System and method for sensor tasking

• US 8,972,306 B2
• Filed: 08/31/2007
• Issued: 03/03/2015
• Est. Priority Date: 08/31/2007
• Status: Active Grant

• Current Assignee: Raytheon Company (Rtx Corporation)
• Original Assignee: Raytheon Company (Rtx Corporation)
• Inventors: Nguyen, Duong, Hampton, Michael T., Janoso, Anthony M.
• Primary Examiner(s): Gaffin, Jeffrey A
• Assistant Examiner(s): Bharadwaj, Kalpana
• Application Number:
  US11/848,990
• Publication Number:
  US 20090062936A1
• Time in Patent Office: 2,741 Days
• Field of Search: 726/19, 700/245
• US Class Current: 706/8
• CPC Class Codes: G01S 13/726 Multiple target tracking
• CPC Class Codes: G01S 13/867 Combination of radar systems with cameras
• CPC Class Codes: G06N 3/043 based on fuzzy logic, fuzzy membership or fuzzy inference, e.g. adaptive neuro-fuzzy inference systems [ANFIS]
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling

Abstract

A system for sensor tasking includes a plurality of sensors operable to perform one or more tasks and a processor. The processor may receive a mission, wherein the mission comprises one or more tasks to be performed by one or more of the plurality of sensors. The processor may also receive one or more environmental conditions associated with the mission and generate a fuzzy cognitive map. The fuzzy cognitive map includes a plurality of nodes and weighted links, wherein one or more of the plurality of nodes are associated with one or more of the environmental conditions. The processor may be further operable to select one or more of the plurality of sensors to perform each of the one or more tasks based at least on a state of the fuzzy cognitive map and schedule each of the one or more tasks to be performed by the respective selected one or more sensors.

Claims

1. A system for sensor tasking comprising:

a plurality of sensors operable to perform one or more tasks;

a processor operable to;

receive a mission, wherein the mission comprises one or more tasks to be performed by one or more of the plurality of sensors;

receive one or more environmental conditions associated with the mission;

generate a fuzzy cognitive map, wherein the fuzzy cognitive map comprises a plurality of nodes and weighted links between the nodes, the weighted links indicating causal relationships between the nodes, wherein a first weighted link of the weighted links that indicates a positive causal relationship between a first node and a second node of the first weighted link that indicates that if a value associated with one node of the first and second nodes increases then a value associated with the other node of the first and second nodes also increases, and wherein a second weighted link of the weighted links that indicates a negative causal relationship between a third node and a fourth node of the second weighted link indicates that if a value associated with one node of the third and fourth nodes increases then a value associated with the other node of the third and fourth nodes decreases, wherein the first node of the nodes includes an input node that includes a static value and the third node of the nodes includes a concept node that includes a dynamic value until the fuzzy cognitive map stabilizes, and wherein one or more of the plurality of nodes are associated with one or more of the environmental conditions;

select one or more of the plurality of sensors to perform each of the one or more tasks, the selection based at least on a state of the fuzzy cognitive map; and

schedule each of the one or more tasks to be performed by the respective selected one or more sensors.

2. The system of claim 1, wherein the processor is further operable to perform an environmental effects assessment based at least on the state of the fuzzy cognitive map, the environmental effects assessment indicating a causal relationship between the one or more environmental conditions and one or more of the plurality of sensors.

3. The system of claim 2, wherein a processor operable to select one or more of the plurality of sensors to perform each of the one or more tasks comprises a processor operable to select one or more of the plurality of sensors to perform each of the one or more tasks based at least on the environmental effects assessment.

4. The system of claim 1, wherein the environmental conditions comprise weather data.

5. The system of claim 1, wherein the processor is further operable to determine the one or more tasks to be performed by the sensors, the determination based at least on the mission.

6. The system of claim 1, wherein a processor operable to schedule, comprises a processor operable to:

determine the value of a task; and

rank the task based at least on the value of the task.

7. The system of claim 6, wherein the value of the task is determined based on Real Options Theory and a market-based auction, the market-based auction comprising a plurality of bids, wherein each of the plurality of bids is at least a function of:

a predicted effectiveness of a particular sensor of the plurality of sensors for performing a particular task of the one or more tasks, wherein the predicted effectiveness includes a rank of the particular sensor relative to a rank of other sensors of the plurality of sensors, wherein a sensor of the plurality sensors is ranked higher than another sensor if it is predicted to be more effective at performing the task;

the availability of the particular sensor to perform the particular task; and

a priority of the particular task, the priority of the particular task based at least on the importance of the particular task to the success of the mission.

8. The system of claim 7, wherein the predicted effectiveness of the particular sensor is based at least on the state of the fuzzy cognitive map.

9. A computerized method for sensor tasking comprising:

receiving a task at a computer, the task associated with a mission;

generating, by the computer, a fuzzy cognitive map, the fuzzy cognitive map comprising a plurality of nodes and weighted links between the nodes, the weighted links indicating causal relationships between the nodes, wherein a first weighted link of the weighted links that indicates a positive causal relationship between a first node and a second node of the first weighted link that indicates that if a value associated with one node of the first and second nodes increases then a value associated with the other node of the first and second nodes also increases, and wherein a second weighted link of the weighted links that indicates a negative causal relationship between a third node and a fourth node of the second weighted link indicates that if a value associated with one node of the third and fourth nodes increases then a value associated with the other node of the third and fourth nodes decreases, wherein the first node of the nodes includes an input node that includes a static value and the third node of the nodes includes a concept node that includes a dynamic value until the fuzzy cognitive map stabilizes, and;

selecting, by the computer, at least one sensor of a plurality of sensors to perform the task, the selection based at least on a state of the fuzzy cognitive map; and

scheduling, by the computer, the at least one selected sensor to perform the task.

10. The method of claim 9, further comprising:

receiving, at the computer, one or more environmental conditions associated with the task; and

wherein one or more of the plurality of nodes are associated with one or more of the environmental conditions.

11. The method of claim 9, further comprising:

determining, by the computer, a value of the task; and

ranking the task, the ranking based at least on the value of the task.

12. The method of claim 11, wherein determining the value of the task comprises performing a market-based auction, the market-based auction comprising a plurality of bids, wherein each of the plurality of bids is at least a function of:

a predicted effectiveness of a particular sensor of the plurality of sensors for performing the task;

the availability of the particular sensor to perform the particular task; and

a priority of the task, the priority of the task based at least on the importance of the task to the success of the mission.

13. The method of claim 12, wherein the predicted effectiveness of the particular sensor is based at least on the state of the fuzzy cognitive map.

14. Logic embodied in a non-transitory computer readable medium, the computer readable medium comprising code operable when executed on a processor, to:

receive a mission, wherein the mission comprises one or more tasks to be performed by one or more of a plurality of sensors;

receive one or more environmental conditions associated with the mission;

generate a fuzzy cognitive map, wherein the fuzzy cognitive map comprises a plurality of nodes and weighted links between the nodes, the weighted links indicating causal relationships between the nodes, wherein a first weighted link of the weighted links that indicates a positive causal relationship between a first node and a second node of the first weighted link that indicates that if a value associated with one node of the first and second nodes increases then a value associated with the other node of the first and second nodes also increases, and wherein a second weighted link of the weighted links that indicates a negative causal relationship between a third node and a fourth node of the second weighted link indicates that if a value associated with one node of the third and fourth nodes increases then a value associated with the other node of the third and fourth nodes decreases, wherein the first node of the nodes includes an input node that includes a static value and the third node of the nodes includes a concept node that includes a dynamic value until the fuzzy cognitive map stabilizes, and wherein one or more of the plurality of nodes are associated with one or more of the environmental conditions;

select one or more of the plurality of sensors to perform each of the one or more tasks, the selection based at least on a state of the fuzzy cognitive map; and

schedule each of the one or more tasks to be performed by the respective selected one or more sensors.

15. The logic of claim 14, wherein the code is further operable to perform an environmental effects assessment based at least on the state of the fuzzy cognitive map, the environmental effects assessment comprises determining a causal relationship between the one or more environmental conditions and one or more of the plurality of sensors.

16. The logic of claim 15, wherein code operable to select one or more of the plurality of sensors to perform each of the one or more tasks comprises code operable to select one or more of the plurality of sensors to perform each of the one or more tasks based at least on the environmental effects assessment.

17. The logic of claim 14, wherein the environmental conditions comprise information associated with a target, wherein the target is associated with the mission.

18. The logic of claim 14, wherein the code is further operable to determine the one or more tasks to be performed by one or more of the plurality of sensors, the determination based at least on the mission.

19. The logic of claim 14, wherein code operable to schedule each of the one or more tasks, comprises code operable to:

determine the value of a task; and

rank the task based at least on the value of the task.

20. The logic of claim 19, wherein the value of the task is determined based on Real Options Theory and a market-based auction, the market-based auction comprising a plurality of bids, wherein each of the plurality of bids is at least a function of:

a predicted effectiveness of a particular sensor of the plurality of sensors for performing a particular task of the one or more tasks;

the availability of the particular sensor to perform the particular task; and

a priority of the particular task, the priority of the particular task based at least on the importance of the particular task to the success of the mission.

21. The logic of claim 20, wherein the predicted effectiveness of the particular sensor is based at least on the state of the fuzzy cognitive map.