Behavior based friend foe neutral determination method

• US 9,322,907 B1
• Filed: 08/07/2012
• Issued: 04/26/2016
• Est. Priority Date: 08/07/2012
• Status: Active Grant

• Current Assignee: Rockwell Collins, Inc. (Raytheon Technologies Corporation d/b/a RTX), The Institute For Human And Machine Cognition
• Original Assignee: Rockwell Collins, Inc. (Raytheon Technologies Corporation d/b/a RTX)
• Inventors: Kadambe, Shubha L., Haan, Benjamin J., Carvalho, Marco Mattos, Monsalve, Carlos Arturo Perez
• Primary Examiner(s): Labaze, Edwyn
• Application Number:
  US13/568,772
• Time in Patent Office: 1,358 Days
• Field of Search: 235/487, 235/375, 235400-417
• US Class Current: 1/1
• CPC Class Codes: G01S 7/021 Auxiliary means for detecting or identifying radar signals or the like, e.g. radar jamming signals
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: H04B 17/373 Predicting channel quality or other radio frequency [RF] parameters
• CPC Class Codes: H04L 27/0012 arrangements for identifying the type of modulation

Abstract

A method for behavior based Friend/Foe/Neutral determination is disclosed. The method receives RF communications from a plurality of perceived entities and records a plurality of first level characteristics of the RF communications. The method determines, from an analysis of the first level characteristics a plurality of second level characteristics of the RF communications. From these second level characteristics, the method determines transmission patterns of the entities over time which lead to an ultimate classification of the perceived entity as a Friend/Foe/Neutral based on the patterns.

Claims

1. A method for determining an identification of a perceived entity, the method comprising:

receiving a first radio frequency (RF) communication from said perceived entity;

identifying a first instance of at least one first level characteristic associated with said first RF communication;

monitoring said perceived entity for additional RF communications;

receiving additional RF communications from said perceived entity;

identifying a second instance of at least one first level characteristic associated with said additional RF communications;

storing said at least one first level characteristic associated with said first RF communication and said at least one first level characteristic associated with said additional RF communications;

identifying and storing at least one second level characteristic associated with said first RF communication and said additional RF communications, said at least one second level characteristic derived from an analysis of said first instance of at least one first level characteristic and said second instance at least one first level characteristic;

analyzing each of said at least one second level characteristics to determine a signal pattern;

determining an identification of said perceived entity based on said signal pattern, said identification of said perceived entity either of;

a friend or a foe or a neutral; and

displaying said identification to a user on a display.

2. The method of claim 1, wherein said at least one first level characteristic comprises at least one of:

a Time of reception, a Node ID, a Position, a vectorial Velocity, a Voice ID, a Waveform, a Frequency, a Bandwidth, and a Transmission Power Range.

3. The method of claim 1, wherein said at least one second level characteristic comprises at least one of:

a Command Chain, a Frequency Hopping Pattern, a Mobility Change Pattern, a Traffic/Mobility Correlation, a Transmission Power Utilization Pattern, a Voice-ID Change Pattern, and a Waveform Change Pattern.

4. The method of claim 1, wherein said determining an identification of said perceived entity based on said signal pattern further comprises an analysis based on a Markov Chain alternative clustering analysis.

5. The method of claim 1, wherein said receiving a first RF communication from said perceived entity further comprises reception via at least one of:

a subsurface receiver, a surface based receiver, an airborne receiver, and a space based receiver.

6. The method of claim 1, wherein said displaying said identification to a user on a display further comprises configuring said identification for further transmission.

7. The method of claim 1, wherein said analysis of said first instance of at least one first level characteristic and said second instance of at least one first level characteristic changes based on a changed additional RF communications transmitted from said perceived entity.

8. A system for identifying a perceived entity, the system comprising:

a receiver configured for receiving a first RF communication and additional RF communications, said receiver further configured for receiving at least one first level characteristic from each of said RF communications;

a Cognitive Network Electronic Warfare (CNEW) controller configured for directing inner system network communication, directing organization, and for directing mission management;

a processor configured for analysis of said at least one first level characteristic from each of said RF communications, said processor further configured for determining at least one second level characteristic of said RF communications based on the analysis;

a user interface in data communication with said CNEW controller, said user interface configured to display information to, and receive information from, a user;

a data storage in data communication with said receiver, said controller, and said processor;

wherein said processor is configured to further analyze said at least one first level characteristic from each of said RF communications and said at least one second level characteristic of said RF communications to determine a signal pattern and deliver to said user an identification and classification of said perceived entity based on said further analysis and said signal pattern, said identification of said perceived entity either of;

a friend or a foe or a neutral.

9. The system of claim 8, wherein said at least one first level characteristic comprises at least one of:

a Time of reception, a Node ID, a Position, a vectorial Velocity, a Voice ID, a Waveform, a Frequency, a Bandwidth, and a Transmission Power Range.

10. The method of claim 8, wherein said at least one second level characteristic comprises at least one of:

a Command Chain, a Frequency Hopping Pattern, a Mobility Change Pattern, a Traffic/Mobility Correlation, a Transmission Power Utilization Pattern, a Voice-ID Change Pattern, and a Waveform Change Pattern.

11. The method of claim 8, wherein said receiver configured for receiving RF communications further comprises reception via at least one of:

a subsurface receiver, a surface based receiver, an airborne receiver, and a space based receiver.

12. The method of claim 8, wherein said analysis of said at least one first level characteristic from each of said RF communications and said at least one second level characteristic of said RF communications changes based on a changed additional RF communications transmitted from said perceived entity.

13. The method of claim 8, wherein said analysis of said at least one first level characteristic from each of said RF communications and said at least one second level characteristic of said RF communications further comprises an analysis based on a Markov Chain alternative clustering analysis.

14. The method of claim 8, wherein said processor is further configured to change the analysis of said at least one first level characteristic based on a changed first RF communication transmitted from said perceived entity, wherein said processor is further configured to continuously monitor said RF communications, and wherein said processor is further configured to determine and deliver to said user a re-identification and a re-classification of said perceived entity based on analysis resulting from said continuous monitoring.

15. A computer readable medium having non-transitory computer readable program code embodied therein which, when executed on a computer device or processor, performs the steps of:

receiving a first radio frequency (RF) communication from said perceived entity;

identifying a first instance of at least one first level characteristic associated with said first RF communication;

monitoring said perceived entity for additional RF communications;

receiving additional RF communications from said perceived entity;

identifying a second instance of at least one first level characteristic associated with said additional RF communications;

storing said at least one first level characteristic associated with said first RF communication and said at least one first level characteristic associated with said additional RF communications;

identifying and storing at least one second level characteristic associated with said first RF communication and said additional RF communications, said at least one second level characteristic derived from an analysis of said first instance of at least one first level characteristic and said second instance of at least one first level characteristic;

analyzing each of said at least one second level characteristics to determine a signal pattern;

determining an identification of said perceived entity based on said signal pattern, said identification of said perceived entity either of;

a friend or a foe or a neutral; and

displaying said identification to a user on a display.

16. The computer readable medium of claim 15, wherein said at least one first level characteristic comprise at least one of:

a Time of reception, a Node ID, a Position, a vectorial Velocity, a Voice ID, a Waveform, a Frequency, a Bandwidth, and a Transmission Power Range.

17. The computer readable medium of claim 15, wherein said at least one second level characteristic comprises at least one of:

a Command Chain, a Frequency Hopping Pattern, a Mobility Change Pattern, a Traffic/Mobility Correlation, a Transmission Power Utilization Pattern, a Voice-ID Change Pattern, and a Waveform Change Pattern.

18. The computer readable medium of claim 15, wherein said determining an identification of said perceived entity based on said signal pattern further comprises an analysis based on a Markov Chain alternative clustering analysis.

19. The computer readable medium of claim 15, wherein said receiving a first RF communication from said perceived entity further comprises reception via at least one of:

a subsurface receiver, a surface based receiver, an airborne receiver, and a space based receiver.

20. The computer readable medium of claim 15, wherein said displaying said identification to a user on a display further comprises configuring said identification for further transmission.