Dynamic wake prediction and visualization with uncertainty analysis

• US 20030222795A1
• Filed: 05/15/2003
• Published: 12/04/2003
• Est. Priority Date: 05/17/2002
• Status: Active Grant

• Current Assignee: United States of America As REP By The Administrator of The National Aeronautics & Space
• Original Assignee: United States of America As REP By The Administrator of The National Aeronautics & Space
• Inventors: Powell, J. David, Holforty, Wendy L.
• Granted Patent: US 6,963,291 B2
• Time in Patent Office: Days
• US Class Current: 340/968
• CPC Class Codes: B64D 43/00 Arrangements or adaptations of instruments arrangements of cameras B64D47/08; aeronautical measuring instruments per se G01C
• CPC Class Codes: G01C 23/005 Flight directors indicating arrangements specially adapted for rotary gyroscopes G01C19/32

Abstract

A dynamic wake avoidance system utilizes aircraft and atmospheric parameters readily available in flight to model and predict airborne wake vortices in real time. A novel combination of algorithms allows for a relatively simple yet robust wake model to be constructed based on information extracted from a broadcast. The system predicts the location and movement of the wake based on the nominal wake model and correspondingly performs an uncertainty analysis on the wake model to determine a wake hazard zone (no fly zone), which comprises a plurality of “wake planes,” each moving independently from another. The system selectively adjusts dimensions of each wake plane to minimize spatial and temporal uncertainty, thereby ensuring that the actual wake is within the wake hazard zone. The predicted wake hazard zone is communicated in real time directly to a user via a realistic visual representation. In an example, the wake hazard zone is visualized on a 3-D flight deck display to enable a pilot to visualize or “see” a neighboring aircraft as well as its wake. The system substantially enhances the pilot'"'"'s situational awareness and allows for a further safe decrease in spacing, which could alleviate airport and airspace congestion.

Claims

1. A method for dynamic wake prediction and visualization comprising the steps of:

obtaining aircraft data and atmospheric data continuously in essentially real time;

extracting parameters from said aircraft data and said atmospheric data;

determining a nominal wake model with said parameters;

analyzing said nominal wake model to determine uncertainty;

predicting a wake hazard zone with minimal uncertainty by adjusting sizes of said wake hazard zone in accordance with said analyzing step; and

visualizing a location of said wake hazard zone.

2. The method according to claim 1, in which

said wake hazard zone comprises a series of two-dimensional wake planes, each of which is subject to its own sink rate and wind vector as measured at a particular point in time and each moves independent to another.

3. The method according to claim 2, in which

said predicting step further comprises the step of increasing a size of one of said two dimensional wake planes in a horizontal direction, a vertical direction, or both.

4. The method according to claim 2, in which

said visualizing step further comprising depositing said wake planes at a predetermined time interval.

5. The method according to claim 2, in which

each of said wake planes increases in size in two directions as it ages.

6. The method according to claim 1, in which

said visualizing step further comprises the step of visualizing width, height, and depth of said wake hazard zone on a display.

7. The method according to claim 1, further comprising:

determining a lifespan of a wake generated by said aircraft; and

discontinuing said visualizing step when said lifespan ends.

8. The method according to claim 1, in which

said uncertainty includes spatial uncertainty and temporal uncertainty.

9. The method according to claim 1, in which

sources of said uncertainty include time, location, weight, load factor, sink rate, wake vortex span, wake lifespan, wind direction, wind speed, air density, lateral draft, horizontal drift, and instrumentation error.

10. The method according to claim 1, in which

said aircraft data and said atmospheric data are embedded in a wireless datalink message.

11. The method according to claim 10, in which

said wireless datalink message is an automatic dependent surveillance broadcast (ADS-B) message or a traffic collision avoidance system (TCAS) mode-S message.

12. The method according to claim 1, in which

said parameters comprising said aircraft'"'"'s position, said aircraft'"'"'s weight, said aircraft'"'"'s wingspan, said aircraft'"'"'s ground velocity vector, said aircraft'"'"'s true airspeed vector, wind vector, and air density.

13. The method according to claim 1, further comprising:

displaying said aircraft and indicating vertical and horizontal distances to said aircraft.

14. The method according to claim 1, further comprising:

indicating wind speed and direction at said aircraft, ownship, or both.

15. A dynamic wake avoidance system comprising:

wireless communication means for receiving aircraft data including identification, configuration, position, and weight, and atmospheric data including wind speed and air density;

processing means for extracting parameters from said aircraft data and said atmospheric data, for modeling a nominal wake vortex with said parameters, for analyzing said nominal wake model to determine uncertainty, and for determining a resulting wake hazard zone with minimal uncertainty; and

display means for visualizing a location of said wake hazard zone.

16. The system according to claim 15, in which

said wake hazard zone is characterized as having width, height, and depth;

and

said uncertainty includes spatial uncertainty and temporal uncertainty.

17. The system according to claim 15, further comprising:

means for determining said position via global positioning satellite system (GPS), local area augmentation system (LAAS), wide area augmentation system (WAAS), traffic collision avoidance system (TCAS), or inertial navigation systems (INS).

18. The system according to claim 15, in which

said wireless communication means include an automatic dependent surveillance broadcast (ADS-B) datalink.

19. The system according to claim 15, in which

said processing means include

means for modeling and predicting location, movement, and lifespan of said wake hazard zone, said movement including vertical drift and horizontal drift.

20. The system according to claim 15, in which

said display means is capable of rendering a three-dimensional (3-D) out-the-window view and includes a range indicator.

21. The system according to claim 15, in which

said display means is capable of providing a synthetic vision of said wake hazard zone.

22. The system according to claim 15, in which

said wireless communication means, said processing means, and said display means are integrated with a computer located onboard an airborne vehicle, a ground vehicle, a marine vehicle, or in an air traffic control (ATC) facility.