Method for identifying aircraft based on behavior characteristics

Abstract

The application discloses an aircraft identity recognition method based on behavior characteristics, which comprises the following steps: structuring flight trajectory data, forming a predicted flight trajectory line after predicting a suspected landing airport, calculating the similarity value of each element in the structured predicted flight trajectory line corresponding trajectory data and historical flight trajectory data corresponding to the historical flight trajectory line, finally measuring the similarity between the two trajectory lines by d(A, B), and extracting the aircraft identity information recorded in the historical flight trajectory data with the highest similarity value as the identity recognition result of the aircraft to be identified. The recognition method is simple and efficient, and the accuracy of aircraft identity recognition is ensured by calculating the similarity of each element of each trajectory point.

Description

Technical Field

[0001] This invention relates to the field of data analysis technology, and more specifically to an aircraft identification method based on behavioral characteristics. Background Technology

[0002] Accurate identification of aircraft entering controlled airspace is a crucial means of ensuring airspace security. In recent years, data mining technology has developed rapidly. How to extract valuable data from flight data and, through a series of data processing and analysis, ultimately accurately identify the aircraft has become a pressing technical problem in the field of aviation safety. Summary of the Invention

[0003] The present invention aims to achieve rapid and accurate identification of the target aircraft and provides an aircraft identification method based on behavioral features.

[0004] To achieve this objective, the present invention adopts the following technical solution:

[0005] A method for aircraft identification based on behavioral features is provided, comprising the following steps:

[0006] S1, acquire the trajectory data of the aircraft to be identified and perform data structuring processing;

[0007] S2, with the current flight position of the aircraft as the center, search for airports within a specified radius as suspected landing airports, and connect the current trajectory point with several trajectory points collected at specified intervals and the location of each of the suspected landing airports to obtain at least one predicted flight trajectory line.

[0008] S3, perform similarity matching between each predicted flight trajectory line obtained in step S2 and each historical flight trajectory line, and extract the aircraft identity information from the historical flight trajectory data corresponding to the historical aircraft trajectory line with the highest similarity as the identity recognition result of the aircraft to be identified.

[0009] Preferably, the trajectory data of the aircraft obtained in step S1 includes the aircraft's flight altitude, flight speed, longitude and latitude of flight position at each trajectory point.

[0010] Preferably, the trajectory data also includes the aircraft's departure airport.

[0011] Preferably, in step S2, the airport closest to the aircraft's current flight position found within the specified radius is selected as the suspected intended landing airport.

[0012] Preferably, in step S3, the method for similarity matching between each predicted flight trajectory line and each historical flight trajectory line is expressed by the following formula:

[0013]

[0014] In formula (1), A represents the trajectory data corresponding to the predicted flight trajectory line;

[0015] B represents the historical flight trajectory data corresponding to the historical flight trajectory line;

[0016]

[0017] A∩B represents the number of elements with the same element value in the structured A and B;

[0018] A∪B represents the sum of the number of elements with the same element value and the number of elements with different element values ​​in the structured A and B;

[0019] d(A,B) represents the similarity value between the predicted flight trajectory and the historical flight trajectory.

[0020] This invention uses structured flight trajectory data to form a predicted flight trajectory line after predicting a suspected intended landing airport. Then, it calculates the similarity value of each element in the trajectory data corresponding to the structured predicted flight trajectory line and the historical flight trajectory data corresponding to the historical flight trajectory line. Finally, it uses d(A,B) to measure the similarity between the two trajectory lines and extracts the aircraft identity information recorded in the historical flight trajectory data with the highest similarity value as the identification result of the aircraft to be identified. The identification method is simple and efficient, and the accuracy of aircraft identification is ensured by calculating the similarity of each element of each trajectory point. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments of the present invention will be briefly described below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0022] Figure 1 This is a diagram illustrating the implementation steps of the aircraft identification method based on behavioral features provided in this embodiment of the invention. Detailed Implementation

[0023] The technical solution of the present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0024] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual images. They should not be construed as limiting the scope of this patent. To better illustrate the embodiments of the present invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual dimensions of the product. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0025] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "inner," and "outer" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present patent. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0026] In the description of this invention, unless otherwise explicitly specified and limited, the term "connection" or similar designation indicating a connection between components should be interpreted broadly. For example, it can refer to a fixed connection, a detachable connection, or an integral part; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can refer to the internal communication between two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0027] The aircraft identification method based on behavioral features provided in this invention embodiment, such as... Figure 1 As shown, the steps include:

[0028] S1, acquire the trajectory data of the aircraft to be identified and perform data structuring processing;

[0029] The acquired trajectory data includes the aircraft's flight altitude, flight speed, longitude and latitude of flight position at each trajectory point. If the information of the aircraft's takeoff airport can be obtained, the trajectory data acquired in step S1 will also include the aircraft's takeoff airport.

[0030] One way to structure trajectory data is as follows: the trajectory data is structured in the form of trajectory point name - trajectory point latitude and longitude - flight altitude at the trajectory point - flight speed at the trajectory point. If the information of the departure airport is also obtained, the structured trajectory data can be expressed as trajectory point name - trajectory point latitude and longitude - flight altitude at the trajectory point - flight speed at the trajectory point - departure airport name.

[0031] S2, with the current flight position of the aircraft as the center, search for airports within a specified radius as suspected landing airports, and connect the current trajectory point with several trajectory points collected at specified intervals and the location of each suspected landing airport to obtain at least one predicted flight trajectory line.

[0032] S3. Perform similarity matching between each predicted flight trajectory line obtained in step S2 and each historical flight trajectory line, and extract the aircraft identity information from the historical flight trajectory data corresponding to the historical aircraft trajectory line with the highest similarity as the identity recognition result of the aircraft to be identified.

[0033] In step S3, the method for similarity matching between each predicted flight trajectory line and each historical flight trajectory line is expressed by the following formula:

[0034]

[0035] In formula (1), A represents the trajectory data corresponding to the predicted flight trajectory line;

[0036] B represents the historical flight trajectory data corresponding to the historical flight trajectory line;

[0037]

[0038] A∩B represents the number of elements with the same element value in the structured A and B;

[0039] A∪B represents the sum of the number of elements with the same element value and the number of elements with different element values ​​in the structured A and B;

[0040] d(A,B) represents the similarity value between the predicted flight trajectory and the historical flight trajectory.

[0041] An example of a method for calculating the similarity between a predicted flight trajectory and a historical flight trajectory is as follows:

[0042] For example, the trajectory data corresponding to the predicted flight trajectory line, after structured processing, is expressed as: trajectory point A - latitude and longitude of trajectory point A - flight altitude of the aircraft at trajectory point A - flight speed at trajectory point A - trajectory point B - latitude and longitude of trajectory point B - flight altitude of the aircraft at trajectory point B - flight speed at trajectory point B - trajectory point C - latitude and longitude of trajectory point C - flight altitude of the aircraft at trajectory point C - flight speed at trajectory point C - suspected intended landing airport is X;

[0043] The historical flight trajectory data corresponding to a certain historical flight trajectory line is expressed as follows after structured processing: trajectory point D - latitude and longitude of trajectory point D - flight altitude of historical aircraft at trajectory point D - flight speed at trajectory point D - trajectory point E - latitude and longitude of trajectory point E - flight altitude of historical aircraft at trajectory point E - flight speed at trajectory point E - trajectory point F - latitude and longitude of trajectory point F - flight altitude of historical aircraft at trajectory point F - flight speed at trajectory point F - landing airport is X;

[0044] If the difference between the latitude and longitude of trajectory point A and trajectory point D is less than a preset latitude and longitude difference threshold, then the element value of "latitude and longitude of trajectory point A" in the structured data is determined to be the same as the element value of "latitude and longitude of trajectory point D," and the number of intersections between the predicted flight trajectory line and the historical flight trajectory line is incremented by "1." Conversely, if the difference between the aircraft's flight altitude at trajectory point A and the historical aircraft's flight altitude at trajectory point D is greater than a preset altitude difference threshold, then the element value of "flight altitude of aircraft at trajectory point A" in the structured data is determined to be different from the element value of "flight altitude of historical aircraft at trajectory point D," and the number of unions between the predicted flight trajectory line and the historical flight trajectory line is incremented by "1." Finally, the aircraft identity information in the historical flight trajectory data corresponding to the historical flight trajectory line with the largest d(A,B) value is extracted as the aircraft identity recognition result to be identified.

[0045] It should be noted that the historical flight trajectory data corresponding to the historical flight trajectory lines includes the historical aircraft's identity information. For example, the historical aircraft's identity information is expressed as "Civil Aviation Passenger C919, belonging to XXX Company." This identity information is one of the data elements in the structured historical flight trajectory data. The historical flight trajectory data is stored in a database or in the cloud.

[0046] After identifying and verifying the aircraft's identity, the identification result is added to the structured trajectory data to form the historical flight trajectory data of the aircraft after identity recognition, which is then added to the database.

[0047] This invention uses structured flight trajectory data to form a predicted flight trajectory line after predicting a suspected intended landing airport. Then, it calculates the similarity value of each element in the trajectory data corresponding to the structured predicted flight trajectory line and the historical flight trajectory data corresponding to the historical flight trajectory line. Finally, it uses d(A,B) to measure the similarity between the two trajectory lines and extracts the aircraft identity information recorded in the historical flight trajectory data with the highest similarity value as the identification result of the aircraft to be identified. The identification method is simple and effective, and the accuracy of aircraft identification is ensured by calculating the similarity of each element of each trajectory point.

[0048] It should be stated that the above-described specific embodiments are merely preferred embodiments of the present invention and the technical principles employed. Those skilled in the art should understand that various modifications, equivalent substitutions, and variations can be made to the present invention. However, such variations, as long as they do not depart from the spirit of the present invention, should be within the scope of protection of the present invention. Furthermore, some terminology used in this specification and claims is not limiting, but merely for ease of description.

Claims

1. An aircraft identification method based on behavior characteristics, characterized by the steps of Comprise: S1, obtaining the trajectory data of the aircraft to be identified and structuring the data; S2, taking the current flight position of the aircraft as the center, searching for the airport existing in the specified radius range as the suspected landing airport, and connecting the current trajectory point and the subsequent several trajectory points collected at specified time intervals and the site of each suspected landing airport to obtain at least one predicted flight trajectory line; S3, matching each predicted flight trajectory line obtained in step S2 with each historical flight trajectory line for similarity, and extracting the aircraft identity information in the historical flight trajectory data corresponding to the highest similarity historical flight trajectory line as the identity identification result of the aircraft to be identified; The trajectory data of the aircraft obtained in step S1 includes the flight height, flight speed, longitude and latitude of the flight position of the aircraft at each trajectory point; In step S3, the similarity matching method for each predicted flight trajectory line and each historical flight trajectory line is expressed by the following formula: In equation (1), representing the trajectory data corresponding to the predicted flight trajectory line; representing the historical flight trajectory data corresponding to the historical flight trajectory line; ； number of elements in the structure and number of elements with the same element value in representing the structured and the number of elements having the same element value and the cumulative number of elements having different element values in the middle characterizing a similarity value of the predicted flight trajectory line to the historical flight trajectory line.

2. The method of claim 1, wherein, The trajectory data also includes the take-off airport of the aircraft. 3.The method of claim 1, wherein, In step S2, the airport closest to the current flight position of the aircraft in the specified radius range is searched as the suspected landing airport.

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