Systems and methods for dynamic situational signal processing for target detection and classfication

• US 20080106403A1
• Filed: 11/07/2006
• Published: 05/08/2008
• Est. Priority Date: 11/07/2006
• Status: Active Grant

• Current Assignee: Ollnova Technologies Limited (Atlantic IP Services Limited)
• Original Assignee: Harris Corporation (L3Harris Technologies, Inc.)
• Inventors: Voglewede, Paul Edward, Jordan, Michael D., Cloutier, Scott J.
• Granted Patent: US 7,710,265 B2
• Time in Patent Office: Days
• US Class Current: 340/540
• CPC Class Codes: G01D 21/00 Measuring or testing not otherwise provided for
• CPC Class Codes: G01V 1/001 Acoustic presence detection
• CPC Class Codes: G08B 13/1663 using seismic sensing means
• CPC Class Codes: G08B 13/19 using infrared-radiation detection systems G08B13/194 takes precedence
• CPC Class Codes: G08B 25/007 Details of data content structure of message packets; data protocols
• CPC Class Codes: G08B 25/10 using wireless transmission systems G08B25/009 takes precedence

Abstract

Certain embodiments of the present invention provide a system for improved signal processing within a remote sensor system. The system includes a detection component and a processing component. The detection component is adapted to detect an event and generate a signal based at least in part on the event. The processing component adapted to process a signal based at least in part on a situation. Certain embodiments of the present invention provide a method for improved signal processing within a remote sensor system. The method includes determining a situation, detecting an event, generating a signal based at least in part on the event, and processing the signal based at least in part on the situational parameter.

Claims

1. A system for improved signal processing within a remote sensor system, the system including:

a detection component adapted to detect an event and generate a signal based at least in part on the event; and

a processing component adapted to process a signal based at least in part on a situation.

2. The system of claim 1, wherein the detection component includes at least one of a seismic detector, an acoustic detector, a magnetic detector, and a passive infra-red detector.

3. The system of claim 1, wherein the processing component is adapted to determine a processing parameter based at least in part on the situation.

4. The system of claim 3, wherein the processing parameter includes at least one of a filter bandwidth, a detection threshold, a detection pulse length, a detection pulse spacing, a detection time window length, a detection time window pulse number, an association window length, and an association window threshold.

5. The system of claim 1, wherein the situation includes at least one of a target type, an environment, and a dynamic environmental condition.

6. The system of claim 1, wherein the situation is determined by a user.

7. The system of claim 1, wherein the situation is determined automatically by the system.

8. The system of claim 1, further including a classification component adapted to classify the event based at least in part on the situation.

9. The system of claim 8, wherein the classification component is adapted to determine a classification parameter based at least in part on the situation.

10. The system of claim 9, wherein the classification parameter includes at least one of feature selection and feature execution order.

11. The system of claim 8, wherein the classification component is adapted to select a feature set based at least in part on the situation.

12. The system of claim 1, further including an analysis component is adapted to analyze the signal.

17. The method of claim 1, wherein the situation is determined by a user.

18. The method of claim 1, wherein the situation is determined automatically.

13. A method for improved signal processing within a remote sensor system, the method including:

determining a situation;

detecting an event;

generating a signal based at least in part on the event; and

processing the signal based at least in part on the situational parameter.

14. The method of claim 13, wherein the processing step includes determining a processing parameter based at least in part on the situation.

15. The method of claim 14, wherein the processing parameter includes at least one of a filter bandwidth, a detection threshold, a detection pulse length, a detection pulse spacing, a detection time window length, a detection time window pulse number, an association window length, and an association window threshold.

16. The method of claim 13, wherein the situation includes at least one of a target type, an environment, and a dynamic environmental condition.

19. The method of claim 13, further including classifying the event based at least in part on the situation.

20. The method of claim 19, wherein the classifying step includes determining a classification parameter based at least in part on the situation.

21. The method of claim 20, wherein the classification parameter includes at least one of feature selection and feature execution order.

22. The method of claim 19, wherein classifying step includes selecting a feature set based at least in part on the situation.

23. The method of claim 13, further including analyzing the signal.

24. A computer readable storage medium including a set of instructions for execution on a computer, the set of instructions including:

a detection routine configured to detect an event and generate a signal based at least in part on the event; and

a processing routine configured to process the signal based at least in part on a situation.