Underwater navigation by aided light sensor

• US 20070297289A1
• Filed: 06/22/2006
• Published: 12/27/2007
• Est. Priority Date: 06/22/2006
• Status: Active Grant

• Current Assignee: Northrop Grumman Systems Corporation (Northrop Grumman Corporation)
• Original Assignee: Northrop Grumman Corporation
• Inventors: Polvani, Donald
• Granted Patent: US 7,505,364 B2
• Time in Patent Office: Days
• US Class Current: 367/131
• CPC Class Codes: B63B 49/00 Arrangements of nautical instruments or navigational aids nautical measuring instruments G01C; radio navigation, analogous arrangements using other waves G01S
• CPC Class Codes: B63B 79/10 using sensors, e.g. pressure sensors, strain gauges or accelerometers
• CPC Class Codes: B63B 79/40 for controlling the operation of vessels, e.g. monitoring their speed, routing or maintenance schedules
• CPC Class Codes: B63G 2008/004 autonomously operating
• CPC Class Codes: G01C 21/1656 with passive imaging devices, e.g. cameras

Abstract

The present invention provides a navigation system for an unmanned underwater vehicle that includes at least two navigation sensors that provide latitude and longitude measurements of unequal accuracy, a processor and a memory. The memory stores a machine-readable set of instructions executable by the processor to process the latitude and longitude measurements received from the navigation sensors, and to estimate vehicle latitude and longitude with approximately equal accuracy.

Claims

1. A navigation system for an unmanned underwater vehicle, comprising:

at least two navigation sensors that provide latitude and longitude measurements of unequal accuracy;

a processor; and

a memory storing a machine-readable set of instructions executable by the processor to;

process the latitude and longitude measurements received from the navigation sensors, and

estimate vehicle latitude and longitude with approximately equal accuracy.

2. The navigation system according to claim 1, wherein the navigation sensors include:

a first navigation sensor to provide latitude data and longitude data, the longitude data being more accurate than the latitude data; and

a second navigation sensor to provide at least latitude data, the latitude data being as accurate as the first navigation sensor longitude data.

3. The navigation system according to claim 2, wherein the first navigation sensor longitude data is an order of magnitude more accurate than the first navigation sensor latitude data.

4. The navigation system according to claim 2, wherein the second navigation sensor provides longitude data that is less accurate than the second navigation sensor latitude data.

5. The navigation system according to claim 1, wherein the machine-readable set of instructions are further executable by the processor to estimate vehicle latitude and longitude using a least-squares curve fit.

6. The navigation system according to claim 1, wherein the machine-readable set of instructions are further executable by the processor to estimate vehicle latitude and longitude using a Kalman Filter.

7. The navigation system of claim 1, wherein the navigation sensors include an altitude sensor, and wherein the machine-readable set of instructions are further executable by the processor to estimate vehicle latitude and longitude by matching the altitude data to a bathymetric map database.

8. The navigation system of claim 1, wherein the navigation sensors include a GPS receiver to provide latitude and longitude data of similar accuracy, and wherein the machine-readable set of instructions are further executable by the processor to estimate vehicle latitude and longitude based on the GPS data.

9. The navigation system of claim 1, wherein the navigation sensors include a MEMS inertial measurement unit to provide three dimensional position data of similar relative accuracy, and wherein the machine-readable set of instructions are further executable by the processor to estimate vehicle latitude and longitude based on the MEMS inertial measurement unit data.

10. An underwater navigation system, comprising:

a light sensor to provide at least longitude data;

a microelectromechanical gyroscope to provide angular rate data about two orthogonal axes; and

a processor, coupled to a memory, the light sensor and the microelectromechanical gyroscope, adapted to estimate position based on the light sensor data and the microelectromechanical gyroscope angular rate data.

11. The underwater navigation system of claim 10, wherein the position estimate includes a longitude estimate provided by the light sensor and a latitude estimate determined from the microelectromechanical gyroscope angular rate data.

12. The underwater navigation system of claim 10, further comprising three orthogonal microelectromechanical accelerometers, coupled to the processor, to provide acceleration data.

13. The underwater navigation system of claim 10, wherein the processor is adapted to estimate position using a least-squares curve fit technique.

14. The underwater navigation system of claim 10, wherein the processor is adapted to estimate position using a Kalman Filter.

15. The underwater navigation system of claim 10, further comprising:

a bathymetric map database; and

an altitude sonar to provide altitude data,

wherein the processor is further adapted to match the altitude data to the bathymetric data to estimate position.

16. The underwater navigation system of claim 10, further comprising a GPS receiver to provide latitude and longitude data, wherein the processor is further adapted to estimate position based on the light sensor data, the microelectromechanical gyroscope data and the GPS data.

17. The underwater navigation system of claim 10, further comprising a microelectromechanical inertial measurement unit, including three orthogonal angular rate sensors to provide angular rate data, and three orthogonal accelerometers to provide acceleration data, wherein the processor is further adapted to estimate position based on the light sensor data, the microelectromechanical gyroscope data and the microelectromechanical inertial measurement unit data.

18. A navigation method for an underwater vehicle, comprising:

processing light sensor data to estimate longitude;

processing microelectromechanical gyroscope angular rate data to estimate latitude, including;

calculating an earth rotation vector based on the microelectromechanical gyroscope angular rate data,

normalizing the magnitude of the earth rotation vector, and estimating latitude based on the normalized earth rotation vector magnitude; and

determining the position of the vehicle based on the estimated latitude and the estimated longitude.

19. The underwater navigation method of claim 18, wherein the microelectromechanical gyroscope angular rate data includes two orthogonal angular rate vectors and the earth rotation vector is calculated by vectorially combining the two orthogonal angular rate vectors.

20. The underwater navigation method of claim 18, wherein the earth rotation vector magnitude is normalized by a maximum earth rotation vector magnitude determined apriori.

21. The underwater navigation method of claim 18, wherein the latitude is estimated by applying an inverse cosine function to the normalized earth rotation vector magnitude.

22. The underwater navigation method of claim 18, further comprising applying a least squares curve fit to the estimated latitude and longitude.

23. The underwater navigation method of claim 18, further comprising applying a Kalman Filter to the estimated latitude and longitude.

24. The underwater navigation method of claim 18, wherein said processing microelectromechanical gyroscope angular rate data further comprises correcting the microelectromechanical gyroscope angular rate data based on vehicle attitude.

25. The underwater navigation method of claim 18, further comprising:

processing GPS data to provide latitude and longitude; and

applying a Kalman Filter to the estimated light sensor longitude, the estimated microelectromechanical gyroscope latitude and the GPS latitude and longitude.

26. The underwater navigation method of claim 18, further comprising:

processing altitude sonar data to provide a vehicle altitude;

matching a terrain map to the altitude data to estimate latitude and longitude; and

applying a Kalman Filter to the estimated light sensor longitude, the estimated microelectromechanical gyroscope latitude and the map-matched latitude and longitude.