Systems and methods for situational feature set selection for target classification
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
G08B-001/08
G08B-021/00
G01V-001/00
G01V-001/28
출원번호
UP-0593835
(2006-11-07)
등록번호
US-7714714
(2010-06-03)
발명자
/ 주소
Voglewede, Paul Edward
Cloutier, Scott J.
Jordan, Michael D.
출원인 / 주소
Harris Corporation
대리인 / 주소
McAndrews, Held & Malloy, Ltd.
인용정보
피인용 횟수 :
1인용 특허 :
16
초록▼
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 classification component. The detection component is adapted to detect an event. The classification component is adapted to clas
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 classification component. The detection component is adapted to detect an event. The classification component is adapted to classify the event 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 system includes determining a situation, detecting an event, and classifying the event based at least in part on a situation.
대표청구항▼
The invention claimed is: 1. A system for improved signal processing within a remote sensor system, the system including: a selection component configured to select a situation from a plurality of selectable situations; a detection component configured to detect an event; and a classification compo
The invention claimed is: 1. A system for improved signal processing within a remote sensor system, the system including: a selection component configured to select a situation from a plurality of selectable situations; a detection component configured to detect an event; and a classification component configured to: select at least one feature set from a plurality of selectable feature sets based at least in part on the selected situation, wherein the at least one feature set indicates at least one measurement type, and classify the detected event based at least in part on the selected feature set, wherein the classification of the detected event provides a decision value indicating whether the classified detected event is related to the selected 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 situation includes at least one of a target type, an environment, and a dynamic environmental condition. 4. The system of claim 1, wherein the situation is selected by a user. 5. The system of claim 1, wherein the situation is selected automatically by the selection component. 6. The system of claim 1, wherein the detection component is configured to generate a signal based at least in part on the detected event. 7. The system of claim 6, further including an analysis component configured to analyze the signal based at least in part on the selected at least one feature set. 8. The system of claim 6, further including an analysis component configured to analyze the signal in a plurality of domains. 9. The system of claim 6, further including a processing component configured to determine an envelope of the signal and an analysis component configured to analyze the envelope of the signal in a plurality of domains. 10. The system of claim 1, wherein the detection component is configured to generate a plurality of signals based at least in part on the detected event. 11. The system of claim 10, wherein the classification component is configured to classify the event based at least in part on the plurality of signals. 12. A method for improved signal processing within a remote sensor system, the system including: using at least one computing device to perform the steps of: selecting a situation from a plurality of selectable situations; detecting an event; selecting at least one feature set from a plurality of selectable feature sets based at least in part on the selected situation, wherein the at least one feature set indicates at least one measurement type; and classifying the event based at least in part on the selected at least one feature set, wherein classification provides a decision value indicating whether the classified event is related to the selected situation. 13. The method of claim 12, further including generating a signal based at least in part on the event and analyzing the signal based at least in part on the selected at least one feature set. 14. The method of claim 12, further including generating a signal based at least in part on the event and analyzing the signal in a plurality of domains. 15. The method of claim 12, further including generating a signal based at least in part on the event, processing the signal to determine an envelope of the signal, and analyzing the envelope of the signal in a plurality of domains. 16. The method of claim 12, further including generating a plurality of signals based at least in part on the event and classifying the event based at least in part on the plurality of signals. 17. A computer readable storage medium including a set of instructions for execution on a computer, the set of instructions including: a situation selection routine configured to select a situation from a plurality of selectable situations; a detection routine configured to detect an event; a feature set selection routine configured to select at least one feature set from a plurality of selectable feature sets based at least in part on the selected situation, wherein the at least one feature set indicates at least one measurement type; and a classification routine configured to classify the event based at least in part on the selected at least one feature set, wherein the classification routine provides a decision value indicating whether the classified event is related to the selected situation. 18. The set of instructions of claim 17, wherein the detection routine is configured to generate a signal. 19. The set of instructions of claim 18, further including an analysis routine configured to analyze the signal based at least in part on the selected at least one feature set. 20. The set of instructions of claim 18, further including an analysis routine configured to analyze the signal in a plurality of domains. 21. The set of instructions of claim 18, further including a processing routine configured to determine an envelope of the signal and an analysis routine configured to analyze the envelope of the signal in a plurality of domains. 22. The set of instructions of claim 18, wherein the detection routine is configured to generate a plurality of signals and wherein the classification routine is configured to classify the event based at least in part on the plurality of signals.
Sonneland, Lars; Gehrmann, Thomas, Method and apparatus for generating a cross plot in attribute space from a plurality of attribute data sets and generating a class data set from the cross plot.
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