WO2003054824B1 - Small spectral signal detection system - Google Patents
Small spectral signal detection systemInfo
- Publication number
- WO2003054824B1 WO2003054824B1 PCT/US2002/030429 US0230429W WO03054824B1 WO 2003054824 B1 WO2003054824 B1 WO 2003054824B1 US 0230429 W US0230429 W US 0230429W WO 03054824 B1 WO03054824 B1 WO 03054824B1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- scene
- chemical vapor
- feature vector
- interferogram
- detection system
- Prior art date
Links
- 230000003595 spectral effect Effects 0.000 title claims abstract 4
- 238000001514 detection method Methods 0.000 title abstract 4
- 239000000126 substance Substances 0.000 claims abstract 6
- 238000001228 spectrum Methods 0.000 claims abstract 3
- 238000011088 calibration curve Methods 0.000 claims abstract 2
- 238000000034 method Methods 0.000 claims 3
- 230000001537 neural effect Effects 0.000 claims 1
- 239000013043 chemical agent Substances 0.000 abstract 4
- 238000013528 artificial neural network Methods 0.000 abstract 1
- 238000012790 confirmation Methods 0.000 abstract 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3504—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing gases, e.g. multi-gas analysis
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
- G01J3/28—Investigating the spectrum
- G01J3/45—Interferometric spectrometry
- G01J3/453—Interferometric spectrometry by correlation of the amplitudes
- G01J3/4535—Devices with moving mirror
Landscapes
- Physics & Mathematics (AREA)
- Spectroscopy & Molecular Physics (AREA)
- General Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
- Spectrometry And Color Measurement (AREA)
Abstract
A standoff chemical agent detection system passively detects chemical agents in a scene. Interferograms are generated from received scene spectral information. In one embodiment, the spectral information is apodized, and a chirp Fast Fourier Transform is performed on the interferogram. A calibration curve is applied to correct gain and offset, and a feature vector is generated based on comparison of the normalized spectrum to predetermined chemical shape templates. The feature vector is provided to a classifier to identify the existence and identity of a chemical agent threat. The chemical agent detection system utilizes a lower resolution search mode, and a higher resolution confirmation mode, wherein both modes utilize the same detection algorithms. The neural network is trained using a large database of training data. The network is iteratively trained using partially random subsets of the training data. Problematic data from previous subsets is included in further subsets to improve the training.
Claims
AMENDED CLAIMS
[received by the International Bureau on 25 July 2003 (25.07.03); original claims 1-25 replaced by amended claims 1-26 (1 page)]
extracting features from the preprocessed spectrum corresponding to predefined feature templates representative of chemical vapor clouds; and processing the features to determine whether, a chemical vapor cloud is present in the scene.
25. A computer readable medium having instructions for causing a computer to perform a method of detecting chemical vapor clouds in a scene, the method comprising: generating an interferogram from received scene spectral information; performing apodization on the interferogram; performing a chirp Fast Fourier Transform on the apodized interferogram; applying a calibration curve to correct gain and/or offset; and matching the gain/offset corrected spectrum to selected chemical vapor cloud shape templates.
26. The computer readable medium of claim 25, wherein the method further comprises: creating feature vector based on the matching to the templates; and processing the feature vector through a neural net to determine whether a chemical vapor clouds is present in the scene.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| EP02803278A EP1430280A2 (en) | 2001-09-24 | 2002-09-24 | Small spectral signal detection system |
| AU2002365125A AU2002365125A1 (en) | 2001-09-24 | 2002-09-24 | Small spectral signal detection system |
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US32439701P | 2001-09-24 | 2001-09-24 | |
| US60/324,397 | 2001-09-24 |
Publications (3)
| Publication Number | Publication Date |
|---|---|
| WO2003054824A2 WO2003054824A2 (en) | 2003-07-03 |
| WO2003054824A3 WO2003054824A3 (en) | 2003-12-18 |
| WO2003054824B1 true WO2003054824B1 (en) | 2004-02-19 |
Family
ID=23263396
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/US2002/030429 WO2003054824A2 (en) | 2001-09-24 | 2002-09-24 | Small spectral signal detection system |
Country Status (3)
| Country | Link |
|---|---|
| EP (1) | EP1430280A2 (en) |
| AU (1) | AU2002365125A1 (en) |
| WO (1) | WO2003054824A2 (en) |
Families Citing this family (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| AU2003295702A1 (en) * | 2002-11-20 | 2004-06-15 | Honeywell International Inc. | Signature simulator |
| US8487979B2 (en) | 2008-11-26 | 2013-07-16 | Honeywell International Inc. | Signal spectra detection system |
| US8117010B2 (en) | 2008-12-05 | 2012-02-14 | Honeywell International Inc. | Spectral signal detection system |
| CN102496060A (en) * | 2011-12-07 | 2012-06-13 | 高汉中 | Neural network-based cloud intelligent machine system |
| US11488369B2 (en) | 2017-02-07 | 2022-11-01 | Teledyne Flir Detection, Inc. | Systems and methods for identifying threats and locations, systems and method for augmenting real-time displays demonstrating the threat location, and systems and methods for responding to threats |
| WO2018148316A1 (en) | 2017-02-07 | 2018-08-16 | Flir Detection, Inc. | Systems and methods for identifying threats and locations, systems and method for augmenting real-time displays demonstrating the threat location, and systems and methods for responding to threats |
| WO2018187548A2 (en) * | 2017-04-05 | 2018-10-11 | Arizona Board Of Regents On Behalf Of Arizona State University | Antimicrobial susceptibility testing with large-volume light scattering imaging and deep learning video microscopy |
| CN117233119B (en) * | 2023-11-10 | 2024-01-12 | 北京环拓科技有限公司 | Method for identifying and quantifying VOC (volatile organic compound) gas cloud image by combining sensor calibration module |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5563982A (en) * | 1991-01-31 | 1996-10-08 | Ail Systems, Inc. | Apparatus and method for detection of molecular vapors in an atmospheric region |
| DE4203588C2 (en) * | 1991-02-16 | 1996-11-14 | Horiba Ltd | Quantitative spectral analysis method |
| US5241179A (en) * | 1991-09-09 | 1993-08-31 | The United States Of America As Represented By The Secretary Of The Navy | Thermoluminescence sensor for the remote detection of chemical agents and their simulants |
| US5631469A (en) * | 1996-04-15 | 1997-05-20 | The United States Of America As Represented By The Secretary Of The Army | Neural network computing system for pattern recognition of thermoluminescence signature spectra and chemical defense |
| US6266428B1 (en) * | 1998-02-06 | 2001-07-24 | The United States Of America As Represented By The Secretary Of The Army | System and method for remote detection of hazardous vapors and aerosols |
| US5982486A (en) * | 1998-04-23 | 1999-11-09 | Ail Systems, Incorporated | Method and apparatus for on-the-move detection of chemical agents using an FTIR spectrometer |
-
2002
- 2002-09-24 EP EP02803278A patent/EP1430280A2/en not_active Withdrawn
- 2002-09-24 WO PCT/US2002/030429 patent/WO2003054824A2/en not_active Application Discontinuation
- 2002-09-24 AU AU2002365125A patent/AU2002365125A1/en not_active Abandoned
Also Published As
| Publication number | Publication date |
|---|---|
| WO2003054824A2 (en) | 2003-07-03 |
| EP1430280A2 (en) | 2004-06-23 |
| WO2003054824A3 (en) | 2003-12-18 |
| AU2002365125A1 (en) | 2003-07-09 |
| AU2002365125A8 (en) | 2003-07-09 |
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