Targeted Agile Raman System for Detection of Unknown Materials

• US 20130135609A1
• Filed: 12/28/2012
• Published: 05/30/2013
• Est. Priority Date: 06/17/2010
• Status: Abandoned Application

• Current Assignee: Chemimage Corporation
• Original Assignee: Chemimage Corporation
• Inventors: Gardner, Charles Jr., Nelson, Matthew
• Application Number:
  US13/729,171
• Publication Number:
  US 20130135609A1
• Time in Patent Office: Days
• US Class Current: 356/51
• CPC Class Codes: G01J 3/02 Details
• CPC Class Codes: G01J 3/0221 the fibers defining an entry slit
• CPC Class Codes: G01J 3/0264 Electrical interface; User interface
• CPC Class Codes: G01J 3/2823 Imaging spectrometer
• CPC Class Codes: G01J 3/36 Investigating two or more bands of a spectrum by separate detectors
• CPC Class Codes: G01J 3/44 Raman spectrometry; Scattering spectrometry ; Fluorescence spectrometry
• CPC Class Codes: G01N 2021/1738 Optionally different kinds of measurements; Method being valid for different kinds of measurement
• CPC Class Codes: G01N 2021/174 either absorption-reflection or emission-fluorescence
• CPC Class Codes: G01N 2021/1744 either absorption or scatter
• CPC Class Codes: G01N 21/6456 Spatial resolved fluorescence measurements; Imaging
• CPC Class Codes: G01N 21/65 Raman scattering
• CPC Class Codes: G01N 33/22 Fuels; Explosives

Abstract

The present disclosure provides for a system and method for detecting unknown materials. A test data set, which may comprise a hyperspectral data set, is generated representative of a first location. The test data set may be analyzed to determine a second location which may be interrogated using a Raman spectroscopic device to generate a Raman data set. The Raman data set may be analyzed to associated an unknown material with a known material such as: a chemical material, a biological material, an explosive material, a hazardous material, a drug material, and combinations thereof.

Claims

1. A method comprising:

scanning a first location comprising an unknown material using a first modality to generate a test data set representative of the first location;

analyzing the test data set to identify a second location;

assessing the second location using a Raman spectroscopic device to generate a Raman data set representative of the second location; and

analyzing the Raman data set to associate the unknown material with at least one known material.

2. The method of claim 1 wherein at least a portion of the first location and the second location overlap.

3. The method of claim 1 wherein generating the test data set further comprises:

illuminating the first location to generate a first plurality of interacted photons;

passing the first plurality of interacted photons through a filter; and

detecting the first plurality of interacted photons to generate the test data set.

4. The method of claim 3 wherein the filter further comprises at least one of:

a tunable filter, a fixed filter, a dielectric filter, and combinations thereof.

5. The method of claim 3 wherein the illuminating is achieved using at least one of:

active illumination, passive illumination, and combinations thereof.

6. The method of claim 5 wherein illuminating further comprises the use of a tunable illumination source.

7. The method of claim 1 wherein assessing the second location further comprises:

illuminating the second location to generate a second plurality of interacted photons;

passing the interacted photons through a fiber array spectral translator device; and

detecting the second plurality of interacted photons to generate the Raman data set.

8. The method of claim 7 wherein the illuminating is achieved using at least one of active illumination, passive illumination, and combinations thereof.

9. The method of claim 7 wherein illuminating further comprises the use of a tunable illumination source.

10. The method of claim 1 wherein the unknown material further comprises at least one of:

a chemical material, a biological material, an explosive material, a hazardous material, a drug material, and combinations thereof.

11. The method of claim 1 wherein the test data set further comprises at least one of:

an infrared test data set, a visible test data set, a visible-near infrared test data set, a fluorescence test data set, and combinations thereof.

12. The method of claim 11 wherein the infrared test data set further comprises at least one of:

a SWIR test data set, a MWIR test data set, a LWIR test data set, and combinations thereof.

13. The method of claim 1 wherein the first location is scanned in at least one of the following modalities:

on-the-move, stationary, and combinations thereof.

14. The method of claim 1 wherein the second location is assessed in at least one of the following modalities:

on-the-move, stationary, and combinations thereof.

15. The method of claim 1 wherein analyzing the test data set further comprises:

comparing the test data set to at least one reference data set.

16. The method of claim 15 wherein the comparing is achieved by applying at least one chemometric technique.

17. The method of claim 16 wherein the chemometric technique is selected from the group consisting of:

principle components analysis, partial least squares discriminate analysis, cosine correlation analysis, Euclidian distance analysis, k-means clustering, multivariate curve resolution, band t. entropy method, mahalanobis distance, adaptive subspace detector, spectral mixture resolution, Bayesian fusion, and combinations thereof.

18. The method of claim 1 wherein generating the test data set further comprises filtering interacted photons from the first location into a plurality of wavelength bands using a tunable filter.

19. The method of claim 1 further comprising illuminating at least one of the first location and the second location using wide-field illumination.

20. The method of claim 1 wherein the test data set further comprises at least one of:

a spectrum, a spatially accurate wavelength image, a hyperspectral image, and combinations thereof.

21. The method of claim 1 wherein the Raman data set further comprises at least one of:

a Raman spectrum, a spatially accurate Raman image, a hyperspectral image, and combinations thereof.

22. The method of claim 1 wherein at least one of the test data set and the Raman data set are generated using pulsed laser excitation and time-gated detection.