CN112330982A - Medium-term conflict early warning method, device and storage medium applied to terminal area - Google Patents
Medium-term conflict early warning method, device and storage medium applied to terminal area Download PDFInfo
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Abstract
The invention discloses a medium-term conflict early warning method, equipment and a storage medium applied to a terminal area, which comprise the following steps: s100, obtaining historical track data of flights, wherein the historical track data comprises track dynamic data, planning dynamic data and instruction data; s200, performing intention identification on the historical flight path data through an intention identifier to obtain flight intention data and a future flight path shape; s300, predicting a four-dimensional position of the flight within the future preset time based on the flight intention data and the historical track data; s400, performing conflict detection based on the four-dimensional position of the flight within the future preset time, and calculating the conflict probability within the future preset time; and S500, if the conflict probability exceeds a threshold value, giving an early warning prompt to the flight conflict event if the flight conflict event exists. The method can effectively and accurately predict the future flight track shape of the flight and perform early warning on the flight conflict time.
Description
Technical Field
The invention relates to the technical field of civil aviation traffic control, in particular to a medium-term conflict early warning method, medium-term conflict early warning equipment and medium, which are applied to a terminal area.
Background
The air traffic control automation system is used as a core system for implementing air traffic control by a civil aviation air traffic control department, provides display of air flight situation and warning of various flight conflicts and various exceptions for a controller by processing monitoring data such as radar signals, provides relevant information and management means of the flight plan and the flight dynamics for the controller by processing the flight plan and the dynamic telegraph, and plays an important role in ensuring safe implementation of a civil aviation air traffic control task.
The collision early warning is one of main functions of an air traffic control automation system and is used for detecting the condition that the distance between airplanes is smaller than a safety interval in a future period of time. The prediction time period can be divided into short term, medium term and long term. The medium-term conflict early warning generally refers to an early warning function with early warning time of 5-30 minutes. The terminal area is an airspace with the airport as the center and the height below 6000 meters. The aircraft in the airspace is usually in the stage of takeoff climbing or landing descending, and the flight height and direction change frequently.
The existing middle-term conflict early warning method has the following problems: 1. the early warning accuracy is not high, the prediction on the motion change for a long time is insufficient, and the false alarms are more; 2. the model is complex, the calculated amount is large, and the real-time alarm requirement cannot be met; for example, in a probability type calculation method, the probability is used for predicting the probability of conflict of multiple tracks in the future, the requirement on calculation performance is high, and the real-time performance of alarm is poor; the application requirements cannot be met. Therefore, the middle-term collision early warning function actually applied in the air traffic control automation system is only applied to a high-altitude airspace (cruise stage) and cannot be applied to a terminal area.
Disclosure of Invention
In order to overcome the defects of the prior art, the second objective of the invention is to provide a medium-term conflict early warning method applied to a terminal area, which can effectively and accurately predict the future flight track shape of a flight and carry out early warning on the flight conflict time.
The second objective of the present invention is to provide an electronic device, which executes the above-mentioned medium-term conflict warning method applied to a terminal area, and can effectively and accurately predict the future flight trajectory shape of a flight, and perform a warning on the flight conflict time.
The invention also aims to provide a storage medium, which executes the medium-term conflict early warning method applied to the terminal area, can effectively and accurately predict the future flight track shape of the flight and can early warn the flight conflict time.
One of the purposes of the invention is realized by adopting the following technical scheme:
a middle-term conflict early warning method applied to a terminal area comprises the following steps:
s100, obtaining historical track data of flights, wherein the historical track data comprises track dynamic data, planning dynamic data and instruction data;
s200, performing intention identification on the historical flight path data through an intention identifier to obtain flight intention data and a future flight path shape;
s300, predicting a four-dimensional position of the flight within the future preset time based on the flight intention data and the historical track data;
s400, performing conflict detection based on the four-dimensional position of the flight within the future preset time, and calculating the conflict probability within the future preset time;
and S500, if the conflict probability exceeds a threshold value, giving an early warning prompt to the flight conflict event if the flight conflict event exists.
Further, in the step S200, performing intent recognition on the historical flight path data through an intent recognizer to obtain flight intent data and a future flight path shape, including the following steps:
step S210, extracting historical track data deviating from a plan from the historical track data, and recording the historical track data deviating from the plan as t;
step S220, classifying the historical track data deviated from the plan according to the shapes of areas and tracks, recording the area corresponding to each track data as a, recording the shape corresponding to each track as S, representing each track data as { a, S, t }, and classifying each track according to { a, S }, so as to obtain a classification C;
step S230, processing the track of the classification C, and marking the flight intention i for each classification, wherein each classification is expressed as { a, S, i, { t | t with characteristics a, S } };
and step S240, performing dimension reduction processing on the historical track data t of each deviation plan of the classification C through an association analysis method to obtain a characteristic value set f, wherein the historical track data has characteristic values { a, f }, the flight intention i of the historical track data is presumed, and the future flight track shape is S.
Further, the step S300 of predicting the four-dimensional position of the flight within the future preset time based on the flight intention data and the historical track data includes the following steps:
step S310, predicting the coincidence degree of the flight path and the dynamic flight plan according to the real-time flight path, the dynamic flight plan and the control instruction;
step S320, if the coincidence degree of the predicted flight path and the dynamic flight plan exceeds a threshold value, predicting a short-term flight intention i and a flight path shape S in the dynamic flight plan by taking the dynamic flight plan as a main part; if the coincidence degree of the predicted flight path and the dynamic flight plan is lower than a threshold value, calculating a characteristic value { a, f } of the flight path to deduce a flight intention i and a future flight path shape s;
step S330, calculating the predicted four-dimensional position and probability p of the flight path at regular intervals according to the real-time flight dynamic state of the flight path, and expressing the predicted four-dimensional position and probability of each flight path as { time, x, y, h, p }, wherein time is time, x and y are coordinates of the position, h is height, and p is probability.
Further, the step S400 of performing collision detection based on the four-dimensional position of the flight within the future preset time, and calculating the collision probability within the future preset time includes the following steps:
s410, acquiring a predicted four-dimensional position set of potential conflict flights, and calculating the horizontal interval and the vertical interval of every two flights at the time T of a predicted point;
and step S420, judging whether the horizontal interval or the vertical interval is smaller than a safety interval, and if the horizontal interval or the vertical interval is smaller than the safety interval, calculating the probability of the occurrence of the conflict event in the future prediction time.
Further, the probability of occurrence of a collision event is calculated by the following formula:
Further, the step S500 of performing an early warning prompt on the flight conflict event is to display the flight conflict event according to the urgency of the flight conflict event and the influence object.
Further, the track dynamics comprises the position, the height, the speed, the course, the turning speed and the lifting speed of the airplane; the plan dynamic data comprises dynamic flight records and aviation message data of an automatic system; the command data includes commands from ground controllers and pilots.
Further, the historical track data is obtained through a ground-air data link, an air traffic control automation system, ADS-B and a multipoint positioning system.
The second purpose of the invention is realized by adopting the following technical scheme:
an apparatus comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement a medium term collision warning method applied to a terminal area as described above.
The third purpose of the invention is realized by adopting the following technical scheme:
a storage medium having stored thereon a computer program which, when executed, implements a medium term collision warning method applied to a terminal area as described in any one of the above.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a medium-term conflict early warning method applied to a terminal, electronic equipment and a storage medium. The method can effectively and accurately predict the future flight track shape of the flight, early warn the flight conflict time, has high real-time performance, and solves the problem that the current air traffic control system cannot be applied to medium-term conflict early warning in a terminal area.
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Fig. 1 is a schematic flow chart of a first embodiment of 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.
Example one
As shown in fig. 1, the present invention provides a medium term collision early warning method applied to a terminal area, which includes the following steps:
step S100, obtaining historical track data of the flight, wherein the historical track data comprises track dynamic data, planning dynamic data and instruction data. Specifically, the track dynamics is the comprehensive track through a ground-air data link and an air traffic control automatic system, and the data output by the ground radar, the ADS-B and the multipoint positioning system are selected from the data with high applicability and high real-time performance, and specifically include the position, the height, the speed, the course, the turning speed and the lifting speed of the airplane. The plan dynamic data comprises dynamic flight records and aviation message data of an automatic system; the command data comprises commands of ground controllers and pilots, and can be acquired through an air traffic control automation system, an air-ground data link or other ways.
And S200, performing intention identification on the historical flight path data through an intention identifier to obtain flight intention data and a future flight path shape. The consciousness recognizer is constructed based on historical data of airplane flight in the terminal area, and can predict the future flight altitude, course change and other conditions of the flight. The method specifically comprises the following steps:
step S210, extracting historical track data deviating from a plan from the historical track data, and recording the historical track data deviating from the plan as t (track); the historical track data of the departure plan comprises information such as track dynamics, flight intentions and the like, and specifically comprises position, altitude, planned route, heading, turning speed, ascending/descending speed and the like.
Step S220, classifying the historical track data deviated from the plan according to the shapes of areas and tracks, recording the area corresponding to each track data as a, recording the shape corresponding to each track as S, representing each track data as { a, S, t }, and classifying each track according to { a, S }, so as to obtain a classification C;
step S230, processing the track of the classification C, and marking the flight intention i for each classification, wherein each classification is expressed as { a, S, i, { t | t with characteristics a, S } };
step S240, performing dimension reduction processing on the historical track data t of each deviation plan of the category C by using an association analysis method to obtain a feature value set f, and then the consciousness recognizer can represent the historical track as having the feature values { a, f }, so as to estimate the flight intention i, where the future flight trajectory shape is S. Specifically, each historical track data t includes a plurality of attributes, such as position, altitude, speed, heading, lift, commanded altitude, selected altitude, next waypoint, and the like. And analyzing the association degree of the attribute and whether the attribute drifts by using a Principal Component Analysis (PCA) method to obtain an attribute subset with higher association degree, thereby obtaining the characteristic value set f. Generally, the number of attribute values included in the historical track data t is not more than 10 (about 5-7), so that a relatively accurate result can be obtained, the characteristic attribute dimension can be reduced from tens of attributes to single-digit attributes, and a large number of operations are reduced.
S300, predicting a four-dimensional position of the flight within the future preset time based on the flight intention data and the historical track data; the flight intent data and the future flight trajectory shape s are analyzed and obtained by the intent recognizer, and the four-dimensional position of the predicted flight within the future preset time is executed by the four-dimensional flight path prediction module. The specific prediction steps are as follows:
step S310, predicting the coincidence degree of the flight path and the dynamic flight plan according to the real-time flight path, the dynamic flight plan and the control instruction; the actual flight path and the dynamic flight plan are acquired through an automatic system or aviation message data.
Step S320, if the coincidence degree of the predicted flight path and the dynamic flight plan exceeds a threshold value, predicting a short-term flight intention i and a flight path shape S in the dynamic flight plan by taking the dynamic flight plan as a main part; and if the coincidence degree of the predicted flight path and the dynamic flight plan is lower than a threshold value, calculating the characteristic values { a, f } of the flight path so as to deduce a flight intention i and a future flight path shape s. Specifically, the threshold is a parameter for a specific airspace, and needs to be adjusted according to different airspaces and flight characteristics. Preferably, when the flight path is high, the projection distance between the flight path position and the planned flight path does not exceed 20 kilometers, and the angle difference between the heading and the current flight path does not exceed 5 degrees. But under different airports and entering and leaving modes, the adjustment is needed according to the actual situation.
The specific way to calculate the track characteristic values { a, f } is explained in conjunction with the following example:
suppose that the future leg in the flight plan for flight A is A1- > A2- > A3.
1. If the current state of the flight path A is judged to be consistent with the plane plan, the predicted flight path is also basically consistent with A1- > A2- > A3.
2. If it is determined that the current state of flight path a does not match the flight plan (e.g., the shortest distance between the aircraft and the planned flight path is greater than 20 km), the system finds the closest class from class C in S240 according to the current flight characteristics f of flight path a, and calculates the next flight path of flight path a according to the flight path shape S corresponding to class C.
And S330, calculating the predicted four-dimensional position and probability p of the flight path at regular intervals according to the real-time flight dynamic of the flight path, and expressing the predicted four-dimensional position and probability of each flight path as { time, x, y, h, p }. The real-time flight dynamics comprises factors such as the position, the height, the speed, the ascending/descending speed, the turning speed and the flight performance of the flight dynamics, and the four-dimensional position and the probability of a flight path are calculated at regular intervals, such as every 1 second and every 5 seconds, so as to obtain the four-dimensional position and the probability { time, x, y, h and p } predicted by each flight path, wherein time is time, x and y are coordinates of the position, h is the height, and p is the probability. The probability is the probability that the aircraft is present at a certain location. For example, flight a is currently heading 90 degrees (east). After 5 seconds, its heading may be constant or variable, in each case with a certain statistical probability, such as: keeping the flight path at 90 degrees with 50% probability, and keeping the position at P1 after 5 seconds; the flight path has 15% probability of being changed into 87 degrees, and the position is P2 after 5 seconds; the flight path becomes 93 degrees with 15% probability and the position is at P3 after 5 seconds, so the calculation needs to be done according to the real-time flight dynamics.
S400, performing conflict detection based on the four-dimensional position of the flight within the future preset time, and calculating the conflict probability within the future preset time; the method specifically comprises the following steps:
s410, acquiring a predicted four-dimensional position set of potential conflict flights, and calculating the horizontal interval and the vertical interval of every two flights at a predicted time point T; the potential conflict flight refers to a flight which is possible to conflict in a preset time, the flight is aligned with the time T of the predicted point, and the vertical interval and the horizontal interval between every two flights are judged through the presumed four-dimensional position.
And step S420, judging whether the horizontal interval or the vertical interval is smaller than a safety interval, and if the horizontal interval or the vertical interval is smaller than the safety interval, calculating the probability of the occurrence of the conflict event in the future prediction time. Specifically, the probability of the occurrence of the collision time is calculated by the following formula:
The probability of collision time is described below with reference to an example:
assume that after 5 seconds, track A is at Pa1Probability of (5) 25%, Pa2Has a probability of 12%, and track B appears at Pb1Has a probability of 10% of Pb2The probability of (2) is 13%;
2、Pa1and Pb1Will conflict, track A is at Pa1And track B at Pb1The probability of collision is 25% by 10% to 2.5%;
3、Pa2and Pb2Conflict can occur, and the flight path A and the flight path B are in Pa2And Pb2Collision probability is 12% by 13% to 1.56%;
4. after 5 seconds, the probability of collision between a and B is 2.5% + 1.56% — 4.06%;
and S500, if the conflict probability exceeds a threshold value, giving an early warning prompt to the flight conflict event if the flight conflict event exists. The early warning prompt specifically means that according to the emergency degree and the influence object of the flight conflict event, early warning information is displayed in an acousto-optic prompt mode to remind a worker to schedule the flight conflict event.
The invention provides a middle-term conflict early warning method, electronic equipment and a storage medium applied to a terminal, which are used for accurately predicting four-dimensional tracks of flight in middle and short periods according to the historical track data of the flight, real-time positions, flight plans and flight intentions, calculating the conflict probability of the flight in the future preset time and early warning on the basis of the conflict probability. The method can effectively and accurately predict the future flight track shape of the flight, early warn the flight conflict time, has high real-time performance, and solves the problem that the current air traffic control system cannot be applied to medium-term conflict early warning in a terminal area.
Example two
The present invention also provides an electronic device comprising a memory, a processor and a program stored in the memory, the program being configured to be executed by the processor, the processor implementing the steps of the above-mentioned medium term collision warning method applied to the terminal area when executing the program.
In addition, the present invention further provides a storage medium, where the storage medium stores a computer program, and the computer program, when executed by a processor, implements the steps of the aforementioned medium-term collision warning method applied to a terminal area. The invention is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet-type devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
The apparatus in this embodiment and the method in the foregoing embodiment are based on two aspects of the same inventive concept, and the method implementation process has been described in detail in the foregoing, so that those skilled in the art can clearly understand the structure and implementation process of the system in this embodiment according to the foregoing description, and for the sake of brevity of the description, details are not repeated here.
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. A medium-term conflict early warning method applied to a terminal area is characterized by comprising the following steps:
s100, obtaining historical track data of flights, wherein the historical track data comprises track dynamic data, planning dynamic data and instruction data;
s200, performing intention identification on the historical flight path data through an intention identifier to obtain flight intention data and a future flight path shape;
s300, predicting a four-dimensional position of the flight within the future preset time based on the flight intention data and the historical track data;
s400, performing conflict detection based on the four-dimensional position of the flight within the future preset time, and calculating the conflict probability within the future preset time;
and S500, if the conflict probability exceeds a threshold value, giving an early warning prompt to the flight conflict event if the flight conflict event exists.
2. The medium term collision warning method applied to the terminal area as claimed in claim 1, wherein the step S200 performs an intention recognition on the historical flight path data through an intention recognizer to obtain flight intention data and a future flight trajectory shape, and includes the following steps:
step S210, extracting historical track data deviating from a plan from the historical track data, and recording the historical track data deviating from the plan as t;
step S220, classifying the historical track data deviated from the plan according to the shapes of areas and tracks, recording the area corresponding to each track data as a, recording the shape corresponding to each track as S, representing each track data as { a, S, t }, and classifying each track according to { a, S }, so as to obtain a classification C;
step S230, processing the track of the classification C, and marking the flight intention i for each classification, wherein each classification is expressed as { a, S, i, { t | t with characteristics a, S } };
and step S240, performing dimension reduction processing on the historical track data t of each deviation plan of the classification C through an association analysis method to obtain a characteristic value set f, wherein the historical track data has characteristic values { a, f }, the flight intention i of the historical track data is presumed, and the future flight track shape is S.
3. The medium term collision warning method applied to the terminal area as claimed in claim 2, wherein the step S300 of predicting the four-dimensional position of the flight within the future preset time based on the flight intention data and the historical track data comprises the following steps:
step S310, predicting the coincidence degree of the flight path and the dynamic flight plan according to the real-time flight path, the dynamic flight plan and the control instruction;
step S320, if the coincidence degree of the predicted flight path and the dynamic flight plan exceeds a threshold value, predicting a short-term flight intention i and a flight path shape S in the dynamic flight plan by taking the dynamic flight plan as a main part; if the coincidence degree of the predicted flight path and the dynamic flight plan is lower than a threshold value, calculating a characteristic value { a, f } of the flight path to deduce a flight intention i and a future flight path shape s;
step S330, calculating the predicted four-dimensional position and probability p of the flight path at regular intervals according to the real-time flight dynamic state of the flight path, and expressing the predicted four-dimensional position and probability of each flight path as { time, x, y, h, p }, wherein time is time, x and y are coordinates of the position, h is height, and p is probability.
4. The medium term collision early warning method applied to the terminal area according to claim 3, wherein the step S400 of performing collision detection based on a four-dimensional position of the flight within a preset future time and calculating the collision probability within the preset future time comprises the following steps:
s410, acquiring a predicted four-dimensional position set of potential conflict flights, and calculating the horizontal interval and the vertical interval of every two flights at the time T of a predicted point;
and step S420, judging whether the horizontal interval or the vertical interval is smaller than a safety interval, and if the horizontal interval or the vertical interval is smaller than the safety interval, calculating the probability of the occurrence of the conflict event in the future prediction time.
5. The medium term collision warning method applied to the terminal area according to claim 4, wherein the probability of collision occurrence is calculated by the following formula:
6. The medium term collision warning method applied to the terminal area as claimed in claim 1, wherein the warning prompt for the flight collision event in step S500 is to display the flight collision event according to the urgency of the flight collision event and the influence object.
7. The method as claimed in claim 1, wherein the flight path dynamics includes position, altitude, speed, heading, turning speed, and lifting speed of the aircraft; the plan dynamic data comprises dynamic flight records and aviation message data of an automatic system; the command data includes commands from ground controllers and pilots.
8. The medium term collision warning method applied to the terminal area as claimed in claim 7, wherein the historical track data is obtained through a ground-air data link, an air traffic control automation system, ADS-B, a multipoint positioning system.
9. An apparatus comprising a processor, a memory and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method of any one of claims 1 to 8 for middle collision warning in a terminal area.
10. A storage medium having a computer program stored thereon, wherein the computer program is executed to implement the medium term collision warning method applied to a terminal area according to any one of claims 1 to 8.
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