Retro-regression residual remediation for spectral/signal identification

• US 7,127,372 B2
• Filed: 02/24/2005
• Issued: 10/24/2006
• Est. Priority Date: 02/24/2005
• Status: Active Grant

• Current Assignee: Peraton, Inc.
• Original Assignee: ITT Manufacturing Enterprises, Inc. (ITT, Inc.)
• Inventors: Boysworth, Marc Kenneth
• Primary Examiner(s): Wachsman, Hal D.
• Application Number:
  US11/064,290
• Publication Number:
  US 20060190216A1
• Time in Patent Office: 607 Days
• Field of Search: 702/179, 702/19, 702/22, 702/23, 702/25, 702/27, 702 30- 32, 702/21
• US Class Current: 702/179
• CPC Class Codes: G01J 3/28 Investigating the spectrum using colour filters G01J3/51
• CPC Class Codes: G01N 2021/6417 Spectrofluorimetric devices
• CPC Class Codes: G01N 21/31 Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry G01N21/72 takes precedence
• CPC Class Codes: G01N 21/33 using ultraviolet light G01N21/39 takes precedence
• CPC Class Codes: G01N 21/359 using near infrared light
• CPC Class Codes: G01N 21/65 Raman scattering
• CPC Class Codes: G01N 2201/1293 resolving multicomponent spectra

Abstract

An improved regression-based qualitative analysis algorithm useful when the mixture to be analyzed contains a compound not in the library spectra, a so-called unknown. A regression of a measured spectrum is computed against the library spectra. This regression is referred to as a “master” regression. Estimated mixing coefficients for an estimated spectrum are computed from the regression. Next, a residual error is computed between the estimated spectrum and the measured spectrum. Peaks in the residual error are identified that extend in a direction opposite to that of peaks in the measured spectrum. These peaks are referred to as “negative” peaks. A regression is performed on the peaks. This is referred to as a “retro-regression” to be distinguished from the master regression performed on the measured spectrum. Using information from the retro-regression, corrected mixing coefficients are computed and the process repeats.

Claims

1. A method for improving regression-based spectroscopic analysis, comprising:

a. computing a residual error between an estimated spectrum and a measured spectrum taken of a sample of a solid, liquid or gas substance to be analyzed using spectroscopy techniques, wherein the estimated spectrum is derived from mixing coefficients for members of a library spectra that are produced by computing a regression on the measured spectrum with the library spectra;

b. identifying peaks in the residual error that extend in a direction opposite to that of peaks in the measured spectrum;

c. performing a regression on the peaks in the residual error that extend in a direction opposite to that of the peaks in the measured spectrum to produce retro-regression coefficients;

d. computing corrected mixing coefficients based on the retro-regression coefficients by subtracting the retro-regression coefficients from the mixing coefficients for the estimated spectrum for a current iteration;

e. repeating (a) through (d) with the corrected mixing coefficients computed in (d) being used to generate a new estimated spectrum for computing the residual error in (a) at the next iteration; and

f. determining whether a chemical or biological constituent whose spectra is contained in said library spectra is present in said sample based on said new estimated spectrum.

2. The method of claim 1, and further comprising (d)(1) removing a member of the library spectra whose mixing coefficient in the corrected mixing coefficients is less than a threshold.

3. The method of claim 2, wherein when a member of the library spectra is removed, further comprising (d)(2) performing a regression of the measured spectrum with the library spectra without the member that was removed to produce new mixing coefficients, and wherein (e) repeating comprises repeating (a) computing, (b) identifying, (c) performing, (d) computing, (d)(1) removing and (d)(2) performing, wherein the new mixing coefficients being used to generate a new estimated spectrum for computing the residual error at the next iteration.

4. The method of claim 3, wherein (e) repeating comprises repeating (a) through (d)(2) until no members of the library spectra remain.

5. The method of claim 1, wherein (e) repeating comprises repeating (a) through (d) until there are no more peaks in the residual error.

6. The method of claim 1, wherein (b) identifying comprises identifying a peak as at least a predetermined number of contiguous points that are on the opposite side, with respect to a baseline, to peaks in the measured spectrum.

7. The method of claim 6, wherein (e) repeating comprises repeating (a) through (d) until there are no more regions in the residual error having at least the predetermined number of contiguous points.

8. A processor readable medium storing instructions that, when executed by a processor, cause the processor to:

a. compute a residual error between an estimated spectrum and a measured spectrum taken of a sample of a solid, liquid or gas substance to be analyzed using spectroscopy techniques, wherein the estimated spectrum is derived from a mixing coefficients for members of a library spectra that are produced by computing a regression on the measured spectrum with the library spectra;

b. identify peaks in the residual error that extend in a direction opposite to that of peaks in the measured spectrum;

c. perform a regression on the peaks in the residual error that extend in a direction opposite to that of the peaks in the measured spectrum to produce retro-regression coefficients;

d. compute corrected mixing coefficients based on the retro-regression coefficients by subtracting the retro-regression coefficients from the mixing coefficients for the estimated spectrum for a current iteration;

e. repeat (a) through (d) with the corrected mixing coefficients computed in (d) being used to generate a new estimated spectrum for computing the residual error in (a) at the next iteration; and

f. determine whether a chemical or biological constituent whose spectra is contained in said library spectra is present in said sample based on said new estimated spectrum.

9. The processor readable medium of claim 8, and further comprising instructions stored on the medium that, when executed, cause the processor to (d)(1) remove a member of the library spectra whose mixing coefficient in the corrected mixing coefficients is less than a threshold.

10. The processor readable medium of claim 9, and further comprising instructions stored on the medium that, when executed, cause the processor to (d)(2) perform a regression of the measured spectrum with the library spectra without the member that was removed to produce new mixing coefficients, and that cause the processor to (e) repeat (a) through (d)(2) with the new mixing coefficients being used to generate a new estimated spectrum for computing the residual error at the next iteration.

11. The processor readable medium of claim 10, and further comprising instructions stored on the medium that, when executed, cause the processor to repeat (a) through (d)(2) until no members of the library spectra remain.

12. The processor readable medium of claim 8, and further comprising instructions stored on the medium that, when executed, cause the processor to repeat (a) through (d) until there are no more peaks in the residual error.

13. The processor readable medium of claim 8, and further comprising instructions stored on the medium that, when executed, cause the processor to identify a peak as at least a predetermined number of contiguous points that are on the opposite side, with respect to a baseline, to peaks in the measured spectrum.

14. The processor readable medium of claim 8, and further comprising instructions stored on the medium that, when executed, cause the processor to repeat (a) through (d) until there are no more regions in the residual error having at least the predetermined number of contiguous points.

15. A system for spectroscopic analysis comprising:

a. a sensor that produces data from a sample of a solid, liquid or gas substance to be analyzed using spectroscopy techniques; and

b. a processor coupled to the sensor, wherein the processor is programmed to;

i. generate a measured spectrum from the data produced by the sensor;

ii. perform a regression of the measured spectrum with a library spectra;

iii. generate estimated mixing coefficients from the regression;

iv. compute a residual error between an estimated spectrum generated from the estimated mixing coefficients and the measured spectrum;

v. identify peaks in the residual error that extend in a direction opposite to that of peaks in the measured spectrum;

vi. perform a regression on the peaks in the residual error that extend in a direction opposite to that of the peaks in the measured spectrum to produce retro-regression coefficients;

vii. compute corrected mixing coefficients based on the retro-regression coefficients by subtracting the retro-regression coefficients from the mixing coefficients for the estimated spectrum for a current iteration;

viii. repeat (iv) through (vii) with the corrected mixing coefficients computed in (vii) being used to generate a new estimated spectrum for computing the residual error in (iv) at the next iteration; and

ix. determine whether a chemical or biological constituent whose spectra is contained in said library spectra is present in said sample based on said new estimated spectrum.

16. The system of claim 15, wherein the processor is programmed to remove a member of the library spectra whose mixing coefficient in the corrected mixing coefficients is less than a threshold.

17. The system of claim 16, wherein the processor is programmed to perform a regression of the measured spectrum with the library spectra without the member that was removed to produce new mixing coefficients, and repeating (iv) through (vii) with the new mixing coefficients being used to generate a new estimated spectrum for computing the residual error at the next iteration.