Abstract

In a recently demonstrated algorithmic spectral-tuning technique by Jang et al. [Opt. Express 19, 19454-19472, (2011)], the reconstruction of an object’s emissivity at an arbitrarily specified spectral window of interest in the long-wave infrared region was achieved. The technique relied upon forming a weighted superposition of a series of photocurrents from a quantum dots-in-a-well (DWELL) photodetector operated at discrete static biases that were applied serially. Here, the technique is generalized such that a continuously varying biasing voltage is employed over an extended acquisition time, in place using a series of fixed biases over each sub-acquisition time, which totally eliminates the need for the post-processing step comprising the weighted superposition of the discrete photocurrents. To enable this capability, an algorithm is developed for designing the time-varying bias for an arbitrary spectral-sensing window of interest. Since continuous-time biasing can be implemented within the readout circuit of a focal-plane array, this generalization would pave the way for the implementation of the algorithmic spectral tuning in focal-plane arrays within in each frame time without the need for on-sensor multiplications and additions. The technique is validated by means of simulations in the context of spectrometry and object classification while using experimental data for the DWELL under realistic signal-to-noise ratios.

© 2012 OSA

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    [CrossRef]
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    [CrossRef]
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    [CrossRef]
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    [CrossRef]
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    [CrossRef]
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2011

2010

M. G. Brown, J. Baker, C. Colonero, J. Costa, T. Gardner, M. Kelly, K. Schultz, B. Tyrrell, and J. Wey, “Digital-pixel focal plane array development,” Proc. SPIE7608, 76082H, 76082H-10 (2010).
[CrossRef]

2009

W.-Y. Jang, M. M. Hayat, J. S. Tyo, R. S. Attaluri, T. E. Vandervelde, Y. D. Sharma, R. Shenoi, A. Stintz, E. R. Cantwell, S. C. Bender, S. J. Lee, S. K. Noh, and S. Krishna, “Demonstration of bias controlled algorithmic tuning of quantum dots in a well (DWELL) MidIR detectors,” IEEE J. Quantum Electron.45(6), 5537–5540 (2009).
[CrossRef]

2008

B. Paskaleva, M. M. Hayat, Z. Wang, J. S. Tyo, and S. Krishna, “Canonical correlation feature selection for sensors with overlapping bands: theory and application,” IEEE T. Geo. Remote Sens.46(10), 3346–3358 (2008).
[CrossRef]

2006

2005

S. Krishna, “Quantum dots-in-a-well infrared photodetectors,” J. Phys. D Appl. Phys.38(13), 2142–2150 (2005).
[CrossRef]

2004

2003

S. Krishna, S. Raghavan, G. von Winckel, A. Stintz, G. Ariyawansa, S. G. Matsik, and A. G. U. Perera, “Three-color (λp1~3.8μm, λp2~8.5μm, λp3~23.2μm) InAs/InGaAs quantum-dots-in-a-well detector,” Appl. Phys. Lett.83(14), 2745–2747 (2003).
[CrossRef]

T. Yasuda, T. Hamamoto, and K. Aizawa, “Adaptive-integration-time image sensor with real-time reconstruction function,” IEEE Trans. Electron. Dev.50(1), 111–120 (2003).
[CrossRef]

2001

T. Hamamoto and K. Aizawa, “A computational image sensor with adaptive pixel-based integration time,” IEEE J. Solid-state Circuits36(4), 580–585 (2001).
[CrossRef]

1984

D. A. B. Miller, D. S. Chemla, T. C. Damen, A. C. Gossard, W. Wiegmann, T. H. Wood, and C. A. Burrus, “Band-edge electroabsorption in quantum well structures: the quantum-confined stark effect,” Phys. Rev. Lett.53(22), 2173–2176 (1984).
[CrossRef]

Aizawa, K.

T. Yasuda, T. Hamamoto, and K. Aizawa, “Adaptive-integration-time image sensor with real-time reconstruction function,” IEEE Trans. Electron. Dev.50(1), 111–120 (2003).
[CrossRef]

T. Hamamoto and K. Aizawa, “A computational image sensor with adaptive pixel-based integration time,” IEEE J. Solid-state Circuits36(4), 580–585 (2001).
[CrossRef]

Annamalai, S.

Ariyawansa, G.

S. Krishna, S. Raghavan, G. von Winckel, A. Stintz, G. Ariyawansa, S. G. Matsik, and A. G. U. Perera, “Three-color (λp1~3.8μm, λp2~8.5μm, λp3~23.2μm) InAs/InGaAs quantum-dots-in-a-well detector,” Appl. Phys. Lett.83(14), 2745–2747 (2003).
[CrossRef]

Attaluri, R. S.

W.-Y. Jang, M. M. Hayat, J. S. Tyo, R. S. Attaluri, T. E. Vandervelde, Y. D. Sharma, R. Shenoi, A. Stintz, E. R. Cantwell, S. C. Bender, S. J. Lee, S. K. Noh, and S. Krishna, “Demonstration of bias controlled algorithmic tuning of quantum dots in a well (DWELL) MidIR detectors,” IEEE J. Quantum Electron.45(6), 5537–5540 (2009).
[CrossRef]

Baker, J.

M. G. Brown, J. Baker, C. Colonero, J. Costa, T. Gardner, M. Kelly, K. Schultz, B. Tyrrell, and J. Wey, “Digital-pixel focal plane array development,” Proc. SPIE7608, 76082H, 76082H-10 (2010).
[CrossRef]

Bender, S. C.

W.-Y. Jang, M. M. Hayat, S. E. Godoy, S. C. Bender, P. Zarkesh-Ha, and S. Krishna, “Data compressive paradigm for multispectral sensing using tunable DWELL mid-infrared detectors,” Opt. Express19(20), 19454–19472 (2011).
[CrossRef] [PubMed]

W.-Y. Jang, M. M. Hayat, J. S. Tyo, R. S. Attaluri, T. E. Vandervelde, Y. D. Sharma, R. Shenoi, A. Stintz, E. R. Cantwell, S. C. Bender, S. J. Lee, S. K. Noh, and S. Krishna, “Demonstration of bias controlled algorithmic tuning of quantum dots in a well (DWELL) MidIR detectors,” IEEE J. Quantum Electron.45(6), 5537–5540 (2009).
[CrossRef]

Brown, M. G.

M. G. Brown, J. Baker, C. Colonero, J. Costa, T. Gardner, M. Kelly, K. Schultz, B. Tyrrell, and J. Wey, “Digital-pixel focal plane array development,” Proc. SPIE7608, 76082H, 76082H-10 (2010).
[CrossRef]

Burrus, C. A.

D. A. B. Miller, D. S. Chemla, T. C. Damen, A. C. Gossard, W. Wiegmann, T. H. Wood, and C. A. Burrus, “Band-edge electroabsorption in quantum well structures: the quantum-confined stark effect,” Phys. Rev. Lett.53(22), 2173–2176 (1984).
[CrossRef]

Cantwell, E. R.

W.-Y. Jang, M. M. Hayat, J. S. Tyo, R. S. Attaluri, T. E. Vandervelde, Y. D. Sharma, R. Shenoi, A. Stintz, E. R. Cantwell, S. C. Bender, S. J. Lee, S. K. Noh, and S. Krishna, “Demonstration of bias controlled algorithmic tuning of quantum dots in a well (DWELL) MidIR detectors,” IEEE J. Quantum Electron.45(6), 5537–5540 (2009).
[CrossRef]

Chemla, D. S.

D. A. B. Miller, D. S. Chemla, T. C. Damen, A. C. Gossard, W. Wiegmann, T. H. Wood, and C. A. Burrus, “Band-edge electroabsorption in quantum well structures: the quantum-confined stark effect,” Phys. Rev. Lett.53(22), 2173–2176 (1984).
[CrossRef]

Colonero, C.

M. G. Brown, J. Baker, C. Colonero, J. Costa, T. Gardner, M. Kelly, K. Schultz, B. Tyrrell, and J. Wey, “Digital-pixel focal plane array development,” Proc. SPIE7608, 76082H, 76082H-10 (2010).
[CrossRef]

Costa, J.

M. G. Brown, J. Baker, C. Colonero, J. Costa, T. Gardner, M. Kelly, K. Schultz, B. Tyrrell, and J. Wey, “Digital-pixel focal plane array development,” Proc. SPIE7608, 76082H, 76082H-10 (2010).
[CrossRef]

Damen, T. C.

D. A. B. Miller, D. S. Chemla, T. C. Damen, A. C. Gossard, W. Wiegmann, T. H. Wood, and C. A. Burrus, “Band-edge electroabsorption in quantum well structures: the quantum-confined stark effect,” Phys. Rev. Lett.53(22), 2173–2176 (1984).
[CrossRef]

Dowd, P.

Gardner, T.

M. G. Brown, J. Baker, C. Colonero, J. Costa, T. Gardner, M. Kelly, K. Schultz, B. Tyrrell, and J. Wey, “Digital-pixel focal plane array development,” Proc. SPIE7608, 76082H, 76082H-10 (2010).
[CrossRef]

Godoy, S. E.

Gossard, A. C.

D. A. B. Miller, D. S. Chemla, T. C. Damen, A. C. Gossard, W. Wiegmann, T. H. Wood, and C. A. Burrus, “Band-edge electroabsorption in quantum well structures: the quantum-confined stark effect,” Phys. Rev. Lett.53(22), 2173–2176 (1984).
[CrossRef]

Hamamoto, T.

T. Yasuda, T. Hamamoto, and K. Aizawa, “Adaptive-integration-time image sensor with real-time reconstruction function,” IEEE Trans. Electron. Dev.50(1), 111–120 (2003).
[CrossRef]

T. Hamamoto and K. Aizawa, “A computational image sensor with adaptive pixel-based integration time,” IEEE J. Solid-state Circuits36(4), 580–585 (2001).
[CrossRef]

Hayat, M. M.

W.-Y. Jang, M. M. Hayat, S. E. Godoy, S. C. Bender, P. Zarkesh-Ha, and S. Krishna, “Data compressive paradigm for multispectral sensing using tunable DWELL mid-infrared detectors,” Opt. Express19(20), 19454–19472 (2011).
[CrossRef] [PubMed]

W.-Y. Jang, M. M. Hayat, J. S. Tyo, R. S. Attaluri, T. E. Vandervelde, Y. D. Sharma, R. Shenoi, A. Stintz, E. R. Cantwell, S. C. Bender, S. J. Lee, S. K. Noh, and S. Krishna, “Demonstration of bias controlled algorithmic tuning of quantum dots in a well (DWELL) MidIR detectors,” IEEE J. Quantum Electron.45(6), 5537–5540 (2009).
[CrossRef]

B. Paskaleva, M. M. Hayat, Z. Wang, J. S. Tyo, and S. Krishna, “Canonical correlation feature selection for sensors with overlapping bands: theory and application,” IEEE T. Geo. Remote Sens.46(10), 3346–3358 (2008).
[CrossRef]

Ü. Sakoğlu, M. M. Hayat, J. S. Tyo, P. Dowd, S. Annamalai, K. T. Posani, and S. Krishna, “Statistical adaptive sensing by detectors with spectrally overlapping bands,” Appl. Opt.45(28), 7224–7234 (2006).
[CrossRef] [PubMed]

Ü. Sakoğlu, J. S. Tyo, M. M. Hayat, S. Raghavan, and S. Krishna, “Spectrally adaptive infrared photodetectors using bias-tunable quantum dots,” J. Opt. Soc. Am. B21(1), 7–17 (2004).
[CrossRef]

Jang, W.-Y.

W.-Y. Jang, M. M. Hayat, S. E. Godoy, S. C. Bender, P. Zarkesh-Ha, and S. Krishna, “Data compressive paradigm for multispectral sensing using tunable DWELL mid-infrared detectors,” Opt. Express19(20), 19454–19472 (2011).
[CrossRef] [PubMed]

W.-Y. Jang, M. M. Hayat, J. S. Tyo, R. S. Attaluri, T. E. Vandervelde, Y. D. Sharma, R. Shenoi, A. Stintz, E. R. Cantwell, S. C. Bender, S. J. Lee, S. K. Noh, and S. Krishna, “Demonstration of bias controlled algorithmic tuning of quantum dots in a well (DWELL) MidIR detectors,” IEEE J. Quantum Electron.45(6), 5537–5540 (2009).
[CrossRef]

Kelly, M.

M. G. Brown, J. Baker, C. Colonero, J. Costa, T. Gardner, M. Kelly, K. Schultz, B. Tyrrell, and J. Wey, “Digital-pixel focal plane array development,” Proc. SPIE7608, 76082H, 76082H-10 (2010).
[CrossRef]

Krishna, S.

W.-Y. Jang, M. M. Hayat, S. E. Godoy, S. C. Bender, P. Zarkesh-Ha, and S. Krishna, “Data compressive paradigm for multispectral sensing using tunable DWELL mid-infrared detectors,” Opt. Express19(20), 19454–19472 (2011).
[CrossRef] [PubMed]

W.-Y. Jang, M. M. Hayat, J. S. Tyo, R. S. Attaluri, T. E. Vandervelde, Y. D. Sharma, R. Shenoi, A. Stintz, E. R. Cantwell, S. C. Bender, S. J. Lee, S. K. Noh, and S. Krishna, “Demonstration of bias controlled algorithmic tuning of quantum dots in a well (DWELL) MidIR detectors,” IEEE J. Quantum Electron.45(6), 5537–5540 (2009).
[CrossRef]

B. Paskaleva, M. M. Hayat, Z. Wang, J. S. Tyo, and S. Krishna, “Canonical correlation feature selection for sensors with overlapping bands: theory and application,” IEEE T. Geo. Remote Sens.46(10), 3346–3358 (2008).
[CrossRef]

Ü. Sakoğlu, M. M. Hayat, J. S. Tyo, P. Dowd, S. Annamalai, K. T. Posani, and S. Krishna, “Statistical adaptive sensing by detectors with spectrally overlapping bands,” Appl. Opt.45(28), 7224–7234 (2006).
[CrossRef] [PubMed]

S. Krishna, “Quantum dots-in-a-well infrared photodetectors,” J. Phys. D Appl. Phys.38(13), 2142–2150 (2005).
[CrossRef]

Ü. Sakoğlu, J. S. Tyo, M. M. Hayat, S. Raghavan, and S. Krishna, “Spectrally adaptive infrared photodetectors using bias-tunable quantum dots,” J. Opt. Soc. Am. B21(1), 7–17 (2004).
[CrossRef]

S. Krishna, S. Raghavan, G. von Winckel, A. Stintz, G. Ariyawansa, S. G. Matsik, and A. G. U. Perera, “Three-color (λp1~3.8μm, λp2~8.5μm, λp3~23.2μm) InAs/InGaAs quantum-dots-in-a-well detector,” Appl. Phys. Lett.83(14), 2745–2747 (2003).
[CrossRef]

Lee, S. J.

W.-Y. Jang, M. M. Hayat, J. S. Tyo, R. S. Attaluri, T. E. Vandervelde, Y. D. Sharma, R. Shenoi, A. Stintz, E. R. Cantwell, S. C. Bender, S. J. Lee, S. K. Noh, and S. Krishna, “Demonstration of bias controlled algorithmic tuning of quantum dots in a well (DWELL) MidIR detectors,” IEEE J. Quantum Electron.45(6), 5537–5540 (2009).
[CrossRef]

Matsik, S. G.

S. Krishna, S. Raghavan, G. von Winckel, A. Stintz, G. Ariyawansa, S. G. Matsik, and A. G. U. Perera, “Three-color (λp1~3.8μm, λp2~8.5μm, λp3~23.2μm) InAs/InGaAs quantum-dots-in-a-well detector,” Appl. Phys. Lett.83(14), 2745–2747 (2003).
[CrossRef]

Miller, D. A. B.

D. A. B. Miller, D. S. Chemla, T. C. Damen, A. C. Gossard, W. Wiegmann, T. H. Wood, and C. A. Burrus, “Band-edge electroabsorption in quantum well structures: the quantum-confined stark effect,” Phys. Rev. Lett.53(22), 2173–2176 (1984).
[CrossRef]

Noh, S. K.

W.-Y. Jang, M. M. Hayat, J. S. Tyo, R. S. Attaluri, T. E. Vandervelde, Y. D. Sharma, R. Shenoi, A. Stintz, E. R. Cantwell, S. C. Bender, S. J. Lee, S. K. Noh, and S. Krishna, “Demonstration of bias controlled algorithmic tuning of quantum dots in a well (DWELL) MidIR detectors,” IEEE J. Quantum Electron.45(6), 5537–5540 (2009).
[CrossRef]

Paskaleva, B.

B. Paskaleva, M. M. Hayat, Z. Wang, J. S. Tyo, and S. Krishna, “Canonical correlation feature selection for sensors with overlapping bands: theory and application,” IEEE T. Geo. Remote Sens.46(10), 3346–3358 (2008).
[CrossRef]

Perera, A. G. U.

S. Krishna, S. Raghavan, G. von Winckel, A. Stintz, G. Ariyawansa, S. G. Matsik, and A. G. U. Perera, “Three-color (λp1~3.8μm, λp2~8.5μm, λp3~23.2μm) InAs/InGaAs quantum-dots-in-a-well detector,” Appl. Phys. Lett.83(14), 2745–2747 (2003).
[CrossRef]

Posani, K. T.

Raghavan, S.

Ü. Sakoğlu, J. S. Tyo, M. M. Hayat, S. Raghavan, and S. Krishna, “Spectrally adaptive infrared photodetectors using bias-tunable quantum dots,” J. Opt. Soc. Am. B21(1), 7–17 (2004).
[CrossRef]

S. Krishna, S. Raghavan, G. von Winckel, A. Stintz, G. Ariyawansa, S. G. Matsik, and A. G. U. Perera, “Three-color (λp1~3.8μm, λp2~8.5μm, λp3~23.2μm) InAs/InGaAs quantum-dots-in-a-well detector,” Appl. Phys. Lett.83(14), 2745–2747 (2003).
[CrossRef]

Sakoglu, Ü.

Schultz, K.

M. G. Brown, J. Baker, C. Colonero, J. Costa, T. Gardner, M. Kelly, K. Schultz, B. Tyrrell, and J. Wey, “Digital-pixel focal plane array development,” Proc. SPIE7608, 76082H, 76082H-10 (2010).
[CrossRef]

Sharma, Y. D.

W.-Y. Jang, M. M. Hayat, J. S. Tyo, R. S. Attaluri, T. E. Vandervelde, Y. D. Sharma, R. Shenoi, A. Stintz, E. R. Cantwell, S. C. Bender, S. J. Lee, S. K. Noh, and S. Krishna, “Demonstration of bias controlled algorithmic tuning of quantum dots in a well (DWELL) MidIR detectors,” IEEE J. Quantum Electron.45(6), 5537–5540 (2009).
[CrossRef]

Shenoi, R.

W.-Y. Jang, M. M. Hayat, J. S. Tyo, R. S. Attaluri, T. E. Vandervelde, Y. D. Sharma, R. Shenoi, A. Stintz, E. R. Cantwell, S. C. Bender, S. J. Lee, S. K. Noh, and S. Krishna, “Demonstration of bias controlled algorithmic tuning of quantum dots in a well (DWELL) MidIR detectors,” IEEE J. Quantum Electron.45(6), 5537–5540 (2009).
[CrossRef]

Stintz, A.

W.-Y. Jang, M. M. Hayat, J. S. Tyo, R. S. Attaluri, T. E. Vandervelde, Y. D. Sharma, R. Shenoi, A. Stintz, E. R. Cantwell, S. C. Bender, S. J. Lee, S. K. Noh, and S. Krishna, “Demonstration of bias controlled algorithmic tuning of quantum dots in a well (DWELL) MidIR detectors,” IEEE J. Quantum Electron.45(6), 5537–5540 (2009).
[CrossRef]

S. Krishna, S. Raghavan, G. von Winckel, A. Stintz, G. Ariyawansa, S. G. Matsik, and A. G. U. Perera, “Three-color (λp1~3.8μm, λp2~8.5μm, λp3~23.2μm) InAs/InGaAs quantum-dots-in-a-well detector,” Appl. Phys. Lett.83(14), 2745–2747 (2003).
[CrossRef]

Tyo, J. S.

W.-Y. Jang, M. M. Hayat, J. S. Tyo, R. S. Attaluri, T. E. Vandervelde, Y. D. Sharma, R. Shenoi, A. Stintz, E. R. Cantwell, S. C. Bender, S. J. Lee, S. K. Noh, and S. Krishna, “Demonstration of bias controlled algorithmic tuning of quantum dots in a well (DWELL) MidIR detectors,” IEEE J. Quantum Electron.45(6), 5537–5540 (2009).
[CrossRef]

B. Paskaleva, M. M. Hayat, Z. Wang, J. S. Tyo, and S. Krishna, “Canonical correlation feature selection for sensors with overlapping bands: theory and application,” IEEE T. Geo. Remote Sens.46(10), 3346–3358 (2008).
[CrossRef]

Ü. Sakoğlu, M. M. Hayat, J. S. Tyo, P. Dowd, S. Annamalai, K. T. Posani, and S. Krishna, “Statistical adaptive sensing by detectors with spectrally overlapping bands,” Appl. Opt.45(28), 7224–7234 (2006).
[CrossRef] [PubMed]

Ü. Sakoğlu, J. S. Tyo, M. M. Hayat, S. Raghavan, and S. Krishna, “Spectrally adaptive infrared photodetectors using bias-tunable quantum dots,” J. Opt. Soc. Am. B21(1), 7–17 (2004).
[CrossRef]

Tyrrell, B.

M. G. Brown, J. Baker, C. Colonero, J. Costa, T. Gardner, M. Kelly, K. Schultz, B. Tyrrell, and J. Wey, “Digital-pixel focal plane array development,” Proc. SPIE7608, 76082H, 76082H-10 (2010).
[CrossRef]

Vandervelde, T. E.

W.-Y. Jang, M. M. Hayat, J. S. Tyo, R. S. Attaluri, T. E. Vandervelde, Y. D. Sharma, R. Shenoi, A. Stintz, E. R. Cantwell, S. C. Bender, S. J. Lee, S. K. Noh, and S. Krishna, “Demonstration of bias controlled algorithmic tuning of quantum dots in a well (DWELL) MidIR detectors,” IEEE J. Quantum Electron.45(6), 5537–5540 (2009).
[CrossRef]

von Winckel, G.

S. Krishna, S. Raghavan, G. von Winckel, A. Stintz, G. Ariyawansa, S. G. Matsik, and A. G. U. Perera, “Three-color (λp1~3.8μm, λp2~8.5μm, λp3~23.2μm) InAs/InGaAs quantum-dots-in-a-well detector,” Appl. Phys. Lett.83(14), 2745–2747 (2003).
[CrossRef]

Wang, Z.

B. Paskaleva, M. M. Hayat, Z. Wang, J. S. Tyo, and S. Krishna, “Canonical correlation feature selection for sensors with overlapping bands: theory and application,” IEEE T. Geo. Remote Sens.46(10), 3346–3358 (2008).
[CrossRef]

Wey, J.

M. G. Brown, J. Baker, C. Colonero, J. Costa, T. Gardner, M. Kelly, K. Schultz, B. Tyrrell, and J. Wey, “Digital-pixel focal plane array development,” Proc. SPIE7608, 76082H, 76082H-10 (2010).
[CrossRef]

Wiegmann, W.

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Figures (12)

Fig. 1
Fig. 1

Bias-tunable spectral responses of the DWELL photodetector at 60K device temperature by varying applied biases in the range from −3 to 3 V.

Fig. 2
Fig. 2

Approximation of a continuous time-varying biasing waveform (solid black line) by the discretization (blue shaded region) with a constant interval Δt within the total integration time α.

Fig. 3
Fig. 3

Illustration of a continuous time-varying biasing waveform (blue shaded region) obtained by the GST algorithm using the adjusted integration time bi within the total integration time τt).

Fig. 4
Fig. 4

Desired triangular narrowband tuning filter, r(λ;λn) with λn = 8.8 μm, whose transmittance is shown by the dashed line. Transmittance of algorithmic tuning filter, r ^ (λ; λ n ) , as shown in solid black line, was obtained by the ST algorithm [57] using the minimal set of four biases, {-3.0, −0.8, 1.0, 2.8 V} identified by the MBS selection algorithm reported in [8]. The algorithmic tuning filter r ^ (λ; λ n ) is implemented via post processing (without using any physical spectral filters) to reconstruct sample of the emissivity of an object (in red) at λn = 8.8 μm.

Fig. 5
Fig. 5

Transmittances of three algorithmic spectral matched filters [8], r ^ (λ; λ 1 ) (left), r ^ (λ; λ 2 ) (middle) and r ^ (λ; λ 3 ) (right) in solid black line were obtained by the ST algorithm using same minimal set of four biases, {-3.0, −0.8, 1.0, 2.8 V}. Transmittances of actual spectral filters, r1(λ;λ1), r2(λ;λ2) and r3(λ;λ3) are shown in dashed line. These three algorithmic matched filters are used to classify the test object, r1(λ;λ1).

Fig. 6
Fig. 6

Time-varying biasing waveform obtained by the GST algorithm for the spectrometry problem. This bias waveform consists of negative waveform (shown in red) and positive waveform (shown in blue), which are used to integrate photocurrents. Inset shows the negative and positive signs of weights over the integration time.

Fig. 7
Fig. 7

Integrated photocurrents, I ^ neg and I ^ pos , based on negative waveform (left) and positive waveform (right). Subtraction of I ^ neg from I ^ pos gives a reconstruction of the emissivity of an object sampled at 8.8 μm using the spectral filter.

Fig. 8
Fig. 8

Three bias waveforms each including negative (in red) and positive (in blue) waveforms for three matched filters, (a) r ^ (λ; λ 1 ) , (b) r ^ (λ; λ 2 ) and (c) r ^ (λ; λ 3 ) . Inset shows the negative and positive signs of weights over the integration time.

Fig. 9
Fig. 9

Transmittances of three algorithmic spectral matched filters, r ^ (λ; λ 1 ) (left), r ^ (λ; λ 2 ) (middle) and r ^ (λ; λ 3 ) (right) in solid black line were obtained by the GST algorithm using the bias waveforms as shown in Fig. 8. Actual filter transmittances, r1(λ;λ1) (left), r2(λ;λ2) (middle) and r3(λ;λ3) (right) are shown in dashed line.

Fig. 10
Fig. 10

Integrated photocurrents, I ^ neg, class (from red curve) and I ^ pos, class (from blue curve) for (a) Class 1, (b) Class 2 and (c) Class 3 based on the bias waveforms as shown in Fig. 8.

Fig. 11
Fig. 11

Classification results for the GST algorithm (blue) compared to the conventional ST algorithm (white) for identifying the test filter object, r1(λ;λ1). Results show that the classifier has successfully classified the test object to Class 1 using both algorithms.

Fig. 12
Fig. 12

Functional representation of bidirectional integrator: (a) The input photocurrent charges the integrator capacitor, and (b) the input photocurrent discharges the integrator capacitor.

Tables (2)

Tables Icon

Table 1 Comparison of reconstructed emissivity at 8.8 μm between the conventional ST algorithm and the GST algorithm. Results are also compared to the true value of the emissivity.

Tables Icon

Table 2 Summary of results for the effect of nonuniformity noise to reconstruct the emissivity of the LWIR object at 8.8 μm. Results are also compared to the reference value of the emissivity. Reconstruction errors as compared to the reference value are shown in parentheses.

Equations (12)

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I k =q[ Ω λ min λ max e(λ,T) M p (λ,T) R k (λ) τ filt (λ) τ window (λ)dλ ] A det + N k ,
I k =C λ min λ max e(λ) R k (λ)dλ + N k ,
w n = [ A T A+Φ+α A T Q T QA] 1 [ A T r(λ; λ n )],
SNR k = I k σ N,k
I ^ = i=1 m w i I i .
f ^ = i=1 k w i R B i (f) (λ)
I ^ = 0 α w f (t) I B(f) (t) dt,
I ^ = 0 α I B ^ (f) (t)dt ,
w ^ i = w i min i=1,...k | w i | .
τ(Δt)= i=1 k b i =Δt i=1 k | w ^ i | ,
t * =sup{Δt:(1ε)ατ(Δt)α},
R ˜ k (λ)= R k (λ)×ρ at the k th bias,

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