DEVICE AND METHOD FOR AN AIRCRAFT BIRD CONGESTION INDICATOR SYSTEM

Abstract

A real-time aircraft bird congestion indicator system for measuring congestion in an airspace between aircraft and birds uses one or more radars to continuously survey an airspace around an airport or aerodrome and continuously generate aircraft tracks and bird tracks in the airspace. A congestion processor connected to the radar(s) receives the aircraft and bird tracks and processes them to periodically generate a congestion indicator that measures the congestion in the airspace. A display processor connected to the congestion processor receives the congestion indicator which is updated periodically by the congestion processor and displays the congestion indicator to a user, generates an alert if the congestion indicator falls outside set operating limits, and/or sends the congestion indicator or alert to another system.

Claims

1. (canceled)

2. The system of claim 23 wherein said one or more radars include at least one avian radar and one air traffic control radar.

3. The system of claim 23 wherein at least one of said one or more radars is an Automatic Dependent Surveillance Broadcast (ADS-B) system which generates said aircraft tracks.

4. The system of claim 23 wherein at least one of said radars is a 3D avian radar.

5. The system of claim 4 where said 3D avian radar is configured to generate two channels of track data, one of said channels configured to generate said bird tracks and the second channel configured to generate said aircraft tracks.

6. The system of claim 23 where said aircraft tracks and said bird tracks are located in the said airspace in 3D, with each of said tracks specified respectively with coordinates {x, y, z, t} where x, y and z define a Cartesian coordinate system and t represents the current time.

7. The system of claim 23 wherein said risk matrix is generated at least once every few minutes and calculated based on the most recently received aircraft tracks and bird tracks which span respectively a duration in the tens of minutes, with respective updates to said aircraft tracks and bird tracks received from said radars at least once every few seconds.

8. (canceled)

9. A method for providing bird-aircraft strike risk information to airport stakeholders including pilots, comprising: operating one or more radars to continuously survey a predetermined airspace throughout an entirety thereof and continuously generate bird tracks and aircraft tracks of birds and any number of aircraft in said predetermined airspace; operating a congestion processor to receive said aircraft tracks and said bird tracks from said one or more radars and process them to periodically generate a risk matrix that indicates or indexes bird-aircraft strike risk separately in each of a multiplicity of cells or subspaces in said predetermined airspace; and communicating bird-aircraft strike risk in one or more of said cells or subspaces, pursuant to said risk matrix, to one or more users in said predetermined airspace.

10. The method in claim 9 wherein the operating of said one or more radars includes operating at least one avian radar and at least one air traffic control radar

11. The method of claim 9 wherein at least one of said one or more radars is an Automatic Dependent Surveillance—Broadcast (ADS-B) system which generates said aircraft tracks.

12. The method of claim 9 wherein at least one of said one or more radars is a 3D avian radar

13. The method of claim 12 where the operating of said one or more radars includes operating said 3D avian radar to generate two channels of track data, one of said two channels including said bird tracks and only said bird tracks, the other of the said two channels including said aircraft tracks and only said aircraft tracks.

14. The method of claim 9 where said aircraft tracks and said bird tracks are located in the said airspace in 3D, with each of said tracks specified respectively with coordinates {x, y, z, t} where x, y and z define a Cartesian coordinate system and t represents the current time.

15. The method of claim 9 wherein the operating of said congestion processor includes operating said congestion processor to calculate an updated value for said risk matrix at least once every few minutes based on most recently received aircraft tracks and bird tracks.

16. The method of claim 15 wherein the most recently received aircraft tracks and bird tracks for use by said congestion processor in calculating said updated value span respectively a duration in the tens of minutes, with respective updates to said aircraft tracks and bird tracks received from said one or more radars at least once every few seconds.

17. (canceled)

18. The method of claim 15, further comprising operating said congestion processor to periodically calculate a congestion indicator that measures congestion in said predetermined airspace taken as a whole, wherein the congestion indicator calculation includes summing, over the predetermined airspace, the cell-wise bird-aircraft strike risk.

19. The method of claim 9 wherein the operating of said congestion processor to periodically generate said risk matrix includes computing, for each given cell or subspace of the predetermined airspace, a sum of products of (i) the aircraft density of that given cell or subspace, (ii) the bird density of each of the other cells or subspaces, and (iii) a proximity function that is inversely proportional to the separation or distance between the given cell and the respective other cells in the predetermined airspace.

20. The method of claim 9 wherein the operating of said congestion processor to periodically generate said risk matrix includes computing, for each given cell or subspace of the entire aerodrome space, a sum of products of (i) the bird density of the given cell or subspace, (ii) the aircraft density of each of the other cells or subspaces, and (iii) a proximity function that is inversely proportional to the separation or distance between the given cell and the respective other cells in the predetermined airspace.

21. The method of claim 9 wherein the communicating of bird-aircraft strike risk in one or more of said cells or subspaces, pursuant to said risk matrix, to one or more users in said predetermined airspace is undertaken in real-time.

22. The method of claim 9, further comprising periodically organizing and storing said risk matrix, the communicating of bird-aircraft strike risk in one or more of said cells or subspaces, pursuant to said risk matrix, to one or more users in said predetermined airspace being undertaken as historical data mining or access at a time subsequent to the organizing and storing.

23. A real-time aircraft bird congestion indicator system for providing bird-aircraft strike risk information to airport stakeholders including pilots, comprising: one or more radars configured to continuously survey a predetermined airspace throughout an entirety thereof and continuously generate bird tracks and aircraft tracks of birds and any number of aircraft in said airspace; and a congestion processor operatively connected to said one or more radars, said congestion processor being configured to receive said aircraft tracks and said bird tracks and process them together to periodically determine for each cell of a preselected multiplicity of cells or subspaces of said predetermined airspace a respective aircraft density and a respective bird density, collectively constituting an aircraft density function and a bird density function respectively over or across said predetermined airspace, and to generate a risk matrix that identifies aircraft bird strike risk in each of said cells or subspaces of said predetermined airspace separately, wherein said congestion processor includes a risk correlator configured to calculate said risk matrix by multiplying densities of all possible cell-pairs of the aircraft density function and the bird density function and multiplying these products by a proximity function that is inversely proportional to the respective cell-to-cell separation in the airspace.

24. The system of claim 23 wherein said congestion processor includes a summer operatively connected to said risk correlator to periodically calculate a congestion indicator that measures congestion in said predetermined airspace taken as a whole, wherein the summer is configured to add, over the predetermined airspace, the cell-wise bird-aircraft strike risk.

25. A method for measuring congestion between aircraft and birds in a predetermined airspace in real-time to provide bird-aircraft strike risk information to airport stakeholders including pilots, comprising: operating one or more radars to continuously survey said predetermined airspace throughout an entirety thereof and continuously generate bird tracks of birds in said predetermined airspace and aircraft tracks of any number of aircraft in said predetermined airspace; operating a congestion processor to receive said aircraft tracks and said bird tracks from said one or more radars and to process them to periodically generate a risk matrix that measures bird-aircraft strike risk separately in each of a multiplicity of cells of said predetermined airspace; and periodically storing the risk matrix to build a historical database accessible for understanding bird-aircraft strike probabilities in said predetermined airspace in accordance with time.

26. The method of claim 25, further comprising operating the congestion processor to periodically sum the bird-aircraft strike risk over all the cells of said predetermined airspace to generate a congestion indicator for the entirety of said predetermined airspace, also comprising storing periodically storing the congestion indicator in the historical database.

27. The method of claim 25 wherein the operating of said congestion processor to generate said risk matrix includes calculating for each of said cells a product of an aircraft density function and a bird density function, selectively using said aircraft tracks and said bird tracks, and further multiplied by a proximity function that is inversely proportional to cell-wise separation in the airspace.

28. The method of claim 25 wherein the operating of said congestion processor to periodically generate said risk matrix includes computing, for each given cell or subspace of the predetermined airspace, a sum of products of (i) the aircraft density of that given cell or subspace, (ii) the bird density of each of the other cells or subspaces, and (iii) a proximity function that is inversely proportional to the separation or distance between the given cell and the respective other cells in the predetermined airspace.

29. The method of claim 25 wherein the operating of said congestion processor to periodically generate said risk matrix includes computing, for each given cell or subspace of the entire aerodrome space, a sum of products of (i) the bird density of the given cell or subspace, (ii) the aircraft density of each of the other cells or subspaces, and (iii) a proximity function that is inversely proportional to the separation or distance between the given cell and the respective other cells in the predetermined airspace.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0042] FIG. 1 is a block diagram of the aircraft bird congestion indicator system in accordance with this invention.

[0043] FIG. 2 is a block diagram of a preferred embodiment of the congestion processor in accordance with this invention.

DETAILED DESCRIPTION

[0044] An aircraft bird congestion indicator system 1 in accordance with the present invention is illustrated in FIG. 1. One or more radars 11 generate bird tracks 14 and aircraft tracks 15 that feed congestion processor 12 with real-time tracks of birds and aircraft in the airspace. Congestion processor 12 generates a congestion indicator 16 periodically, typically in accordance with a set update rate (e.g. once a minute). The congestion indicator 16 is operated on by display processor 13 which interfaces to users or third-party systems 19. Display processor 13 provides users with an indicator display 18 that presents the congestion indicator 16 in an easy to understand format, and/or alerts 17 which occur when the congestion indicator crosses pre-set thresholds.

[0045] Those skilled in the art will appreciate that the one or more radars 11 could be any type of radar capable of generating aircraft tracks 15 and bird tracks 14 in the airspace. For example, one avian radar and one air traffic control radar could be used. The aircraft tracks 15 could also be generated from an Automatic Dependent Surveillance Broadcast (ADS-B) system. A 3D avian radar, exemplarily that disclosed in U.S. Pat. No. 9,291,707, is preferably used to generate high quality bird tracks. A state-of-the-art 3D avian radar that is configured to generate two channels of track data, one channel configured for bird tracks and the other channel configured for aircraft tracks is also preferred, in order to reduce cost and match both resolution and track update rates throughout the airspace. The update rate associated with the aircraft tracks and bird tracks is preferably on the order of seconds.

[0046] For the case of 3D radars, aircraft tracks 15 and bird tracks 14 can be geolocated in the airspace using any convenient three-dimensional coordinate system. For example, the tracks can be specified respectively with coordinates {x, y, z, t} where x, y and z define a Cartesian coordinate system and t represents time.

[0047] For a given update for congestion indicator 16, the congestion processor 12 preferably processes a contiguous block of the most recent aircraft tracks 15 and bird tracks 14 received immediately prior in time to the current update time. This block of track data preferably spans an interval of time on the order of tens of minutes. The aircraft block and bird block need not be the same duration and are specified to generate sufficient data to support the aircraft density and bird density calculations illustrated in FIG. 2.

[0048] Congestion processor 12 is further illustrated in FIG. 2 where a preferred embodiment is shown. For each congestion indicator 16 update, bird tracks 14 are used by bird density calculator 21 and aircraft tracks 15 are used by aircraft density calculator 22 to calculate respective bird density function 25 and aircraft density function 26. In accordance with the invention, we divide the airspace into subspaces or cells in three spatial dimensions, and calculators 21 and 22 calculate the respective densities on a cell by cell basis.

[0049] In a first embodiment, the respective cell-wise density function (25 or 26) for a given update time is determined by counting the number of respective tracks contained within the respective block of track data that intersects or passes through the respective cell. A risk correlator 23 generates risk matrix 27 by multiplying the densities of all possible cell-pairs of the computed aircraft density and bird density functions and then further multiplying these products by a proximity function that is inversely proportional to the respective cell-to-cell separation in the airspace. Risk matrix 27 represents the cell-wise risk in the airspace. When summed by summer 24, risk matrix 27 reduces to a single congestion indicator 16, which is a single number representing the current risk of a bird strike across the entire airspace.

[0050] In other words, risk correlator 23 generates risk matrix 27 by computing, for each given cell or subspace of the entire aerodrome space, a sum of products of (i) the aircraft density of that given cell, (ii) the bird density of each of the other cells or subspaces, and (iii) a proximity function that is inversely proportional to the separation or distance between the given cell and the respective other cell in the airspace or aerodrome space. This sum represents, for the given cell, a respective cellular congestion index. Summer 24 adds together all of the cellular congestion indices over the entire airspace to derive the singular congestion indicator 16 representing the current risk of a bird strike across the entire airspace.

[0051] Equivalently, risk correlator 23 generates risk matrix 27 by computing, for each given cell or subspace of the entire aerodrome space, a sum of products of (i) the bird density of that given cell, (ii) the aircraft density of each of the other cells or subspaces, and (iii) a proximity function that is inversely proportional to the separation or distance between the given cell and the respective other cell in the airspace or aerodrome space. This sum represents, for the given cell, a respective alternative cellular congestion index. Summer 24 adds together all of the alternative cellular congestion indices over the entire airspace to derive the same singular congestion indicator 16 representing the current risk of a bird strike across the entire airspace.

[0052] Should the congestion indicator 16 exceed a predetermined threshold or magnitude of acceptable risk, steps may be taken to compare the cellular congestion indices to determine whether a particular region of the entire airspace is subject to an unacceptable degree of bird strike risk. Steps may then be taken in the routing of air traffic to avert avian collisions.

[0053] The proximity function can take a number of forms familiar to those skilled in the art. A simple embodiment has the proximity function monotonically decreasing with the 3D separation between the respective cells. A preferred embodiment has the proximity function equal to the product of two factors: i) a factor monotonically decreasing with the height separation between the respective cells, and ii) a factor monotonically decreasing with the lateral separation between the respective cells.

[0054] An important feature of the present invention is the ability to rapidly determine where in the airspace the congestion lies that is responsible for congestion indicator 16 exceeding a risk threshold. Risk matrix 27 contains the cell-wise risk components. As a result, visualization tools such as heat maps or automated algorithms that extract regions in the airspace with continuous high-risk components can rapidly alert users to problem areas in the airspace so that action can be taken to mitigate risk. This feature can also drive automated messaging and advisories such as ATIS messages that not only indicate the aerodrome congestion indicator but also the nature of the congestion. For example, if risk matrix 27 is approximately uniform, the message might read “aircraft bird congestion high throughout the critical airspace”. Alternatively, if concentrations of risk occur in the departure corridor of runway 24L and 24R due to migrating birds between 500-1500 feet AGL, the message might read “aircraft bird congestion high in runway 24 departure corridor 500′ to 1500′ AGL”.

[0055] Another feature in accordance with the present invention is a congestion advisory system that organizes (for example by year, month, day, hour) and stores congestion indicator 16 and risk matrix 27 in a suitably designed database management system with a user-friendly front-end that makes it easy for users to understand historical aircraft bird congestion at an airport. Airport operators, SMS managers, wildlife control personnel, airlines and flight dispatchers, and regulators could make excellent use of such a tool.

[0056] A feature of congestion processor 12 is the ability to incorporate additional preference factors into aircraft density calculator 22 and bird density calculator 21. For example, specific bird density cells (subspaces) can be emphasized (biased upwards) or de-emphasized (biased downwards) based on prior knowledge of bird strikes, seasons, construction, radar coverage in those areas, et cetera. Similar adjustments can be made for aircraft densities (e.g. for volumes with greater risk, such as departure corridors). Risk correlator 23 can also include cell by cell modifications to emphasize certain volumes (subspaces) over others. The volumes to be emphasized could be those deemed to have greater a-priori risk, e.g. departure corridors.

[0057] In more complex embodiments, rather than simply counting intersecting tracks, the density function in a cell can be computed as the sum of the products of various risk factors for each intersecting track. The risk factors can include (radar-estimated) mass, speed and direction. Those skilled in the art can create any number of such density computations, using any available track measurements provided by the radars.

[0058] Mother feature of the present invention is the fact that the resulting congestion indicator 16 can be customized and applied uniquely to the risk posture of each aerodrome, flight crew and airline. Customized congestion indicator 16 thresholds (which require action if crossed) can be set by each stakeholder in accordance with the aircraft they are flying, the aerodrome they are visiting, or the risk posture they are comfortable assuming. This, and other features described herein make the congestion indicator 16 a key performance indicator (KPI) for aviation safety.

[0059] Analogous adjustments to aircraft density calculator 22, bird density calculator 21 and risk correlator 23 can be incorporated for other reasons such as making the calculated congestion indicator 16 more robust to varying environmental conditions (e.g. when birds are not flying during a particular update interval) and operating conditions (e.g. when there is a temporary lull in aircraft operations). Those skilled in the art will appreciate that to be useful, the congestion indicator 16 cannot change value wildly. These biasing adjustments will allow congestion indicator 16 to be optimized so that it can be used in an airport's safety management system and it can be actionable. These biasing adjustments can include baseline defaults, minima, maxima, ordered statistics and other linear and nonlinear filtering methods known to those skilled in the art.

[0060] Particular features of our invention have been described herein. However, simple variations and extensions known to those skilled in the art are certainly within the scope and spirit of the present invention. This includes variations on integration of the functional blocks described herein. For instance, FIG. 1 shows congestion processor 12 and display processor 13 as two separate processing components. It is obvious that these two components can be combined into a single component, or into more than two components, with complete flexibility on where the boundaries lie.

[0061] User interfaces 17 and 18 and system interface 19 can be implemented using all standard methods known to those skilled in the art. For example, Display processor 13 could use a Web server to provide indicator display 18 via a web browser accessible from any desktop or mobile device, alerts 17 could be text messages or e-mails, and interface 19 could be a database to database transfer.