Method of using a self-locking travel pattern to achieve calibration of remote sensors using conventionally collected data

• US 20040054488A1
• Filed: 09/17/2002
• Published: 03/18/2004
• Est. Priority Date: 09/17/2002
• Status: Active Grant

• Current Assignee: VI Technologies, LLC (VI GP LLC (f/k/a M7 Visual Intelligence GP LLC))
• Original Assignee: M7 Visual Intelligence, LP
• Inventors: Mai, Tuy Vu
• Granted Patent: US 7,212,938 B2
• Time in Patent Office: Days
• US Class Current: 702/104
• CPC Class Codes: G01C 11/00 Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
• CPC Class Codes: G01C 25/00 Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass testing, calibrating or compensating compasses G01C17/38
• CPC Class Codes: G01S 7/497 Means for monitoring or calibrating

Abstract

The present invention provides a method to calibrate an on-board remote sensing system using a self-locking travel pattern and target remote sensing data. The self-locking travel pattern includes a number of parallel travel lines having overlapping swath widths between adjacent travel lines. The overlapping swath widths are used to determine the boresight angles and range offset of the remote sensor device. In addition, the method can be used to generate estimated horizontal and vertical displacement errors. These estimated errors can be used as correction factors for the range offset and boresight angles.

Claims

1. A method of calibrating a remote sensor system comprising the steps of:

(a) mounting at least one remote sensor on a vehicle;

(b) moving the vehicle in a self-locking pattern over a target area, the movement comprising any pattern that produces at least three substantially parallel travel lines out of a group of three or more lines, at least one of which travel lines is in an opposing direction to the other substantially parallel travel lines;

(c) generating swath widths for each substantially parallel travel line with the remote sensor device;

(d) collecting remote sensing data of the target area during vehicle movement;

(e) inputting the remote sensing data into a computer to calculate calibration data; and

(f) applying the calibration data to the remote sensing data to remove bias in image output.

2. The method of claim 1, wherein the vehicle is an aircraft.

3. The method of claim 1, wherein the vehicle is a satellite.

4. The method of claim 2, wherein the travel pattern comprises at least one pair of parallel flight lines in a matching direction and at least one pair of parallel flight lines in an opposing direction.

5. The method of claim 2 wherein the remote sensor device is LIDAR.

6. The method of claim 1 wherein the yaw angle is calculated using the overlapping swath width areas of pairs of travel lines having matching direction.

7. The method of claim 1 wherein the pitch angle is calculated using the overlapping swath width areas of pairs of travel lines having opposing direction.

8. The method of claim 1 wherein the range offset is calculated using the overlapping swath width areas of pairs of travel lines having matching direction.

9. The method of claim 1 wherein the roll angle is calculated using the overlapping swath width areas of pairs of flight lines having crossing direction.

10. The method of claim 1 wherein the remote sensor device is CCD.

11. A method of calibrating a remote sensor system for use in airborne imaging comprising the steps of:

(a) mounting at least one remote sensor device on an aircraft;

(b) flying the aircraft in a self-locking flying pattern over a target area, the self-locking flying pattern comprising any pattern that produces at least three substantially parallel flight lines out of a group of three or more lines, at least one of which flight lines is in an opposing direction to the other substantially parallel flight lines;

(c) generating swath widths between the adjacent substantially parallel flight lines with the remote sensor device such that the adjacent substantially parallel flight lines produce at least one overlapping swath width area;

(d) collecting remote sensing data of the target area in-flight;

(e) inputting the remote sensing data into a computer to calculate a yaw angle, a pitch angle, a range offset, and a roll angle; and

(f) applying the yaw angle, the pitch angle, the range offset, and the roll angle to remove bias in an image output.

12. The method of claim 11 wherein the flight lines are parallel.

13. The method of claim 11 wherein the self-locking flying pattern includes at least one pair of flight lines in a matching direction and at least one pair of flight lines in an opposing direction.

14. The method of claim 11 wherein the remote sensor device is LIDAR.

15. The method of claim 11 wherein the yaw angle is calculated using the overlapping swath width areas of pairs of flight lines having matching direction.

16. The method of claim 11 wherein the pitch angle is calculated using the overlapping swath width areas of pairs of flight lines having crossing direction.

17. The method of claim 11 wherein the range offset is calculated using the overlapping swath width areas of pairs of flight lines having matching direction.

18. The method of claim 11 wherein the roll angle is calculated using the overlapping swath width areas of pairs of flight lines having crossing direction.

19. A method of calibrating a remote sensor system for use in airborne imaging comprising the steps of:

(a) mounting at least one remote sensor device on an aircraft;

(b) flying the aircraft in a self-locking flying pattern over a target area, the self-locking flying pattern comprising adjacent substantially parallel flight lines having a right outermost flight line, a left outermost flight line and at least one inner flight line, the adjacent substantially parallel flights lines arranged so that the self-locking flying pattern has at least one pair of adjacent substantially parallel flight lines in a matching direction and at least one pair of adjacent substantially parallel flight lines in a opposing direction;

(c) generating swath widths between the adjacent substantially parallel flight lines with the remote sensor device such that adjacent flight lines produce overlapping swath width areas;

(d) collecting remote sensing data of the target area in-flight;

(e) inputting the data images into a computer to calculate a yaw angle, a pitch angle, and a roll angle; and

(f) applying the yaw angle, the pitch angle, and the roll angle to remove bias in an image output.

20. The method of claim 19 wherein the flight lines are parallel.

21. The method of claim 19 wherein the yaw angle is calculated using the overlapping swath width areas of pairs of adjacent substantially parallel flight lines having matching direction.

22. The method of claim 19 wherein the pitch angle is calculated using the overlapping swath width areas of pairs of adjacent substantially parallel flight lines having crossing direction.

23. The method of claim 19 wherein the roll angle is calculated using the overlapping swath width areas of pairs of adjacent substantially parallel flight lines having crossing direction.

24. A method of determining error in a remote sensing system for airborne imaging comprising the steps of:

(a) mounting at least one remote sensor device on an aircraft;

(b) flying the aircraft in a self-locking flying pattern over a target area, the self-locking flying pattern comprising adjacent substantially parallel flight lines arranged so that the self-locking flying pattern includes at least one pair of flight lines in a matching direction and at least one pair of flight lines in an opposing direction;

(c) generating overlapping swath widths areas between the adjacent substantially parallel flight lines with the remote sensor device;

(d) collecting remote sensing data of the target area in-flight;

(e) inputting the remote sensing data into a computer to generate an estimated horizontal displacement error and an estimated vertical displacement error using the swath widths; and

(f) applying the horizontal displacement error and vertical displacement error to the remote sensing data to reduce the error in the remote sensing system.

25. An in-flight calibrated remote sensing system for use in airborne imaging comprising:

(a) at least one remote sensor device mounted to an aircraft;

(b) a self-locking flight pattern; and

(c) a computer having means to compute a yaw angle, a pitch angle, a range offset, and a roll angle using remote sensing data collected by the remote sensor device.

26. The in-flight calibrated remote sensing system of claim 25 wherein the remote sensor device is a three dimensional remote sensor device.

27. The in-flight calibrated remote sensing system of claim 26 wherein the three dimensional remote sensor device is LIDAR.

28. The in-flight calibrated remote sensing system of claim 25 further comprising a positioning device, an attitude sensing device, a memory unit and a navigation guidance system.

29. The in-flight calibrated remote sensing system of claim 25 wherein the computer further comprises means to generate an estimated horizontal displacement error and an estimated vertical displacement error.

30. A self-locking flying pattern comprising substantially parallel flight lines arranged to form a double-up double-down pattern.