CN111627259A - Unmanned aerial vehicle intrusion classification early warning method in airport clearance protection area and storage medium - Google Patents
Unmanned aerial vehicle intrusion classification early warning method in airport clearance protection area and storage medium Download PDFInfo
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Abstract
The invention discloses a classification early warning method for unmanned aerial vehicle intrusion in an airport clearance protection area and a storage medium, wherein the method comprises the following steps: acquiring information of the unmanned aerial vehicle in real time; judging whether the unmanned aerial vehicle enters a clearance protection area or not according to the longitude and latitude of the unmanned aerial vehicle; if not, the first early warning level is set as the first early warning level and early warning information is generated; if yes, judging whether to enter a core protection area; if not, the first early warning level is the first early warning level and early warning information is generated; if so, acquiring the information of the civil aircraft and inquiring a take-off and landing track database of the civil aircraft to predict the track; calculating the nearest meeting point of the flight path and the maximum flight speed of the unmanned aerial vehicle; judging whether the minimum meeting distance and the minimum meeting time are both smaller than an early warning threshold value; if not, the third early warning level is set as the third early warning level and early warning information is generated; and if so, generating early warning information for the fourth early warning level. The method can judge the intrusion hazard level of the unmanned aerial vehicle according to the position of the unmanned aerial vehicle and the minimum meeting distance and time between the unmanned aerial vehicle and the civil aircraft, and generate corresponding early warning information.
Description
Technical Field
The invention relates to the field of unmanned aerial vehicle supervision in an airport clearance protection area, in particular to an unmanned aerial vehicle intrusion grading early warning method and a storage medium in the airport clearance protection area.
Background
The unmanned aerial vehicle industry is developing vigorously, and the user of unmanned aerial vehicle also grows rapidly, and its wide application is in a plurality of fields of social life. Meanwhile, the unmanned aerial vehicle flies in disorder and flies in black, and huge pressure is brought to civil aviation safety, airspace management and the like, so that potential safety hazards are caused. If the unmanned plane flies into the Hangzhou Xiaoshan airport in 2017 in 1 month, multiple flights are delayed; in 2017, in a 5-month Chengdu double-flow airport, unmanned aerial vehicle interference events continuously occur; in the end of 2018, 11 ten thousand passengers remained in the downtown London by the unmanned aerial vehicle.
The unmanned aerial vehicle is regulated to engage in commercial flight activities, market supervision is enhanced, and safe, orderly and healthy development of the unmanned aerial vehicle industry is promoted. The civil aviation bureau issues management methods (temporary) of commercial flight activities of civil unmanned aircrafts, and the management methods are implemented from 6 to 1 in 2018. It provides that drones must have reliable monitored capability, airspace-keeping capability, and must comply with restricted-flight-barring provisions. In order to ensure that the user uses the unmanned aerial vehicle legally, each unmanned aerial vehicle manufacturer sets the flying forbidding and flying limiting criteria in the unmanned aerial vehicle. Under normal conditions, unmanned aerial vehicle is difficult to fly in no-fly zone.
But for non-cooperative users, the unmanned aerial vehicle can fly freely without being limited in an airport clearance protection area by tampering GPS information, privately modifying the unmanned aerial vehicle and the like, and potential safety hazards to civil aviation airliners are caused. Therefore, at present, each airport is provided with an unmanned aerial vehicle detection defense system in sequence, and the unmanned aerial vehicle is monitored and disposed through technologies and means such as radar detection, frequency spectrum detection, photoelectric detection and electromagnetic interference. However, at present, the management and control method of the unmanned aerial vehicle in the airport can not perform classified management according to the damage level of the unmanned aerial vehicle invasion.
Disclosure of Invention
In order to overcome the defects of the prior art, one of the purposes of the invention is to provide a classification early warning method for unmanned aerial vehicle intrusion in an airport clearance protection area, which can judge the intrusion hazard level of the unmanned aerial vehicle according to the position of the unmanned aerial vehicle and the minimum meeting distance and time between the unmanned aerial vehicle and a civil aircraft, and generate corresponding early warning information.
The second purpose of the present invention is to provide a computer readable storage medium, which can realize, when running a computer program stored in the storage medium, judging the intrusion hazard level of an unmanned aerial vehicle according to the position of the unmanned aerial vehicle and the minimum meeting distance and time between the unmanned aerial vehicle and a civil aircraft, and generating corresponding early warning information.
One of the purposes of the invention is realized by adopting the following technical scheme:
an unmanned aerial vehicle intrusion classification early warning method in an airport clearance protection area comprises the following steps:
the information of the unmanned aerial vehicle in the monitoring area is obtained in real time, and the information of the unmanned aerial vehicle comprises: the brand model of the unmanned aerial vehicle, the longitude and latitude and the height at the current moment;
judging whether the unmanned aerial vehicle enters a clearance protection area or not according to the longitude and latitude of the unmanned aerial vehicle at the current moment;
if not, judging as the first early warning level and generating corresponding early warning information;
if so, judging whether the unmanned aerial vehicle enters a core protection area or not according to the longitude and latitude of the unmanned aerial vehicle at the current moment;
if not, judging to be the second early warning level and generating corresponding early warning information;
if yes, obtaining information of the civil aircraft in the monitoring area, wherein the information of the civil aircraft comprises: flight identification information, ICAO, latitude and longitude, altitude, ground speed, climb/descent rate, and heading;
inquiring a civil aviation passenger plane take-off and landing track database according to the information of the civil aviation passenger planes to predict the track of the civil aviation passenger planes in a monitoring area, wherein the take-off and landing track database of the civil aviation passenger planes stores take-off tracks and landing tracks corresponding to all the civil aviation passenger plane models;
calculating the nearest meeting point of the predicted track of the civil aviation passenger plane and the maximum flight speed corresponding to the brand model of the unmanned plane to obtain the minimum meeting distance and the minimum meeting time, wherein the minimum meeting distance is the distance between the current position of the unmanned plane and the nearest meeting point, and the minimum meeting time is the shortest flight time for the unmanned plane to reach the nearest meeting point from the current position;
judging whether the minimum meeting distance and the minimum meeting time are both smaller than an early warning threshold value;
if not, judging to be a third early warning level and generating corresponding early warning information;
if yes, judging to be a fourth early warning level and generating corresponding early warning information;
wherein the early warning information comprises: the method comprises the steps of early warning level, the motion direction of the unmanned aerial vehicle, and the direction and distance of the unmanned aerial vehicle relative to a reference point, wherein the reference point is the central point of an airport runway.
Further, after generating the corresponding early warning information, the method further comprises the following steps: and sending the early warning information to a user terminal.
Further, the early warning threshold corresponding to the minimum meeting distance is 600 meters, and the early warning threshold corresponding to the minimum meeting time is 60 seconds.
Further, information of the unmanned aerial vehicles in the monitoring area is acquired in a radar, frequency spectrum, photoelectric or radio mode.
Further, the early warning information further comprises the intrusion time and the intrusion duration of the unmanned aerial vehicle.
Further, the predicted flight path of the civil aircraft is denoted Pt{xt,yt,zt},t∈(t0，t1，t2，ti…,tn) The calculation of the nearest meeting point according to the predicted track of the civil aircraft and the maximum flight speed corresponding to the model of the unmanned aircraft specifically comprises the following steps:
calculating to obtain the track P of the civil aircrafttMiddle distance unmanned plane position Dt0Nearest track point Pt2And calculating slave D of unmanned aerial vehiclet0To Pt2Time of flight Δ t2；
Judge unmanned aerial vehicle from Dt0To Pt2Time of flight Δ t2With said civil aircraft from track starting point Pt0To Pt2Time of flight t20Whether the error of (1) is within a preset range;
if so, then P is determinedt2Is the nearest meeting point of the civil aircraft and the unmanned aerial vehicle;
if not, selecting an intermediate point P according to the dichotomy principletmAnd calculating slave D of unmanned aerial vehiclet0To PtmTime of flight Δ tmAnd the civil aircraft starting point P from trackt0To PtmTime of flight tm0And judging Δ tmAnd tm0Whether the error of (a) is within a preset range,
if so, then P is determinedtmIs the nearest meeting point of the civil aircraft and the unmanned aerial vehicle;
and if not, re-selecting the intermediate point according to the dichotomy principle until the nearest meeting point of the civil aircraft and the unmanned aircraft is found.
Further, selecting a middle point P according to a dichotomy principletmThe method specifically comprises the following steps:
if Δ t2>t20Then is at Pt2And track end point PtnSelect an intermediate point P betweentm；
If Δ t2<t20Then at the starting point P of the trackt0And Pt2Select an intermediate point P betweentm。
Further, unmanned aerial vehicle follows Dt0To Pt2Time of flight Δ t2The calculation formula of (a) is as follows:
wherein S is2hFrom Dt0To Pt2Horizontal distance of (S)2vFrom Dt0To Pt2The vertical distance of (a) is,
is the maximum horizontal flying speed of the unmanned plane,
is the maximum vertical flying speed of the unmanned aerial vehicle.
Further, the early warning grades are displayed in a grading mode through colors, the first early warning grade is displayed in green, the second early warning grade is displayed in yellow, the third early warning grade is displayed in orange, and the fourth early warning grade is displayed in red.
The second purpose of the invention is realized by adopting the following technical scheme:
a computer readable storage medium having stored thereon an executable computer program, which when executed, can implement the method for classifying and warning intrusion by drones in an airport headroom protected area as described above.
Compared with the prior art, the invention has the beneficial effects that:
according to the unmanned aerial vehicle intrusion classification early warning method in the airport clearance protection area, the intrusion hazard grade of the unmanned aerial vehicle can be judged according to the position of the unmanned aerial vehicle and the minimum meeting distance and time between the unmanned aerial vehicle and a civil aircraft, and corresponding early warning information is generated. The method realizes the hierarchical management of the intrusion event of the unmanned aerial vehicle, not only guarantees the safety of the airspace and reduces the management pressure of the airspace, but also gives the unmanned aerial vehicle users the free flight rights as much as possible and promotes the healthy development of the unmanned aerial vehicle industry, thereby eliminating the dual problems of excessive reaction and complete neglect of relevant management departments to the unmanned aerial vehicle in the airport.
Drawings
Fig. 1 is a schematic flow chart of a method for classifying and early warning intrusion of an unmanned aerial vehicle in an airport clearance protection area according to the present invention;
FIG. 2 is a schematic view of an airport clearance protection area provided by the present invention;
fig. 3 is a schematic diagram of the predicted positions of the flight paths and the intruding drones of the civil aircraft provided by the present invention.
Detailed Description
The present invention will be further described with reference to the accompanying drawings and the detailed description, and it should be noted that any combination of the embodiments or technical features described below can be used to form a new embodiment without conflict.
Please refer to fig. 1, a method for classifying and early warning of unmanned aerial vehicle intrusion in an airport clearance protection area includes the following steps:
s1, acquiring information of the unmanned aerial vehicle in the monitoring area in real time in a radar, frequency spectrum, photoelectric or radio mode, wherein the information of the unmanned aerial vehicle comprises: the brand model of the unmanned aerial vehicle, the longitude and latitude and the height at the current moment;
s2, judging whether the unmanned aerial vehicle enters a clearance protection area or not according to the longitude and latitude of the unmanned aerial vehicle at the current moment;
s3, if not, determining the early warning level as the first early warning level and generating corresponding early warning information;
s4, if yes, judging whether the unmanned aerial vehicle enters a core protection area or not according to the longitude and latitude of the unmanned aerial vehicle at the current moment;
s5, if not, judging to be the second early warning level and generating corresponding early warning information;
s6, if yes, obtaining the information of the civil aviation passenger plane in the monitoring area in real time based on an ADS-B system, wherein the information of the civil aviation passenger plane comprises: flight identification information (namely flight number or call sign, wherein the model of the civil aviation passenger plane can be obtained according to the flight identification information), ICAO (global unique body code of the airplane, 24 bits), longitude and latitude, altitude, ground speed, climbing/descending rate and course;
s7, inquiring a take-off and landing track database of the civil aircraft according to the information of the civil aircraft to predict the track of the civil aircraft in the monitoring area; the take-off and landing track database of the civil aviation airliner stores the take-off track and landing track of each airliner model; the specific query process comprises the following steps: searching whether a historical takeoff track or landing track of a corresponding flight exists in a database according to the acquired flight identification information of the civil airliner, and if not, searching the takeoff track or landing track of the same type to obtain a takeoff track set or landing track set; furthermore, the takeoff track set or the landing track set which is obtained by searching is searched for the takeoff track or the landing track which has similar parameters such as longitude and latitude, height, ground speed, climbing/descending rate, heading and the like, specifically, the climbing or descending rate is firstly matched, screening the takeoff track or landing track with similar climbing/descending rate from the searched takeoff track set or landing track set, screening the takeoff track or landing track with similar climbing/descending rate from the screened takeoff track or landing track with similar climbing/descending rate, then, searching for a takeoff track or a landing track with similar longitude and latitude and height from the screened takeoff track or landing track, and finally further searching for the takeoff track or landing track with the closest ground speed from the screened tracks; and after the closest takeoff track or landing track is matched, the subsequent track information of the flight can be predicted according to the historical track, namely the closest takeoff track or landing track is used as the predicted track of the flight. (ii) a
S8, calculating the nearest meeting point of the predicted track of the civil aviation passenger plane and the maximum flight speed corresponding to the brand model of the unmanned plane to obtain the minimum meeting distance and the minimum meeting time, wherein the minimum meeting distance is the distance between the current position of the unmanned plane and the nearest meeting point, and the minimum meeting time is the shortest flight time for the unmanned plane to reach the nearest meeting point from the current position;
s9, judging whether the minimum meeting distance and the minimum meeting time are both smaller than an early warning threshold value, wherein preferentially, the early warning threshold value corresponding to the minimum meeting distance is 600 meters, and the early warning threshold value corresponding to the minimum meeting time is 60 seconds;
s10, if not, determining the early warning level as the third early warning level and generating corresponding early warning information;
s11, if yes, judging to be a fourth early warning level and generating corresponding early warning information;
wherein the early warning information comprises: the method comprises the steps of early warning level, the motion direction of the unmanned aerial vehicle, and the direction and distance of the unmanned aerial vehicle relative to a reference point, wherein the reference point is the central point of an airport runway.
According to the unmanned aerial vehicle intrusion classification early warning method in the airport clearance protection area, the intrusion hazard grade of the unmanned aerial vehicle can be judged according to the position of the unmanned aerial vehicle and the minimum meeting distance and time between the unmanned aerial vehicle and a civil aircraft, and corresponding early warning information is generated. The method realizes the hierarchical management of the intrusion event of the unmanned aerial vehicle, not only guarantees the safety of the airspace and reduces the management pressure of the airspace, but also gives the unmanned aerial vehicle users the free flight rights as much as possible and promotes the healthy development of the unmanned aerial vehicle industry, thereby eliminating the dual problems of excessive reaction and complete neglect of relevant management departments to the unmanned aerial vehicle in the airport.
In particular, the schematic diagram of the airport clearance protection area is shown in fig. 2, and the middle rectangle is a runway; the runway center is the benchmark, calculates unmanned aerial vehicle and relative distance and the position of benchmark, and it is as the main content of early warning information, can reflect unmanned aerial vehicle's motion situation directly perceived. The middle area is 2km of horizontal plane extension in an airport, and is a core protection area; the outermost periphery is a headroom protection zone. Wherein the inner horizontal plane (core protected area) and the clearance protected area are based on the published data of the civil aviation bureau and each airport, and fig. 2 is only an example.
Risks of the first early warning level, the second early warning level, the third early warning level and the fourth early warning level are increased in sequence, the risk of the first early warning level is lowest, and the risk of the fourth early warning level is highest.
As a preferred embodiment, after generating the corresponding warning information, the method further includes the steps of: sending the early warning information to a user terminal, and informing related workers to take corresponding treatment measures according to the early warning information; specifically, the warning information may be sent to the user terminal through a short message, an email, or a WeChat.
As a preferred embodiment, the early warning information further includes an intrusion time and an intrusion duration of the drone. Because unmanned aerial vehicle can trigger corresponding early warning signal in invading the monitoring area promptly, can trigger corresponding early warning signal all the time when unmanned aerial vehicle flies into headroom protection district or even the in-process in core protection district from airport headroom protection district periphery, then early warning information can also include unmanned aerial vehicle's invasion moment and invasion duration to airport staff monitors unmanned aerial vehicle's whereabouts.
As a preferred embodiment, the predicted flight path of a civil aircraft is denoted Pt{xt,yt,zt},t∈(t0,t1,t2,ti…,tn) Wherein, t0Is the current time, Pt0The method comprises the steps of taking a track starting point as a current position of a civil aviation passenger plane acquired in real time; piIs tiAt the moment the civil aircraft is in position, PtnIn order to calculate the track end (the landing passenger aircraft is at the end position of sliding on the runway, and the takeoff passenger aircraft is at the intersection point of the passenger aircraft and the periphery of the core area on the horizontal projection plane), the track prediction calculation adopts a common interpolation algorithm and the like. A schematic diagram of a predicted flight path of a civil aircraft and a position of an unmanned aerial vehicle is shown in fig. 3, and the calculating of the closest meeting point of the predicted flight path of the civil aircraft and the maximum flight speed corresponding to the model of the unmanned aerial vehicle specifically includes the following steps:
calculating to obtain the track P of the civil aircrafttMiddle distance unmanned plane position Dt0Nearest track point Pt2And calculating slave D of unmanned aerial vehiclet0To Pt2Time of flight Δ t2；
Judge unmanned aerial vehicle from Dt0To Pt2Time of flight Δ t2With said civil aircraft from track starting point Pt0To Pt2Time of flight t20Whether the error of (a) is within a preset range, preferably, the error is within 5 seconds;
if so, then P is determinedt2Is the nearest meeting point of the civil aircraft and the unmanned aerial vehicle;
if not, selecting an intermediate point P according to the dichotomy principletmAnd calculating slave D of unmanned aerial vehiclet0To PtmTime of flight Δ tmAnd said civil aircraft arrives at P from track starting point Pt0tmTime of flight tm0And judging Δ tmAnd tm0Whether the error of (a) is within a preset range,
if so, then P is determinedtmIs the nearest meeting point of the civil aircraft and the unmanned aerial vehicle;
and if not, re-selecting the intermediate point according to the dichotomy principle until the nearest meeting point of the civil aircraft and the unmanned aircraft is found.
Specifically, the intermediate point P is selected according to the dichotomy principletmThe method specifically comprises the following steps:
if Δ t2>t20Then is at Pt2And track end point PtnSelect an intermediate point P betweentm；
If Δ t2<t20Then at the starting point P of the trackt0And Pt2Select an intermediate point P betweentm。
For example, when Δ t2>t20When selecting Pt2And PtnIntermediate point P oftiAnd calculating slave D of unmanned aerial vehiclet0To PtiTime of flight Δ ti(ii) a When Δ t is reached2<t20When selecting Pt0And Pt2Intermediate point P oftjAnd calculating slave D of unmanned aerial vehiclet0To PtjTime of flight Δ tj(ii) a At this time, if
Or
Then P istiOr PtjAnd (4) determining the nearest meeting point of the two points, otherwise repeating the previous step, reselecting the middle point, and performing time comparison until the nearest meeting point is found.
Because the unmanned aerial vehicle has randomness in flying, the unmanned aerial vehicle is assumed to be at the maximum speed according to the principle of minimizing risk maximization,Driving to the civil aircraft in the direction meeting with the civil aircraft in the minimum time so as to confirm that the unmanned aircraft invasion model is
Unmanned aerial vehicle slave Dt0To Pt2Time of flight Δ t2The calculation formula of (a) is as follows:
wherein S is2hFrom Dt0To Pt2Horizontal distance of (S)2vFrom Dt0To Pt2The vertical distance of (a) is,
is the maximum horizontal flying speed of the unmanned plane,
is the maximum vertical flying speed of the unmanned aerial vehicle.
As a preferred embodiment, the early warning levels are displayed in a graded manner by colors, the first early warning level is displayed in green, the second early warning level is displayed in yellow, the third early warning level is displayed in orange, and the fourth early warning level is displayed in red. Different early warning levels are represented by different colors, and the method is visual and clear.
The invention also provides a computer readable storage medium, which stores an executable computer program, and when the computer program runs, the method for early warning of unmanned aerial vehicle intrusion classification in an airport clearance protection area can be realized.
The computer-readable storage medium stores a computer program in which the method of the present invention, if implemented in the form of software functional units and sold or used as a stand-alone product, can be stored. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer storage medium and used by a processor to implement the steps of the embodiments of the method. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer storage medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer storage media may include content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer storage media that does not include electrical carrier signals and telecommunications signals as subject to legislation and patent practice.
The above embodiments are only preferred embodiments of the present invention, and the protection scope of the present invention is not limited thereby, and any insubstantial changes and substitutions made by those skilled in the art based on the present invention are within the protection scope of the present invention.
Claims (10)
1. An unmanned aerial vehicle intrusion classification early warning method in an airport clearance protection area is characterized by comprising the following steps:
the information of the unmanned aerial vehicle in the monitoring area is obtained in real time, and the information of the unmanned aerial vehicle comprises: the brand model of the unmanned aerial vehicle, the longitude and latitude and the height at the current moment;
judging whether the unmanned aerial vehicle enters a clearance protection area or not according to the longitude and latitude of the unmanned aerial vehicle at the current moment;
if not, judging as the first early warning level and generating corresponding early warning information;
if so, judging whether the unmanned aerial vehicle enters a core protection area or not according to the longitude and latitude of the unmanned aerial vehicle at the current moment, wherein the core protection area is positioned in the clearance protection area;
if not, judging to be the second early warning level and generating corresponding early warning information;
if yes, obtaining information of the civil aircraft in the monitoring area, wherein the information of the civil aircraft comprises: flight identification information, ICAO, latitude and longitude, altitude, ground speed, climb/descent rate, and heading;
inquiring a civil aviation passenger plane take-off and landing track database according to the information of the civil aviation passenger planes to predict the track of the civil aviation passenger planes in a monitoring area, wherein the take-off and landing track database of the civil aviation passenger planes stores take-off tracks and landing tracks corresponding to all the civil aviation passenger plane models;
calculating the nearest meeting point of the predicted track of the civil aviation passenger plane and the maximum flight speed corresponding to the brand model of the unmanned plane to obtain the minimum meeting distance and the minimum meeting time, wherein the minimum meeting distance is the distance between the current position of the unmanned plane and the nearest meeting point, and the minimum meeting time is the shortest flight time for the unmanned plane to reach the nearest meeting point from the current position;
judging whether the minimum meeting distance and the minimum meeting time are both smaller than an early warning threshold value;
if not, judging to be a third early warning level and generating corresponding early warning information;
if yes, judging to be a fourth early warning level and generating corresponding early warning information;
wherein the early warning information comprises: the method comprises the steps of early warning level, the motion direction of the unmanned aerial vehicle, and the direction and distance of the unmanned aerial vehicle relative to a reference point, wherein the reference point is the central point of an airport runway.
2. The method for hierarchical early warning of unmanned aerial vehicle intrusion into airport headroom protected areas of claim 1, further comprising the steps of, after generating corresponding early warning information: and sending the early warning information to a user terminal.
3. The method as claimed in claim 1, wherein the minimum meeting distance corresponds to an early warning threshold of 600 m, and the minimum meeting time corresponds to an early warning threshold of 60 s.
4. The method for hierarchical early warning of unmanned aerial vehicle intrusion in airport clearance protection areas as claimed in claim 1, wherein the information of unmanned aerial vehicles in the monitoring area is obtained by means of radar, spectrum, photoelectricity or radio.
5. The method of claim 1, wherein the warning information further includes the time of the unmanned aerial vehicle's intrusion and the duration of the intrusion.
6. The method of claim 1, wherein the predicted flight path of the civil aircraft is represented as Pt{xt,yt,zt},t∈(t0,t1,t2,ti…,tn) The calculation of the nearest meeting point according to the predicted track of the civil aircraft and the maximum flight speed corresponding to the model of the unmanned aircraft specifically comprises the following steps:
calculating to obtain the track P of the civil aircrafttMiddle distance unmanned plane position Dt0Nearest track point Pt2And calculating slave D of unmanned aerial vehiclet0To Pt2Time of flight Δ t2；
Judge unmanned aerial vehicle from Dt0To Pt2Time of flight Δ t2With said civil aircraft from track starting point Pt0To Pt2Time of flight t20Whether the error of (1) is within a preset range;
if so, then P is determinedt2Is the nearest meeting point of the civil aircraft and the unmanned aerial vehicle;
if not, selecting an intermediate point P according to the dichotomy principletmAnd calculating slave D of unmanned aerial vehiclet0To PtmTime of flight Δ tmAnd the civil aircraft starting point P from trackt0To PtmTime of flight tm0And judging Δ tmAnd tm0Whether the error of (a) is within a preset range,
if so, then P is determinedtmIs the nearest meeting point of the civil aircraft and the unmanned aerial vehicle;
and if not, re-selecting the intermediate point according to the dichotomy principle until the nearest meeting point of the civil aircraft and the unmanned aircraft is found.
7. The method of claim 6, wherein the selecting the intermediate point P according to dichotomy principle is performed by the unmanned aerial vehicle intrusion classification early warning method in the airport clearance protection areatmThe method specifically comprises the following steps:
if Δ t2>t20Then is at Pt2And track end point PtnSelect an intermediate point P betweentm；
If Δ t2<t20Then at the starting point P of the trackt0And Pt2Select an intermediate point P betweentm。
8. The method of claim 6, wherein the unmanned aerial vehicle is driven from D to stage early warning for unmanned aerial vehicle intrusion in airport clearance protection zonet0To Pt2Time of flight Δ t2The calculation formula of (a) is as follows:
wherein S is2h is from Dt0To Pt2Horizontal distance of (S)2vFrom Dt0To Pt2The vertical distance of (a) is,
is the maximum horizontal flying speed of the unmanned plane,
is the maximum vertical flying speed of the unmanned aerial vehicle.
9. The method as claimed in claim 1, wherein the early warning levels are displayed in a graded manner by colors, the first early warning level is displayed in green, the second early warning level is displayed in yellow, the third early warning level is displayed in orange, and the fourth early warning level is displayed in red.
10. A computer-readable storage medium, wherein the computer-readable storage medium stores an executable computer program, and when the computer program runs, the method for warning intrusion classification of unmanned aerial vehicles in an airport headroom protection zone according to any one of claims 1 to 9 is realized.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112862914A (en) * | 2021-02-04 | 2021-05-28 | 浙江科技学院 | Visual fusion method for defense area of low-altitude aircraft based on multi-level and multi-core |
| CN113467513A (en) * | 2021-07-21 | 2021-10-01 | 齐鲁空天信息研究院 | Alarm detection method |
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| CN114664121B (en) * | 2022-03-23 | 2024-01-09 | 合肥置顶信息技术有限公司 | Intelligent error correction civil aviation meteorological observation making and publishing system and method |
| CN116400738A (en) * | 2023-06-06 | 2023-07-07 | 成都流体动力创新中心 | Low-cost striking method and system for low-speed unmanned aerial vehicle |
| CN116400738B (en) * | 2023-06-06 | 2023-08-08 | 成都流体动力创新中心 | Low-cost striking method and system for low-speed unmanned aerial vehicle |
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