Inertial measurement with an imaging sensor and a digitized map

• US 20100010741A1
• Filed: 07/10/2008
• Published: 01/14/2010
• Est. Priority Date: 07/10/2008
• Status: Active Grant

• Current Assignee: Lockheed Martin Corporation (Martin Marietta Corporation)
• Original Assignee: Lockheed Martin Missiles & Fire Control (Martin Marietta Corporation)
• Inventors: Glaros, Louis N., Bovankovich, Mark A., Hawkins, Andrew H., Tener, Gene D.
• Granted Patent: US 8,265,817 B2
• Time in Patent Office: Days
• US Class Current: 701/220
• CPC Class Codes: F41G 7/34 based on predetermined target position data
• CPC Class Codes: G01C 21/005 with correlation of navigation data from several sources, e.g. map or contour matching G01C21/30 takes precedence
• CPC Class Codes: G01S 13/876 Combination of several spaced transponders or reflectors of known location for determining the position of a receiver G01S13/874 takes precedence
• CPC Class Codes: G01S 17/875 for determining attitude
• CPC Class Codes: G01S 5/163 Determination of attitude using inertial means G01C9/00; control of attitude G05D1/49
• CPC Class Codes: G05D 1/106 Change initiated in response to external conditions, e.g. avoidance of elevated terrain or of no-fly zones
• CPC Class Codes: G06T 2207/10032 Satellite or aerial image; Remote sensing
• CPC Class Codes: G06T 2207/30252 Vehicle exterior; Vicinity of vehicle
• CPC Class Codes: G06T 7/75 involving models

Abstract

The present invention relates to a system and method for determining vehicle attitude and position from image data detected by sensors in a vehicle. The invention uses calculated differences between the locations of selected features in an image plane and the location of corresponding features in a terrain map to determine the attitude of the vehicle carrying the sensors with respect to a ground frame of reference.

Claims

1. A method of electro-optical own-vehicle attitude determination of a moving object comprising:

capturing image data of a first scene from the moving object with a detector or sensor;

identifying at least three features from the image data of said first scene;

correlating said at least three features to features in a map to determine corresponding map locations of said features and a location of the vehicle within the map; and

calculating the attitude of the moving object based on the difference between the locations of the at least three features in the image data and the locations of the correlated features in the map.

2. The method of claim 1, said detector or sensor further comprising that measures the angle of a detected entity with respect to its boresight reference;

and

said identifying at least three features from image data comprising;

selecting features within the pixel space of the image data; and

transforming the selected features into a first set of object space angular coordinates based on the angle of the detected features with respect to the boresight reference of the sensor or detector.

3. The method of claim 2, said calculating the attitude comprising:

transforming the correlated features from the map into a second set of object space angular coordinates based on the location of the vehicle within the map; and

computing the horizontal, vertical, and arc coordinate differences between a coordinate from the first set and its correlated coordinate from the second set.

4. The method of claim 3, further comprising:

calculating pitch based on vertical values of the coordinate differences relative to the imaging plane.

5. The method of claim 3, further comprising:

calculating roll based on horizontal values of the coordinate differences.

6. The method of claim 3, further comprising:

calculating yaw based on arc-length distance from a coordinate from the first set and its correlated coordinate from the second set relative to a reference point in the imaging plane equidistant from both coordinates.

7. The method of claim 1, said image data comprising vehicle-relative locations of passively-detected transmitter beacons wherein at least one feature of said at least three features comprises a transmitter beacon location.

8. The method of claim 1, said image data comprising visible-spectrum imaging data.

9. The method of claim 1, said map comprising a terrain map.

10. The method of claim 4, said map comprising a listing of known beacon locations.

11. The method of claim 1, further comprising:

tracking the at least three features within image data of a second scene captured subsequent to the first scene;

determining, based on the relative changes in position of the at least three features, the change in position of the moving object relative to the at least three features;

calculating, based on a comparison of the determined change in position of the moving object against a previously known position of the moving object, a new position and movement rate and direction for the moving object.

12. The method of claim 11, said previously known position of said moving object comprising a location, orientation, and movement rate and direction of said moving object previously determined by said calculating, based on a comparison.

13. The method of claim 11, said previously known position of said moving object comprising a known position provided through external means comprising user input, a GPS system, or an external tracking system.

14. The method of claim 11, further comprising:

tracking the at least three features within image data of a third scene captured subsequent to the second scene;

determining, based on the relative changes in position of the at least three features, the change in position of the moving object from the second scene to the third scene relative to the at least three features; and

calculating, based on a comparison of the determined change in position of the moving object from the first scene to the second scene and the change in position of the moving object from the second scene to the third scene, an acceleration rate and acceleration direction for the moving object.

15. The method of claim 1, wherein a line-of-sight (LOS) unit vector from the detector to an identified feature is computed as a function of LOS angles (ε

_yi and ε

_zi) measured relative to the detector, such that the unit vector (u) is given by the expression;

${\hat{u}}_i^{d_i}=\left(\begin{array}{c}\cos <br><br>\left({\mathrm{\varepsilon <br><br>}}_{y_i}\right)·<br><br>\cos <br><br>\left({\mathrm{\varepsilon <br><br>}}_{z_i}\right)\\ \cos <br><br>\left({\mathrm{\varepsilon <br><br>}}_{y_i}\right)·<br><br>\sin <br><br>\left({\mathrm{\varepsilon <br><br>}}_{z_i}\right)\\ -\sin <br><br>\left({\mathrm{\varepsilon <br><br>}}_{y_i}\right)\end{array}\right)$

16. A device for electro-optically determining own-vehicle attitude of a moving object, the device comprising:

an imaging sensor that captures image data of scenes from the moving object;

a feature identification unit that identifies features in captured image data;

a feature correlation unit that correlates identified features to a map;

a feature locator that determines corresponding map locations of the correlated features and a location of the vehicle within the map;

an attitude calculator that calculates the attitude of the moving object based on the difference in the locations of the at least three features in the image data and the locations of the correlated features in the map.

17. The device of claim 16, the imaging sensor comprising an imaging sensor that measures the angle of a detected entity with respect to its boresight reference;

and

the feature identification unit comprising;

a feature selection unit that selects features within the pixel space of the image data; and

a space transformation module that transforms the selected features into a first set of object space angular coordinates based on the angle of the detected features with respect to the boresight reference of the sensor.

18. The device of claim 17, the attitude calculator comprising:

a map transformation module that transforms the correlated features from the map into a second set of object space angular coordinates based on the location of the vehicle within the map; and

a difference computation unit that computes the horizontal, vertical, and arc coordinate differences between a coordinate from the first set and its correlated coordinate from the second set.

19. The device of claim 18, the attitude calculator further comprising:

a pitch calculator that calculates pitch based on vertical values of the coordinate differences relative to the imaging plane.

20. The device of claim 18, the attitude calculator further comprising:

a roll calculator that calculates roll based on horizontal values of the coordinate differences.

21. The device of claim 18, the attitude calculator further comprising:

a yaw calculator that calculates yaw based on arc-length distance from a coordinate from the first set and its correlated coordinate from the second set relative to a reference point in the imaging plane equidistant from both coordinates.

22. The device of claim 16, said image data comprising vehicle-relative locations of passively-detected transmitter beacons wherein at least one feature of said at least three features comprises a transmitter beacon location.

23. The device of claim 16, said imaging sensor comprising a visible-spectrum imaging sensor.

24. The device of claim 16, further comprising a memory unit that stores said map, wherein the map is a terrain map.

25. The device of claim 16, further comprising:

a feature tracker that tracks the at least three features within image data of at a second scene captured subsequent to the first scene;

a relative position computer that determines, based on the relative changes in position of the at least three features, the change in position of the moving object relative to the at least three features;

a movement and position calculator that calculates, based on a comparison of the determined change in position of the moving object against a previously known position of the moving object, a new position and movement rate and direction for the moving object.

26. The device of claim 25, said previously known position of said moving object comprising a location, orientation, and movement rate and direction of said moving object previously determined by said calculating, based on a comparison.

27. The device of claim 25, said previously known position of said moving object comprising a known position provided through external means comprising user input, a GPS system, or an external tracking system.

28. The device of claim 25, further comprising:

an acceleration feature tracker that tracks the at least three features within image data of a third scene captured subsequent to the second scene;

an acceleration position computer that determines, based on the relative changes in position of the at least three features, the change in position of the moving object from the second scene to the third scene relative to the at least three features; and

an acceleration calculator that calculates, based on a comparison of the determined change in position of the moving object from the first scene to the second scene and the change in position of the moving object from the second scene to the third scene, an acceleration rate and acceleration direction for the moving object.