Airspace risk mitigation system

• US 8,368,584 B2
• Filed: 06/10/2010
• Issued: 02/05/2013
• Est. Priority Date: 06/10/2009
• Status: Active Grant

• Current Assignee: University of North Dakota (North Dakota University System)
• Original Assignee: University of North Dakota (North Dakota University System)
• Inventors: Trapnell, Benjamin M., Theisen, Christopher Joseph, Marsh, Ronald Arthur, Young, Timothy Raymond, Reza, Hassan, Askelson, Mark Anthony
• Primary Examiner(s): Brainard, Timothy A
• Application Number:
  US12/813,276
• Publication Number:
  US 20100315281A1
• Time in Patent Office: 971 Days
• Field of Search: 342 29- 32, 342/179
• US Class Current: 342/30
• CPC Class Codes: G01S 13/91 for traffic control G01S13/93 takes precedence
• CPC Class Codes: G01S 13/933 of aircraft or spacecraft
• CPC Class Codes: G01S 13/951 ground based
• CPC Class Codes: G01S 7/003 Transmission of data between radar, sonar or lidar systems and remote stations
• CPC Class Codes: G01S 7/22 Producing cursor lines and indicia by electronic means
• CPC Class Codes: G08G 5/0013 with a ground station
• CPC Class Codes: G08G 5/0026 located on the ground
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

An airspace risk mitigation system includes a plurality of airspace input sources, an airspace data fusion and sensor coordination system, a communications link, and a risk mitigation support system. The airspace input sources includes a radar for generating radar data for an airspace, and an Automatic Dependent Surveillance-Broadcast (ADS-B) receiver for generating additional data for the airspace. The airspace data fusion and sensor coordination system is configured to receive airspace data from the plurality of airspace input sources, correlating airspace data with new or known objects in the airspace, fusing airspace data into a common airspace data set, and generating target and system status information. The risk mitigation support system is configured to calculate a risk associated with aircraft operation in the airspace as a function of the target and system status information.

Claims

1. An airspace risk mitigation system comprising:

a plurality of airspace input sources comprising;

a first radar for generating radar data for an airspace; and

an Automatic Dependent Surveillance-Broadcast (ADS-B) receiver for generating additional data for the airspace;

an airspace data fusion and sensor coordination system configured to receive airspace data from the plurality of airspace input sources, correlating airspace data with new or known objects in the airspace, and fusing airspace data into a common airspace data set, wherein the airspace data fusion and sensor coordination system generates target and system status information;

a communications link for communicating between at least one of the plurality of airspace input sources and the airspace data fusion and sensor coordination system; and

a risk mitigation support system configured to calculate a risk associated with aircraft operation in the airspace as a function of the target and system status information, wherein the risk mitigation support system is further configured to determine an interaction volume of a manned aircraft in the airspace as a function of expected maneuverability parameters of the manned aircraft in the airspace.

2. The system of claim 1 and further comprising:

a display for displaying an output indicative of the risk associated with aircraft operation in the airspace.

3. The system of claim 1, the plurality of airspace input sources further comprising:

a weather station for providing weather information related to the airspace, wherein weather events are treated as objects.

4. The system of claim 1, wherein the risk associated with aircraft operation in the airspace is calculated using a Monte Carlo simulation.

5. The system of claim 4, wherein the risk associated with aircraft operation in the airspace is calculated using a probability formula derived from the Monte Carlo simulation that provides a probability of interaction in the airspace as a function of one or more discrete variables.

6. The system of claim 5, wherein the risk associated with aircraft operation in the airspace is calculated using a data accuracy adjustment, applied as location errors associated with each object in the airspace that increase or decrease the probability of interaction.

7. The system of claim 5, wherein the risk associated with aircraft operation in the airspace is calculated by fitting discrete data determined from the Monte Carlo simulation to a smoothly varying function applied to generate the probability of interaction.

8. The system of claim 5, wherein the risk associated with aircraft operation in the airspace is calculated using interpolation of one or more data tables determined from the Monte Carlo simulation applied to generate the probability of interaction.

9. The system of claim 1, wherein the risk mitigation support system is configured as a subsystem of the airspace data fusion and sensor coordination system.

10. The system of claim 1, wherein the risk mitigation support system represents the interaction volume of the manned aircraft within the common airspace as a three-dimensional cone.

11. The system of claim 1, wherein the expected maneuverability parameters include at least one of limits to pitch and banked turns.

12. A computer-implemented method of calculating a risk associated with aircraft operation within an airspace, the method comprising:

obtaining airspace input data from a plurality of data sources in computer-readable format;

identifying objects in the airspace as a function of the airspace input data;

determining an interaction volume of a manned aircraft objects in the airspace as a function of one or more expected maneuverability parameters of the manned aircraft object in the airspace; and

conducting a Monte Carlo simulation using one or more processors to provide a probability of interaction for each of the identified objects in the airspace, including the manned aircraft objects as a function of the airspace input data.

13. The method of claim 12 and further comprising:

fitting discrete data determined from the Monte Carlo simulation to a smoothly varying function to generate the probability of interaction.

14. The method of claim 12 and further comprising:

interpolating one or more data tables determined from the Monte Carlo simulation to generate the probability of interaction.

15. The method of claim 12 and further comprising:

performing a data accuracy adjustment using location errors associated with each object in the airspace that increase or decrease the probability of interaction.

16. The method of claim 12 and further comprising:

representing the interaction volume of the one or more manned aircraft objects as a three-dimensional cone.