IP Library Granted Patent US 9,816,863
Granted Patent B1
US 9,816,863 · App. 14/497,996 · Granted Nov 14, 2017

Wind field vertical profile estimation using spectral radiance of multiband imagery and temperature profiles

Inventors: Christopher E Lietzke (Fort Wayne, IN); Ronald J Glumb (Fort Wayne, IN)
Assignee: Harris Corporation
G01J5/007G01B11/0608G01C11/06G01J5/505G01W1/10
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Quick Facts
Patent No.
US 9,816,863
App. No.
14/497,996
Granted
Nov 14, 2017
Kind
B1
Abstract

Techniques are provided for an image processing device to receive image information comprising image data for a plurality of mid-wave infrared region (MWIR) channels, where the image data is obtained during a first imaging period and during a second imaging period temporally different from the first imaging period. A plurality of sets of atmospheric wind vectors are calculated using differences between image data obtained during the first imaging period and the image data obtained during the second imaging period for corresponding sets of MWIR channels. An altitude is assigned to the plurality of atmospheric wind vectors in each set based on a brightness temperature of each wind vector and a pre-computed atmospheric temperature profile to generate a set of two-dimensional wind fields comprising one two-dimensional wind field for each set of MWIR channels.

Claims (47)

1. An apparatus comprising:

a receiver configured to receive from an image sensor image information comprising image data for a plurality of mid-wave infrared region (MWIR) channels, wherein the image data includes hyperspectral atmospheric radiance indicative of brightness temperatures of the atmosphere, and wherein the image data is obtained during a first imaging period and during a second imaging period temporally different from the first imaging period; and

at least one processor to generate atmospheric wind fields using the image data and atmospheric temperature profile information, the at least one processor configured to:

calculate a plurality of sets of atmospheric wind vectors using differences between image data obtained during the first imaging period and the image data obtained during the second imaging period for corresponding sets of MWIR channels;

assign an altitude to the plurality of atmospheric wind vectors in each set based on a brightness temperature of each wind vector as indicated in the image data and a pre-computed atmospheric temperature profile to generate a set of two-dimensional wind fields comprising one two-dimensional wind field for each set of MWIR channels;

apply temporal constraints to the set of two-dimensional wind fields using a previously generated set of two-dimensional wind fields to produce a three-dimensional wind field product; and

apply spatial constraints in the horizontal plane in order to filter out grid point data that do not meet given horizontal spatial constraints.

2. The apparatus of claim 1 , wherein the at least one processor is further configured to:

interpolate atmospheric wind vectors in each set of atmospheric wind vectors to a geographic grid in order to correlate atmospheric wind vectors among each set of atmospheric wind vectors to the geographic grid.

3. The apparatus of claim 2 , wherein each set of MWIR channels comprise frequency contiguous sets of MWIR channels in a channel group, and the at least one processor is further configured to:

combine image data for each channel group to produce a plurality of imagery subsets; and

correlate imagery subset data combined from image data obtained during the first imaging period with imagery subset data combined from image data obtained during the second imaging period.

4. The apparatus of claim 3 , wherein the at least one processor is further configured to:

calculate the average brightness temperature for image data associated with each channel group at grid points in the geographic grid.

5. The apparatus of claim 1 , wherein the at least one processor is further configured to:

apply vertical constraints in the vertical plane in order to filter out grid point data that do not meet given vertical spatial constraints.

6. A computer implemented method of generating atmospheric wind fields using image data of the atmosphere and atmospheric temperature profile information:

at an image processing device including memory and a processor coupled to the memory, receiving from an image sensor image information comprising the image data for a plurality of mid-wave infrared region (MWIR) channels, wherein the image data includes hyperspectral atmospheric radiance indicative of brightness temperatures of the atmosphere, and wherein the image data is obtained during a first imaging period and during a second imaging period temporally different from the first imaging period;

calculating a plurality of sets of atmospheric wind vectors using differences between image data obtained during the first imaging period and the image data obtained during the second imaging period for corresponding sets of MWIR channels;

assigning an altitude to the plurality of atmospheric wind vectors in each set based on a brightness temperature of each wind vector as indicated in the image data and a pre-computed atmospheric temperature profile to generate a set of two-dimensional wind fields comprising one two-dimensional wind field for each set of MWIR channels; and

calculating an average brightness temperature for image data associated with each channel group at grid points in the geographic grid.

7. The method of claim 6 , further comprising:

applying temporal constraints to the set of two-dimensional wind fields using a previously generated set of two-dimensional wind fields to produce a three-dimensional wind field product.

8. The method of claim 7 , further comprising:

applying spatial constraints in the horizontal plane in order to filter out grid point data that do not meet given horizontal spatial constraints.

9. The method of claim 7 , further comprising:

applying vertical constraints in the vertical plane in order to filter out grid point data that do not meet given vertical spatial constraints.

10. The method of claim 6 , further comprising:

interpolating atmospheric wind vectors in each set of atmospheric wind vectors to a geographic grid in order to correlate atmospheric wind vectors among each set of atmospheric wind vectors to the geographic grid.

11. The method of claim 10 , wherein each set of MWIR channels comprise frequency contiguous sets of MWIR channels in a channel group, the method further comprising:

combining image data for each channel group to produce a plurality of imagery subsets; and

correlating imagery subset data combined from image data obtained during the first imaging period with imagery subset data combined from image data obtained during the second imaging period.

12. A non-transitory computer readable medium encoded with software comprising processor-executable instructions that, when executed by a processor of an image processing device, cause the processor to generate atmospheric wind fields using image data of the atmosphere and atmospheric temperature profile information by performing the functions of:

receiving from an image sensor image information comprising image data for a plurality of mid-wave infrared region (MWIR) channels, wherein the image data includes hyperspectral atmospheric radiance indicative of brightness temperatures of the atmosphere, and wherein the image data is obtained during a first imaging period and during a second imaging period temporally different from the first imaging period;

calculating a plurality of sets of atmospheric wind vectors using differences between image data obtained during the first imaging period and the image data obtained during the second imaging period for corresponding sets of MWIR channels;

assigning an altitude to the plurality of atmospheric wind vectors in each set based on a brightness temperature of each wind vector as indicated in the image data and a pre-computed atmospheric temperature profile to generate a set of two-dimensional wind fields comprising one two-dimensional wind field for each set of MWIR channels; and

interpolating atmospheric wind vectors in each set of atmospheric wind vectors to a geographic grid in order to correlate atmospheric wind vectors among each set of atmospheric wind vectors to the geographic grid.

13. The non-transitory computer readable medium of claim 12 , further comprising instructions that, when executed by a processor, cause the processor to perform functions of:

applying temporal constraints to the set of two-dimensional wind fields using a previously generated set of two-dimensional wind fields to produce a three-dimensional wind field product.

14. The non-transitory computer readable medium of claim 12 , wherein each set of MWIR channels comprise frequency contiguous sets of MWIR channels in a channel group, and further comprising instructions that, when executed by a processor, cause the processor to perform functions of:

combining image data for each channel group to produce a plurality of imagery subsets; and

correlating imagery subset data combined from image data obtained during the first imaging period with imagery subset data combined from image data obtained during the second imaging period.

15. The non-transitory computer readable medium of claim 13 , further comprising instructions that, when executed by a processor, cause the processor to perform functions of:

calculating the average brightness temperature for image data associated with each channel group at grid points in the geographic grid.

16. The non-transitory computer readable medium of claim 13 , further comprising instructions that, when executed by a processor, cause the processor to perform one or more functions of:

applying spatial constraints in the horizontal plane in order to filter out grid point data that do not meet given horizontal spatial constraints; and

applying vertical constraints in the vertical plane in order to filter out grid point data that do not meet given vertical spatial constraints.

Assignments (2)
MERGER Recorded Oct 12, 2017
From: EXELIS INC.
To: HARRIS CORPORATION
Reel/Frame 043854/0188 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 26, 2014
From: LIETZKE, CHRISTOPHER E; GLUMB, RONALD J
To: EXELIS INC.
Reel/Frame 033828/0838 →