Non-cooperative target identification using antenna pattern shape

• US 5,812,083 A
• Filed: 02/11/1997
• Issued: 09/22/1998
• Est. Priority Date: 02/23/1996
• Status: Expired due to Fees

• Current Assignee: Raytheon Company (Rtx Corporation)
• Original Assignee: Raytheon TI Systems, Inc. (Rtx Corporation)
• Inventors: Johnson, Peter W., Backer, Lawrence M.
• Primary Examiner(s): Sotomayor, John B.
• Application Number:
  US08/798,894
• Time in Patent Office: 588 Days
• Field of Search: 342/45, 342/64, 342/90, 342/192, 342/193, 342/196, 342/13, 342/173
• US Class Current: 342/90
• CPC Class Codes: G01S 7/021 Auxiliary means for detecting or identifying radar signals or the like, e.g. radar jamming signals

Abstract

A method of classification of a device by recognizing distorted signals, generally a RF antenna pattern, emanating therefrom wherein a trainable recognition system, preferably a neural network, is provided. Known distorted signals are applied to the trainable recognition system to train the recognition system to recognize individually each of a plurality of different signals having distortion therein. Unknown distorted signals are then provided emanating from a remote device and the unknown distorted signals are then used to classify the remote device by analyzing the received unknown distorted signals in the trained recognition system. The steps of training and classifying each include the step of converting the signals from the time domain to the frequency domain. The steps of training and classifying also can each include the step of down sampling the frequency domain signals to compress the signature content.

Claims

1. A method of passive classification of a device by recognizing signals emanating from said device which comprises the steps of:

(a) providing a trainable recognition system;

(b) providing known signature signals to said trainable recognition system to train said recognition system to recognize individually each of a plurality of different signals having signatures therein, each of said known signature signals representing an RF transmitter antenna scan pattern;

(c) providing unknown signature signals emanating from a remote device; and

(d) classifying said remote device by analyzing the received unknown signals in the trained recognition system.

2. The method of claim 1 wherein said trainable recognition system includes a neural network system.

3. The method of claim 2 wherein said steps of training and classifying each include the step of converting said signals from the time domain to the frequency domain.

4. The method of claim 3 wherein said steps of training and classifying each include the step of down selecting the number of samples and normalizing the data.

5. The method of claim 4 wherein said RF antenna scan pattern represents a received signal intensity versus time profile from said remote device.

6. The method of claim 3 wherein said RF antenna scan pattern represents a received signal intensity versus time profile from said remote device.

7. The method of claim 2 wherein said steps of training and classifying each include the step of down selecting the number of samples and normalizing the data.

8. The method of claim 7 wherein said RF antenna scan pattern represents a received signal intensity versus time profile from said remote device.

9. The method of claim 2 wherein said RF antenna scan pattern represents a received signal intensity versus time profile from said remote device.

10. The method of claim 1 wherein said steps of training and classifying each include the step of converting said signals from the time domain to the frequency domain.

11. The method of claim 10 wherein said steps of training and classifying each include the step of down selecting the number of samples and normalizing the data.

12. The method of claim 11 wherein said RF antenna scan pattern represents a received signal intensity versus time profile from said remote device.

13. The method of claim 10 wherein said RF antenna scan pattern represents a received signal intensity versus time profile from said remote device.

14. The method of claim 1 wherein said steps of training and classifying each include the step of down selecting the number of samples and normalizing the data.

15. The method of claim 14 wherein said RF antenna scan pattern represents a received signal intensity versus time profile from said remote device.

16. The method of claim 1 wherein said RF antenna scan pattern represents a received signal intensity versus time profile from said remote device.

17. An apparatus, comprising:

a recognition system, and means for supplying to said recognition system unknown signature signals emanating from a remote device, said recognition system including means for passively classifying the remote device by analyzing said signature signals emanating therefrom with reference to a plurality of different reference signals, each of said reference signals representing a respective RF transmitter antenna scan pattern.