception of the operating airspace situation.

[0054] like Figure 1 As shown, the low-altitude UAV detection and early warning method based on situation sharing includes the following steps:

[0055] Step 101, spatial geometry modeling of low-altitude sensitive airspace fence.

[0056] The data collected include the latitude and longitude data of low-altitude sensitive airspace such as the airport clearance protection zone (10 kilometers on both sides of the center line of the airport runway and 20 kilometers at both ends of the runway), key sensitive units (such as military control areas), and densely populated areas, as well as information such as restricted altitude and restricted time. Based on the collected airspace data, a corresponding polygonal or sector-shaped fence space is established. Among them, the polygonal fence space geometry model is composed of a cube composed of bottom and top surfaces at different altitudes, and the bottom (top) surface is a closed space area composed of N spatial points on the same plane (starting from true north and named in a clockwise order on the horizontal plane). The sector-shaped fence space geometry model is composed of a cube composed of sector-shaped bottom and top surfaces at different altitudes, and the bottom (top) surface is a closed space area composed of the sector origin, sector radius, and sector start and end azimuths on the same plane.

[0057] Step 102, using active and passive multi-source joint detection and UTM-ATM interoperability technology to identify illegal drones.

[0058] like Figure 2 As shown, it is a flowchart of step 102, which specifically includes the following steps:

[0059] (1) Deployment of active and passive multi-source heterogeneous sensor surveillance networks, including active radars, radio detection equipment, and optoelectronic detection equipment (such as infrared thermal imagers and visible light cameras), to collect real-time video images of sensitive airspace, manipulate radio frequencies, and other surveillance information;

[0060] (2) Intelligently identify the flying targets in the airspace based on the collected multi-source surveillance information, and use the radar images (such as Figure 3 As shown), remove clutter interference such as low-altitude buildings and separate suspicious flying targets:

[0061]

[0062] Where D(i,j,k) is the k-th frame image of the coordinate (i,j) to be detected in L out ×L out and L in ×L in The average gray value of the pixels in the shadow area, L out , L in are the outer and inner rectangular frame sizes, M out 、M in They represent the sum of the grayscale values ​​of the pixels in the outer and inner rectangular boxes respectively, and the calculation formula is:

[0063]

[0064] Where G(·) is the gray value of the original radar image pixel, when D(i,j,k) satisfies the following judgment formula:

[0065]

[0066] Where S is the set threshold. When D(i,j,k)>S, it is considered that the detection target can effectively reflect the active radar electromagnetic waves due to its material, structure and other factors, and it appears as a bright area with a large grayscale in the image. Therefore, it is judged that the pixel belongs to the flying target, otherwise it is a clutter pixel.

[0067] (3) Based on the key flight targets screened out by active radar detection, optoelectronic detection technology is used as a supplement to the radar system. After the radar detects a suspicious flight target at a long distance, the imaging angle of the optoelectronic equipment is operated to lock the target, and the flight target is identified and confirmed using optical image processing methods to determine the specific attributes of the flight target, including drones, birds, or floating objects in the air.

[0068] (4) For flying targets whose photoelectric detection target attributes are drones, use radio monitoring technology to confirm their identities one by one, and identify and locate the drones by monitoring the drone remote control or image transmission signals in the corresponding directions, and obtain the drone’s intrusion location information and identification information such as model, brand, fingerprint information, and frequency band.

[0069] (5) By coordinating and connecting ATM and UTM air traffic control system data, and making full use of information sharing and data interaction between ATM in low-altitude controlled airspace and UTM communication gateway in uncontrolled airspace, we can compare and judge whether the monitored drone activities are legal. If the drone flight mission does not obtain ATM and UTM approval or does not match the time and space range of the suitable airspace in the flight application data, it will be deemed as an illegal drone, otherwise it will be a legal drone.

[0070] Step 103: Conduct an assessment of the drone threat level based on operational risk and trigger an early warning alarm.

[0071] Conduct continuous dynamic tracking of detected illegal drones, analyze moving targets based on accumulated tracking data, and update the precise location, flight speed, movement trajectory and other situation information of illegal drones. Combined with the surrounding airspace user situation information (such as three-dimensional location, flight speed, flight intention, etc.) provided by ATM and UTM, conduct a comprehensive quantitative assessment of the risk of illegal drone operations, focusing on the calculation and weighted scoring of risk assessment indicators including drone weight, flight altitude interval, relative convergence rate of tracks and conflict intensity. The specific process is as follows: Figure 4 shown.

[0072] With reference to the "Light and Small UAV Operation Regulations" and the "UAV General Guidelines", UAVs are divided into 5 categories according to their take-off weight, and the corresponding scores (Weight_score) are as follows: Category I UAV - weight W ≤ 1.5kg, 3 points for danger; Category II UAV - weight 1.5 < W ≤ 7kg, 8 points for danger; Category III UAV - weight 7 < W ≤ 25kg, 16 points for danger; Category IV UAV - weight 25 < W ≤ 150kg, 22 points for danger; Category V UAV - weight W > 150kg, 33 points for danger;

[0073] With reference to the "Flight Separation Regulations" and related classification methods, drones are divided into 5 categories according to their current flight altitude intervals with other aircraft, and the corresponding scores (Height_score) are as follows: Category I drones - altitude interval H ≥ 300m, 3 points for danger; Category II drones - altitude interval 260 ≤ H < 300m, 8 points for danger; Category III drones - altitude interval 180 ≤ H < 260m, 16 points for danger; Category VI drones - altitude interval 100 ≤ H < 180m, 22 points for danger; Category V drones - altitude interval H < 100m, 33 points for danger;

[0074] According to the real-time flight situation data of illegal drones and surrounding aircraft in low-altitude airspace, the degree of track approximation between aircraft, that is, the relative track convergence rate (Convergence_rate), is calculated:

[0075]

[0076] in is the relative position vector between the illegal UAV i and the surrounding aircraft j, is the relative velocity vector between aircraft, is the vector inner product.

[0077] Similarly, calculate the conflict intensity (Conflict_severity) between the illegal drone and surrounding aircraft:

[0078]

[0079] where d min (i, j) is the closest distance between the illegal drone i and the surrounding aircraft j, D0 is the given safety interval, and the conflict intensity coefficient β is calculated as follows:

[0080]

[0081] Where α is an adjustable parameter, usually set to 0.67; d CPA (i,j) is the distance between the current position of illegal drone i and the closest point.

[0082] Based on the scores of the above four types of risk indicators, the expert consultation method is used to determine the weight coefficients w1~w4 of each influencing indicator, and the risk quantification value after composite superposition is obtained:

[0083]

[0084] Normalize the risk quantification value S:

[0085]

[0086] Where S max , S min are the maximum S value and the minimum S value of the sample data respectively.

[0087] The normalized risk quantification value S' is divided into three categories: low risk (S'∈[0,0.4)), medium risk (S'∈[0.4,0.7)), and high risk (S'∈[0.7,1]), and the system alarm is triggered for illegal drones with medium and high operating risks;

[0088] Step 104, realize situation sharing among airspace users and build a unified panoramic situation view of low-altitude air traffic.

[0089] Identify the corresponding risk areas and affected aircraft, and use means such as Traffic Information Service Broadcast (TIS-B) to promptly issue safety warnings to ATM and UTM-related airspace users affected by illegal drone operations and guide them to avoid them. At the same time, combine with a visual interface to enhance the user's airborne terminal's intuitive perception of the air traffic situation in the operating airspace.

[0090] The low-altitude UAV detection and early warning method based on situation sharing provided in this embodiment first collects low-altitude sensitive airspace data to establish the corresponding fence space geometric model, then uses active and passive multi-source joint detection and UTM-ATM interoperability technology to identify the legality of UAV flight activities, and further conducts threat level assessment based on operational risk for detected illegal UAVs, and finally uses air traffic information service broadcasting to enhance the situation awareness of airspace users for medium and high operational risk UAVs. This can effectively prevent the security threat of illegal UAVs invading low-altitude airspace to other airspace users, and ensure real-time situation sharing and continuous safety and stability in low-altitude airspace.

[0091] Example 3

[0092] like Figure 5As shown, in this embodiment 3, a low-altitude UAV detection and early warning device based on situation sharing is provided, which may specifically include an airspace pre-definition module 1, a detection and identification module 2, a risk assessment module 3 and a situation sharing module 4. Among them, the airspace pre-definition module 1 is used to collect low-altitude sensitive airspace data and establish a fence space geometric model; the detection and identification module 2 is used to use active and passive multi-source joint detection and UTM-ATM interoperability to identify the legality of UAV flight activities; the risk assessment module 3 is used to quantitatively assess the operational risk threat level of illegal UAVs; and the situation sharing module 4 is used to provide airspace users with perception of the operational situation of illegal UAVs.

[0093] The airspace pre-definition module 1 may include an airspace data collection module 11 and a fence space geometric modeling module 12. The airspace data collection module 11 is used to collect information such as latitude and longitude data, restricted height, restricted time, etc. of low-altitude sensitive airspace, and the fence space geometric modeling module 12 is used to construct a polygonal or sector-shaped fence space.

[0094] The detection and identification module 2 may include an active radar detection module 21, a photoelectric detection module 22, a radio detection module 23 and a UTM-ATM interoperation module 24. Among them, the active radar detection module 21 is used to realize the intelligent detection of flying targets in low-altitude airspace, the photoelectric detection module 22 is used to determine the specific attributes of the flying targets, the radio detection module 23 is used for UAV positioning and identification information acquisition, and the UTM-ATM interoperation module 24 is used to compare and identify whether the UAV activities are legal.

[0095] The risk assessment module 3 may include an operation risk index calculation module 31 and a threat level assessment module 32. The operation risk index calculation module 31 is used to calculate the values ​​of indicators such as the weight hazard score of the drone, the flight altitude interval hazard score, the relative convergence rate of the track and the conflict intensity, and the threat level assessment module 32 is used to determine the operation threat level by integrating the operation risk indicators of multiple drones.

[0096] Specifically, the situation sharing module 4 may include a safety warning notification module 41 and a visual panoramic situation display module 42. The safety warning notification module 41 is used to issue effective intelligence warnings and flight recommendations to ATM and UTM related airspace users who are interfered with by illegal drone operations, and the visual panoramic situation display module 42 is used to realize the intuitive display of the panoramic situation of the airspace on the airborne end.

[0097] The low-altitude UAV detection and early warning device based on situation sharing provided in this embodiment sets up an airspace pre-definition module, a detection and identification module, a risk assessment module and a situation sharing module, establishes a low-altitude sensitive airspace fence space according to airspace data collection and fence space geometric modeling, combines active radar detection, photoelectric detection, radio detection and multiple joint detection methods with UTM-ATM interoperability to identify the legality of UAV activities, determines the threat level of illegal UAVs through the calculation and comprehensive evaluation of multiple operation risk indicator values, and finally issues security warnings to ATM and UTM-related airspace users affected by illegal UAV intrusions, thereby realizing panoramic situation awareness of the airspace of airspace users on the airborne side and ensuring the continuous safety and stability of the low-altitude airspace.

[0098] Example 4

[0099] This embodiment 4 provides a non-transitory computer-readable storage medium, which is used to store computer instructions. When the computer instructions are executed by a processor, the low-altitude UAV detection and early warning method based on situation sharing as described above is implemented. The method includes:

[0100] Establish a fence space geometry model based on the collected sensitive airspace range data;

[0101] Use active and passive multi-source joint detection and UTM-ATM interoperability technology to effectively distinguish between legal and illegal drones;

[0102] Establish a comprehensive quantitative assessment method for operational risks, conduct drone threat level assessment based on operational risks, and trigger early warning alarms;

[0103] Build a unified panoramic situation view of low-altitude air traffic and realize situation sharing among airspace users.

[0104] Example 5

[0105] This embodiment 5 provides a computer program product, including a computer program. When the computer program is executed on one or more processors, it is used to implement the low-altitude UAV detection and early warning method based on situation sharing as described above. The method includes:

[0106] Establish a fence space geometry model based on the collected sensitive airspace range data;

[0107] Use active and passive multi-source joint detection and UTM-ATM interoperability technology to effectively distinguish between legal and illegal drones;

[0108] Establish a comprehensive quantitative assessment method for operational risks, conduct drone threat level assessment based on operational risks, and trigger early warning alarms;

[0109] Build a unified panoramic situation view of low-altitude air traffic and realize situation sharing among airspace users.

[0110] Example 6

[0111] This embodiment 6 provides an electronic device, including: a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory, so that the electronic device executes instructions for implementing the low-altitude drone detection and early warning method based on situation sharing as described above, and the method includes:

[0112] Establish a fence space geometry model based on the collected sensitive airspace range data;

[0113] Use active and passive multi-source joint detection and UTM-ATM interoperability technology to effectively distinguish between legal and illegal drones;

[0114] Establish a comprehensive quantitative assessment method for operational risks, conduct drone threat level assessment based on operational risks, and trigger early warning alarms;

[0115] Build a unified panoramic situation view of low-altitude air traffic and realize situation sharing among airspace users.

[0116] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0117] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0118] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0119] These computer program instructions can also be loaded onto a computer or other programmable data processing device, and a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0120] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative work on the basis of the technical solution disclosed in the present invention should be included in the scope of protection of the present invention.

Claims

1. A low-altitude UAV detection and early warning method based on situation sharing, characterized in that: include: Establish a fence space geometry model based on the collected sensitive airspace range data; Active and passive multi-source joint detection and UTM-ATM interoperability technology are used to effectively distinguish between legal and illegal drones. This includes: real-time collection of multi-source surveillance information in sensitive airspace; intelligent identification of flight targets in the airspace based on the collected multi-source surveillance information, and removal of low-altitude airspace clutter interference and separation of suspicious flight targets based on radar images obtained by all-round airspace scanning by active radar; after the radar finds a long-distance suspicious flight target, the imaging angle of the optoelectronic device is operated to lock the target, and the optical image processing method is used to identify and confirm the flight target and determine the specific attributes of the flight target; for flight targets whose optoelectronic detection target attributes are drones, their identities are confirmed one by one using radio monitoring technology, and drone remote control or image transmission signals of drones in corresponding directions are used to identify and locate drones to obtain drone identification information; full information sharing and data interaction between ATM in low-altitude controlled airspace and UTM communication gateways in uncontrolled airspace are used to compare and determine whether the monitored drone activities are legal; if the drone flight mission does not obtain ATM or UTM approval or does not match the time and space range of the suitable airspace for flight application data, it is considered an illegal drone, otherwise it is a legal drone; Among them, based on the radar image obtained by the active radar's all-round airspace scanning, the low-altitude airspace clutter interference is removed and suspicious flying targets are separated, including: Where D(i,j,k) is the k-th frame image of the coordinate (i,j) to be detected in L out ×L out and L in ×L in The average gray value of the pixels in the shadow area, L out , L in are the outer and inner rectangular frame sizes, M out 、M in They represent the sum of the grayscale values ​​of the pixels in the outer and inner rectangular boxes respectively, and the calculation formula is: Where G(·) is the gray value of the original radar image pixel, when D(i,j,k) satisfies the following judgment formula: Where S is the set threshold value. When D(i,j,k)>S, it is considered that the detection target can effectively reflect the active radar electromagnetic wave due to its material and structural factors, and it appears as a bright area with a large grayscale in the image. Therefore, it is judged that the pixel belongs to the flying target, otherwise it is a clutter pixel. Establish a comprehensive quantitative assessment method for operational risks, conduct drone threat level assessment based on operational risks, and trigger early warning alarms; Build a unified panoramic situation view of low-altitude air traffic and realize situation sharing among airspace users.

2. The low-altitude UAV detection and early warning method based on situation sharing according to claim 1 is characterized in that: A fence space geometry model is established based on the collected sensitive airspace range data, including: collecting low-altitude sensitive airspace latitude and longitude data, restricted height and restricted time information; based on the collected airspace data, a corresponding polygonal fence space geometry model or a sector-shaped fence space geometry model is established; wherein the polygonal fence space geometry model is composed of a cube composed of bottom and top surfaces at different altitudes, and the bottom and top surfaces are both closed space areas composed of N spatial points on the same plane; the sector-shaped fence space geometry model is composed of a cube composed of sector-shaped bottom and top surfaces at different altitudes, and the bottom and top surfaces are both closed space areas composed of the sector origin, sector radius and sector start and end azimuths on the same plane.

3. The low-altitude UAV detection and early warning method based on situation sharing according to claim 1 is characterized in that: Conduct drone threat level assessment based on operational risk and trigger early warning alarms, including: continuous dynamic tracking of detected illegal drones, analysis of moving targets based on accumulated tracking data, and updating of illegal drone situation information; combined with surrounding airspace user situation information provided by ATM and UTM, conduct a comprehensive quantitative assessment of illegal drone operation risks, calculate and weighted score risk assessment indicators including drone weight, flight altitude interval, relative track convergence rate, and conflict intensity.

4. The low-altitude UAV detection and early warning method based on situation sharing according to claim 1 is characterized in that: Build a unified panoramic view of low-altitude air traffic situation to achieve situation sharing among airspace users, including: determine the corresponding risk areas and affected aircraft, use air traffic information service broadcasts to promptly issue safety warnings to ATM and UTM-related airspace users affected by illegal drone operations and guide them to avoid them, and use a visual interface to display the air traffic situation in the airspace operated by the user's airborne terminal.

5. A low-altitude UAV detection and early warning system based on situation sharing, characterized in that: include: Airspace pre-definition module, used to establish the fence space geometry model based on the collected sensitive airspace range data; The detection and identification module is used to effectively distinguish between legal and illegal drones by using active and passive multi-source joint detection and UTM-ATM interoperability technology. It includes: real-time collection of multi-source surveillance information in sensitive airspace; intelligent identification of flight targets in the airspace based on the collected multi-source surveillance information, removing low-altitude airspace clutter interference and separating suspicious flight targets based on the radar image obtained by the active radar's all-round airspace scanning; after the radar finds a long-distance suspicious flight target, the imaging angle of the optoelectronic device is operated to lock the target, and the optical image processing method is used to identify and confirm the flight target and determine the specific attributes of the flight target; for the flight target whose optoelectronic detection target attribute is a drone, the radio monitoring technology is used to confirm its identity one by one, and the drone is identified and located by monitoring the drone remote control or image transmission signal in the corresponding direction to obtain the drone's identification information; the low-altitude controlled airspace ATM and the uncontrolled airspace UTM communication gateway are used to fully share information and interact with data to compare and determine whether the monitored drone activities are legal; if the drone flight mission does not obtain ATM, UTM approval or does not match the time and space range of the suitable airspace of the flight application data, it is identified as an illegal drone, otherwise it is a legal drone; Among them, based on the radar image obtained by the active radar's all-round airspace scanning, the low-altitude airspace clutter interference is removed and suspicious flying targets are separated, including: Where D(i,j,k) is the k-th frame image of the coordinate (i,j) to be detected in L out ×L out and L in ×L in The average gray value of the pixels in the shadow area, L out , L in are the outer and inner rectangular frame sizes, M out 、M in They represent the sum of the grayscale values ​​of the pixels in the outer and inner rectangular boxes respectively, and the calculation formula is: Where G(·) is the gray value of the original radar image pixel, when D(i,j,k) satisfies the following judgment formula: Where S is the set threshold value. When D(i,j,k)>S, it is considered that the detection target can effectively reflect the active radar electromagnetic wave due to its material and structural factors, and it appears as a bright area with a large grayscale in the image. Therefore, it is judged that the pixel belongs to the flying target, otherwise it is a clutter pixel. The risk assessment module is used to establish a comprehensive quantitative assessment method for operational risks, conduct drone threat level assessment based on operational risks, and trigger early warning alarms; The situation sharing module is used to build a unified panoramic situation view of low-altitude air traffic and realize situation sharing among airspace users.

6. A computer program product, characterized in that It includes a computer program, which, when running on one or more processors, is used to implement the low-altitude UAV detection and early warning method based on situation sharing as described in any one of claims 1 to 4.

7. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by the processor, the low-altitude drone detection and early warning method based on situation sharing as described in any one of claims 1 to 4 is implemented.

8. An electronic device, characterized in that: include: A processor, a memory and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory so that the electronic device executes instructions for implementing the low-altitude UAV detection and early warning method based on situation sharing as described in any one of claims 1 to 4.

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