Aviation noise identification method based on flight path

Abstract

The invention discloses an aviation noise identification method based on a track, and the method comprises the following steps: querying track data in the last hour according to the current time, the track data comprising a plurality of tracks; calculating a PCA value of any track at a ground monitoring station according to the track data; a time range is determined through PCA point time, sound propagation time and error time, and aviation noise event identification is carried out in the time range; and for the identified aviation noise event, establishing an association relationship between the aviation noise event and the track, thereby outputting an aviation noise event set under the track, and performing noise monitoring at the time node where the track exists, so that the aviation noise event can be identified more accurately.

Description

Technical Field

[0001] The present invention relates to the technical field of aviation noise identification, and in particular to an aviation noise identification method based on flight tracks. Background Art

[0002] Traditional aviation noise identification methods usually rely on threshold settings in noise monitoring equipment to identify noise events. Specifically, this method pre-sets a noise threshold in the noise monitoring equipment, and when the monitored noise level exceeds this threshold, the device will generate a noise event record. Afterwards, these noise events will be used to match the aircraft's track data to identify which noise events are generated by the aircraft. The current identification method still has the following problems: 1. Threshold setting problem: If the threshold is set too high, only very strong noise will be identified as a noise event, which will cause many actual aviation noise events to not be captured. On the contrary, if the threshold is set too low, many non-aviation noise events will be mistakenly identified as aviation noise events, increasing the workload and cost of subsequent processing; 2. Due to improper threshold setting, the system may generate a large number of false alarms (i.e. non-aviation noise events are identified as aviation noise events) and missed alarms (i.e. real aviation noise events are not identified); 3. A large number of false alarms will occupy server resources, increase the time and cost of data processing, and also increase the workload of manual review; 4. Since manual intervention is required to distinguish between real aviation noise events and other types of noise events, this reduces the efficiency of the entire identification process.

[0003] In summary, traditional methods have many limitations in identifying aviation noise events, and new solutions need to be found to improve identification accuracy and efficiency. Summary of the invention

[0004] In view of the above-mentioned prior art, the present invention provides an aviation noise identification method based on flight path, which mainly solves the technical problems existing in the above-mentioned background technology.

[0005] To achieve the above object, the technical solution of the embodiment of the present invention is implemented as follows:

[0006] A method for identifying aviation noise based on flight tracks, the method comprising the following steps:

[0007] Query the track data within the last hour according to the current time, where the track data contains multiple tracks;

[0008] Calculate the PCA value of any track at the ground monitoring site according to the track data;

[0009] The time range is determined by using PCA point time, sound propagation time and error time, and aviation noise events are identified within this time range;

[0010] For the identified aviation noise event, an association relationship between the aviation noise event and the aforementioned flight track is established, thereby outputting an aviation noise event set under the flight track.

[0011] Optionally, the track data within the last hour is queried based on the current time, specifically including: obtaining the current system time, subtracting a time difference of one hour from the current time to determine the starting time point of the query, and exporting the track data from a third-party track software based on the starting time point of the query.

[0012] Optionally, the PCA value of any track at the ground monitoring site is calculated based on the track data, wherein the PCA value includes: the elevation angle, the height when the aircraft flies over the aforementioned closest point, the time point when the aircraft is closest to the ground monitoring site, and the slant distance, and is calculated separately by the following methods:

[0013] Acquire radar data of the aircraft within a specific time period, wherein the radar data includes latitude, longitude and altitude information of the aircraft;

[0014] The slant distance between the aircraft and the ground monitoring station is calculated based on the aircraft's latitude and longitude information and the ground monitoring station's latitude and longitude information;

[0015] Finding the time when the aircraft is closest to the ground monitoring station and the altitude when it flies over the closest point based on the radar data;

[0016] Based on the slant range and the aircraft's altitude when it passed the aforementioned closest point, the elevation angle is calculated.

[0017] Optionally, the time range is determined by the PCA point time, the sound propagation time, and the error time, including:

[0018] Setting the error time and obtaining the sound propagation time from the aircraft to the ground monitoring site based on the slant range and the speed of sound;

[0019] The time range of the noise event is determined by adding the PCA point time to the sound propagation time and the error time, where the PCA point time refers to the time point when the aircraft is closest to the ground monitoring station.

[0020] Optionally, aviation noise event identification is performed within the time range, specifically including: within the aforementioned time range, all sound events are acquired through noise monitoring equipment, and the Leq value, spectrum, and LAS value of the sound events are calculated respectively; if the Leq value, spectrum, and LAS value of the sound event all meet the requirements, the sound event is determined to be an aviation noise event.

[0021] Optionally, determine whether the Leq value, spectrum, and LAS value of the sound event meet the requirements, including:

[0022] For the Leq value and the LAS value, if both the Leq value and the LAS value exceed the corresponding threshold value, the Leq value and the LAS value of the sound event meet the requirements;

[0023] For the spectrum value, compare the spectrum in the sound event with the spectrum in a typical aviation noise event to determine whether the similarity of the spectrum meets the requirements.

[0024] Optionally, judging whether the similarity of the spectrum meets the requirement includes:

[0025] The shape similarity between the spectrum in the sound event and the spectrum in a typical aviation noise event is determined by a similarity comparison method;

[0026] Compare the energy distribution similarity of the spectrum in the sound event with that in typical aviation noise events through spectral density or energy distribution diagram;

[0027] If the shape similarity and energy distribution similarity of the spectrum meet the requirements, it means that the spectrum in the sound event is similar to the spectrum in a typical aviation noise event.

[0028] The beneficial effects of the present invention are as follows: the track-based aviation noise identification method proposed in the present application can more accurately identify aviation noise events by performing noise monitoring at time nodes where the track exists; secondly, the time range of the aviation noise event is determined by precise calculation, thereby reducing the amount of noise data that needs to be processed, thereby reducing the occupancy of server resources and saving computing resources; due to the improvement in identification accuracy, the workload of subsequent manual review is reduced, and the overall work efficiency is improved; finally, through a comprehensive analysis of the Leq value, spectrum and LAS value, it is ensured that the identified noise event is a valid aviation noise event, rather than other types of noise events. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 The figure is a flow chart of a method for identifying aviation noise based on flight path in an embodiment of the present application. DETAILED DESCRIPTION

[0030] The technical solution of the present invention is further elaborated in detail below in conjunction with the drawings and specific embodiments of the specification. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention. In the following description, the expression "some embodiments" is related to a subset of all possible embodiments, but it should be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict.

[0031] In the following description, a large number of specific details are provided to provide a more thorough understanding of the present invention. However, it is apparent to those skilled in the art that the present invention can be implemented without one or more of these details. In other examples, in order to avoid confusion with the present invention, some technical features well known in the art are not described.

[0032] It should be understood that the present invention can be implemented in different forms and should not be interpreted as being limited to the embodiments proposed herein. On the contrary, providing these embodiments will make the disclosure thorough and complete, and the scope of the present invention will be fully conveyed to those skilled in the art. And the purpose of the terms used herein is only to describe specific embodiments and is not intended to be a limitation of the present invention. When used herein, the singular forms of "one", "one" and "said / the" are also intended to include plural forms, unless the context clearly indicates another way. It should also be understood that the terms "compose" and / or "include" when used in this specification determine the presence of the features, integers, steps, operations, elements and / or parts, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, parts and / or groups. When used herein, the term "and / or" includes any and all combinations of the relevant listed items.

[0033] It should also be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "inside", "outside", "left", "right" and similar expressions used herein are for illustrative purposes only and are not intended to be the only implementation method.

[0034] In order to fully understand the present invention, a detailed structure will be proposed in the following description to illustrate the technical solution proposed by the present invention. The optional embodiments of the present invention are described in detail as follows, but in addition to these detailed descriptions, the present invention may also have other implementations.

[0035] Please refer to the attached Figure 1 The present application provides a method for identifying aviation noise based on flight path, the method comprising the following steps:

[0036] S1. Query the track data within the last hour according to the current time, where the track data includes multiple tracks;

[0037] S2, calculating the PCA value of any track at the ground monitoring site according to the track data;

[0038] S3, determining the time range by using the PCA point time, the sound propagation time and the error time, and identifying the aviation noise event within the time range;

[0039] S4. For the identified aviation noise event, an association relationship between the aviation noise event and the aforementioned flight track is established, thereby outputting an aviation noise event set under the flight track.

[0040] In an optional implementation, querying the track data within the last hour based on the current time in step S1 specifically includes: obtaining the current time of the system, subtracting a time difference of one hour from the current time to determine the starting time point of the query, and exporting the track data from a third-party track software based on the starting time point of the query.

[0041] Among them, third-party track software includes FlightAware: This is a well-known flight tracking website that provides detailed flight tracking information. You can obtain track data by visiting the FlightAware website, entering a specific flight number or viewing past flight records. Airline database: Airline's own database: Many airlines will record detailed flight tracks of flights, and these data are usually stored in their internal databases. If you have access to these databases, you can query the required track data from them. Aviation regulatory authorities: Aviation regulatory authorities database: Aviation regulatory authorities in various countries (such as the FAA in the United States, EASA in Europe, etc.) usually also collect and store aviation track data. These data may need to be obtained through formal application procedures. Professional track analysis tools: Track analysis software: There are many professional track analysis tools on the market that can read and parse track files in specific formats (such as GPX files). For example, Google Earth software can be used to open and view track changes in GPX files. Nautical charts and navigation software: Guye Electronic Chart: This is a navigation software used to display tracks. If you are using this type of software, you can enable the track function in the software and select the corresponding menu operation to display or save track data. Third-Party Data Providers: In addition to the sources listed above, there are also a number of third-party service providers that specialize in providing track data and may sell or provide access.

[0042] In an optional implementation, in step S2, the PCA value of any track at the ground monitoring site is calculated based on the track data, wherein the PCA value includes: the elevation angle, the height when the aircraft flies over the aforementioned closest point, the time point when the aircraft is closest to the ground monitoring site, and the slant distance, and is calculated separately by the following methods:

[0043] Acquire radar data of the aircraft within a specific time period, wherein the radar data includes latitude, longitude and altitude information of the aircraft;

[0044] Based on the latitude and longitude information of the aircraft and the latitude and longitude information of the ground monitoring station, the slant distance d between the two is calculated;

[0045] The specific calculation formula of the slope distance d is as follows:

[0046] d = R*arccos(sin(lat plane )sin(lat site ))+cos(lat plane )*cos(lat site )*cos(lon plane -lon site )

[0047] where lat plane is the latitude of the aircraft, lon plane is the longitude of the aircraft, lat site is the latitude of the site, lon site is the longitude of the site, and R is the radius of the Earth.

[0048] Finding the time when the aircraft is closest to the ground monitoring station and the altitude when it flies over the closest point based on the radar data;

[0049] Based on the slant range and the altitude of the aircraft when it passes the aforementioned closest point, the elevation angle θ is calculated.

[0050] The elevation angle θ is calculated by the following formula:

[0051]

[0052] Where h is the aircraft altitude.

[0053] Furthermore, the time range is determined by the PCA point time, the sound propagation time and the error time, including:

[0054] Setting the error time and obtaining the sound propagation time from the aircraft to the ground monitoring site based on the slant range and the speed of sound;

[0055] The time range of the noise event is determined by adding the PCA point time to the sound propagation time and the error time, where the PCA point time refers to the time point when the aircraft is closest to the ground monitoring station.

[0056] Furthermore, aviation noise events are identified within the time range, specifically including: within the aforementioned time range, all sound events are acquired through noise monitoring equipment, and the Leq value, spectrum, and LAS value of the sound events are calculated respectively; if the Leq value, spectrum, and LAS value of the sound event all meet the requirements, the sound event is determined to be an aviation noise event.

[0057] In an optional implementation, determining whether the Leq value, spectrum, and LAS value of the sound event meet the requirements specifically includes:

[0058] For the Leq value and the LAS value, if both the Leq value and the LAS value exceed the corresponding threshold value, the Leq value and the LAS value of the sound event meet the requirements;

[0059] For the spectrum value, compare the spectrum in the sound event with the spectrum in a typical aviation noise event to determine whether the similarity of the spectrum meets the requirements.

[0060] The methods for calculating the Leq value and the LAS value are common knowledge to those skilled in the art and will not be elaborated in detail in this embodiment.

[0061] Furthermore, it is determined whether the similarity of the spectrum meets the requirements, specifically including:

[0062] The shape similarity between the spectrum in the sound event and the spectrum in a typical aviation noise event is determined by a similarity comparison method;

[0063] Compare the energy distribution similarity of the spectrum in the sound event with that in typical aviation noise events through spectral density or energy distribution diagram;

[0064] If the shape similarity and energy distribution similarity of the spectrum meet the requirements, it means that the spectrum in the sound event is similar to the spectrum in a typical aviation noise event.

[0065] If the similarity score exceeds the preset threshold, it is considered to be a valid aviation noise event, otherwise, it is considered to be a non-aviation noise event.

[0066] Finally, the identified aviation noise events and their association with the flight tracks are saved.

[0067] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. The protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for identifying aviation noise based on flight path, characterized in that: The method comprises the following steps: Query the track data within the last hour according to the current time, where the track data contains multiple tracks; Calculate the PCA value of any track at the ground monitoring site according to the track data; The time range is determined by using PCA point time, sound propagation time and error time, and aviation noise events are identified within this time range; For the identified aviation noise event, an association relationship between the aviation noise event and the aforementioned flight track is established, thereby outputting an aviation noise event set under the flight track.

2. The method for identifying aviation noise based on flight path according to claim 1, characterized in that: Querying the track data within the last hour according to the current time specifically includes: obtaining the current system time, subtracting the time difference of one hour from the current time to determine the starting time point of the query, and exporting the track data from the third-party track software based on the starting time point of the query.

3. The method for identifying aviation noise based on flight path according to claim 1, characterized in that: The PCA value of any track at the ground monitoring station is calculated according to the track data, wherein the PCA value includes: the elevation angle, the height when the aircraft flies over the aforementioned closest point, the time point when the aircraft is closest to the ground monitoring station, and the slant distance, and is calculated separately by the following methods: Acquire radar data of the aircraft within a specific time period, wherein the radar data includes latitude, longitude and altitude information of the aircraft; The slant distance between the aircraft and the ground monitoring station is calculated based on the aircraft's latitude and longitude information and the ground monitoring station's latitude and longitude information; Finding the time when the aircraft is closest to the ground monitoring station and the altitude when it flies over the closest point based on the radar data; Based on the slant range and the aircraft's altitude when it passed the aforementioned closest point, the elevation angle is calculated.

4. The method for identifying aviation noise based on flight path according to claim 3, characterized in that: The time range is determined by the PCA point time, sound propagation time and error time, including: Setting the error time and obtaining the sound propagation time from the aircraft to the ground monitoring site based on the slant range and the speed of sound; The time range of the noise event is determined by adding the PCA point time to the sound propagation time and the error time, where the PCA point time refers to the time point when the aircraft is closest to the ground monitoring station.

5. The method for identifying aviation noise based on flight path according to claim 4, characterized in that: Aviation noise events are identified within the time range, specifically including: within the aforementioned time range, all sound events are acquired through noise monitoring equipment, and the Leq value, spectrum, and LAS value of the sound events are calculated respectively; if the Leq value, spectrum, and LAS value of the sound event all meet the requirements, the sound event is determined to be an aviation noise event.

6. The method for identifying aviation noise based on flight path according to claim 5, characterized in that: Determine whether the Leq value, spectrum, and LAS value of the sound event meet the requirements, including: For the Leq value and the LAS value, if both the Leq value and the LAS value exceed the corresponding threshold value, the Leq value and the LAS value of the sound event meet the requirements; For the spectrum value, compare the spectrum in the sound event with the spectrum in a typical aviation noise event to determine whether the similarity of the spectrum meets the requirements.

7. The method for identifying aviation noise based on flight path according to claim 6, characterized in that: Determine whether the similarity of the spectrum meets the requirements, including: The shape similarity between the spectrum in the sound event and the spectrum in a typical aviation noise event is determined by a similarity comparison method; Compare the energy distribution similarity of the spectrum in the sound event with that in typical aviation noise events through spectral density or energy distribution diagram; If the shape similarity and energy distribution similarity of the spectrum meet the requirements, it means that the spectrum in the sound event is similar to the spectrum in a typical aviation noise event.

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