Abstract

The U.S. Army Night Vision and Electronic Sensors Directorate (NVESD) and the U.S. Army Research Laboratory have developed a terahertz (THz) -band imaging system performance model for detection and identification of concealed weaponry. The MATLAB-based model accounts for the effects of all critical sensor and display components and for the effects of atmospheric attenuation, concealment material attenuation, and active illumination. The model is based on recent U.S. Army NVESD sensor performance modeling technology that couples system design parameters to observer–sensor field performance by using the acquire methodology for weapon identification performance predictions. This THz model has been developed in support of the Defense Advanced Research Project Agencies’ Terahertz Imaging Focal-Plane Technology (TIFT) program and is currently being used to guide the design and development of a 0.650THz active–passive imaging system. This paper will describe the THz model in detail, provide and discuss initial modeling results for a prototype THz imaging system, and outline plans to calibrate and validate the model through human perception testing.

© 2008 Optical Society of America

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References

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  1. W. R. Tribe, D. A. Newnham, P. F. Taday, and M. C. Kemp, “Hidden object detection: security applications of terahertz technology,” Proc. SPIE 5354, 168-176 (2004).
    [Crossref]
  2. C. Baker, W. R. Tribe, T. Lo, B. E. Cole, S. Chandler, and M.C. Kemp, “People screening using terahertz technology,” Proc. SPIE 5790, 1-10 (2005).
    [Crossref]
  3. M. C. Kemp, P. F. Taday, B. E. Cole, J. A. Cluff, A. J. Fitzgerald, and W. R. Tribe, “Security applications of terahertz technology,” Proc. SPIE 5070, 44-52 (2003).
    [Crossref]
  4. D. Zimdars, “Fiber-pigtailed terahertz time domain spectroscopy instrumentation for package inspection and security imaging,” Proc. SPIE 5070, 108-116 (2003).
    [Crossref]
  5. F. C. De Lucia,“THz + X--A search for new approaches to significant problems,” Proc. SPIE 5790, 219-230 (2005).
    [Crossref]
  6. T. W. Crowe, D. W. Porterfield, J. L. Hesler, W. L. Bishop, D. S. Kurtz, and K. Hui, “Terahertz sources and detectors,” Proc. SPIE 5790, 271-280 (2005).
    [Crossref]
  7. MATLAB is a mathematical engineering software product of Mathworks, Inc. (Natick, Mass.)
  8. P. G. J. Barten, “Evaluation of subjective image quality with the square-root integral method.” J. Opt. Soc. Am. A 7, 2024-2031 (1990).
    [Crossref]
  9. R. Vollmerhausen, “Incorporating display limitations into night vision performance models,” in Proceedings of the 1995 Meeting of the Infrared Information Symposium (IRIS) Specialty Group on Passive Sensors (Infrared Information Analysis Center, 1995) Vol. 2, pp. 11-31.
  10. NVTherm, www.ontar.com.
  11. P. G. J. Barten, Contrast Sensitivity of the Human Eye and Its Effects on Image Quality (SPIE, 1999).
    [Crossref]
  12. J. Johnson, “Analysis of image forming systems,” in Proceedings of the Image Intensifier Symposium (Warfare Electrical Engineering Department, U.S. Army Research and Development Laboratories, 1958), pp. 249- 273.
  13. R. H. Vollmerhausen, E. L. Jacobs, and R. G. Driggers, “New metric for predicting target acquisition performance,” Proc. SPIE 5076, 28-40, 2003.
    [Crossref]
  14. G. D. Boreman, Basic Electo-Optics for Electrical Engineers (SPIE, 1998), pp. 23-30.
    [Crossref]
  15. R. H. Vollmerhausen and R. G. Driggers, Analysis of Sampled Imaging Systems (SPIE, 2000), Chap. 2.
    [Crossref]
  16. J. W. Goodman, Introduction to Fourier Optics (McGraw Hill, 1996), Chap. 2.
  17. W. C. Jakes Jr., “Gain of electromagnetic horns,” Proc. IRE , 39, 160-162 (1951).
    [Crossref]
  18. R. H. Vollmerhausen and E. L. Jacobs, “The Targeting Task Performance (TTP) Metric: A New Model for Predicting Target Acquisition Performance,” AMSEL-NV-TR-230 (U.S. Army Night Vision and Electronic Sensors Directorate, 2004), pp. 29-40, 66.
  19. F. T.Ulaby, R. K. Moore, and A. K. Fung, in Microwave Remote Sensing: Active and Passive (Addison-Wesley, 1982), Vol. 2, pp. 457-463.
  20. http://www.virginiadiodes.com/.

2005 (3)

C. Baker, W. R. Tribe, T. Lo, B. E. Cole, S. Chandler, and M.C. Kemp, “People screening using terahertz technology,” Proc. SPIE 5790, 1-10 (2005).
[Crossref]

F. C. De Lucia,“THz + X--A search for new approaches to significant problems,” Proc. SPIE 5790, 219-230 (2005).
[Crossref]

T. W. Crowe, D. W. Porterfield, J. L. Hesler, W. L. Bishop, D. S. Kurtz, and K. Hui, “Terahertz sources and detectors,” Proc. SPIE 5790, 271-280 (2005).
[Crossref]

2004 (1)

W. R. Tribe, D. A. Newnham, P. F. Taday, and M. C. Kemp, “Hidden object detection: security applications of terahertz technology,” Proc. SPIE 5354, 168-176 (2004).
[Crossref]

2003 (3)

R. H. Vollmerhausen, E. L. Jacobs, and R. G. Driggers, “New metric for predicting target acquisition performance,” Proc. SPIE 5076, 28-40, 2003.
[Crossref]

M. C. Kemp, P. F. Taday, B. E. Cole, J. A. Cluff, A. J. Fitzgerald, and W. R. Tribe, “Security applications of terahertz technology,” Proc. SPIE 5070, 44-52 (2003).
[Crossref]

D. Zimdars, “Fiber-pigtailed terahertz time domain spectroscopy instrumentation for package inspection and security imaging,” Proc. SPIE 5070, 108-116 (2003).
[Crossref]

1990 (1)

1951 (1)

W. C. Jakes Jr., “Gain of electromagnetic horns,” Proc. IRE , 39, 160-162 (1951).
[Crossref]

J. Opt. Soc. Am. A (1)

Proc. IRE (1)

W. C. Jakes Jr., “Gain of electromagnetic horns,” Proc. IRE , 39, 160-162 (1951).
[Crossref]

Proc. SPIE (7)

R. H. Vollmerhausen, E. L. Jacobs, and R. G. Driggers, “New metric for predicting target acquisition performance,” Proc. SPIE 5076, 28-40, 2003.
[Crossref]

W. R. Tribe, D. A. Newnham, P. F. Taday, and M. C. Kemp, “Hidden object detection: security applications of terahertz technology,” Proc. SPIE 5354, 168-176 (2004).
[Crossref]

C. Baker, W. R. Tribe, T. Lo, B. E. Cole, S. Chandler, and M.C. Kemp, “People screening using terahertz technology,” Proc. SPIE 5790, 1-10 (2005).
[Crossref]

M. C. Kemp, P. F. Taday, B. E. Cole, J. A. Cluff, A. J. Fitzgerald, and W. R. Tribe, “Security applications of terahertz technology,” Proc. SPIE 5070, 44-52 (2003).
[Crossref]

D. Zimdars, “Fiber-pigtailed terahertz time domain spectroscopy instrumentation for package inspection and security imaging,” Proc. SPIE 5070, 108-116 (2003).
[Crossref]

F. C. De Lucia,“THz + X--A search for new approaches to significant problems,” Proc. SPIE 5790, 219-230 (2005).
[Crossref]

T. W. Crowe, D. W. Porterfield, J. L. Hesler, W. L. Bishop, D. S. Kurtz, and K. Hui, “Terahertz sources and detectors,” Proc. SPIE 5790, 271-280 (2005).
[Crossref]

Other (11)

MATLAB is a mathematical engineering software product of Mathworks, Inc. (Natick, Mass.)

R. Vollmerhausen, “Incorporating display limitations into night vision performance models,” in Proceedings of the 1995 Meeting of the Infrared Information Symposium (IRIS) Specialty Group on Passive Sensors (Infrared Information Analysis Center, 1995) Vol. 2, pp. 11-31.

NVTherm, www.ontar.com.

P. G. J. Barten, Contrast Sensitivity of the Human Eye and Its Effects on Image Quality (SPIE, 1999).
[Crossref]

J. Johnson, “Analysis of image forming systems,” in Proceedings of the Image Intensifier Symposium (Warfare Electrical Engineering Department, U.S. Army Research and Development Laboratories, 1958), pp. 249- 273.

G. D. Boreman, Basic Electo-Optics for Electrical Engineers (SPIE, 1998), pp. 23-30.
[Crossref]

R. H. Vollmerhausen and R. G. Driggers, Analysis of Sampled Imaging Systems (SPIE, 2000), Chap. 2.
[Crossref]

J. W. Goodman, Introduction to Fourier Optics (McGraw Hill, 1996), Chap. 2.

R. H. Vollmerhausen and E. L. Jacobs, “The Targeting Task Performance (TTP) Metric: A New Model for Predicting Target Acquisition Performance,” AMSEL-NV-TR-230 (U.S. Army Night Vision and Electronic Sensors Directorate, 2004), pp. 29-40, 66.

F. T.Ulaby, R. K. Moore, and A. K. Fung, in Microwave Remote Sensing: Active and Passive (Addison-Wesley, 1982), Vol. 2, pp. 457-463.

http://www.virginiadiodes.com/.

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Figures (10)

Fig. 1
Fig. 1

Imaging system relationships.

Fig. 2
Fig. 2

Performance model architecture. Note that the task difficulty factor(s) are determined independently through human perception testing.

Fig. 3
Fig. 3

Relationship between system CTF, limiting frequency, and excess contrast.

Fig. 4
Fig. 4

Illustration of the formal, horn-antenna radiation transfer process: illustration of (a) the numerical correlation (outer curve) of the source beam (middle curve) with the target reflectance (inner curve), and (b) the return irradiance across a 12 in . focusing mirror (upper curve) and the weighting of that irradiance by the pattern of a 22 dB gain receiver–detector horn antenna (lower curve). The power received by the detector is the integration of the product of the two functions.

Fig. 5
Fig. 5

Illustration of the present radiometric model for active target–background illumination. Note that the input aperture is that of either a lens or a mirror focusing element.

Fig. 6
Fig. 6

Example graphical output from the MATLAB-based imaging system performance model.

Fig. 7
Fig. 7

ID range performance as a function of (a) aperture size (f-number), (b) target-to-background contrast ratio.

Fig. 8
Fig. 8

Probability of ID versus range results using a horn output antenna: atmospheric attenuation set to (a)  30.0 dB/km , (b)  60.0 dB/km .

Fig. 9
Fig. 9

Probability of ID versus range results using a collimated output beam: detector integration time set to (a)  10 ms , (b)  52 μ s . In (b) an entire image frame could be captured in 1 s .

Fig. 10
Fig. 10

Probability of ID versus range results using a scene-collimated, active-illumination output beam: detector integration time set to (a)  10 ms , (b)  1 s .

Tables (2)

Tables Icon

Table 1 Summary of Active-Illumination Radiometric Results

Tables Icon

Table 2 Summary of Passive-Emission Radiometric Results

Equations (31)

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CTF eye ( f ) = ( a f e b f 1 + c e b f ) 1 ,
a = 540 ( 1 + 0.7 L ) 0.2 1 + 12 w ( 1 + f 3 ) 2 ,
b = 0.3 ( 1 + 100 L ) 0.15 ,
CTF sys ( f ) = CTF eye ( f ) H sys ( f ) [ 1 + α 2 σ 2 ( f ) L 2 ] 1 / 2 ,
σ 2 ( f ) = S n ( ξ ) | H Post ( ξ ) H Per ( ξ , f ) | 2 d ξ ,
H Per ( ξ , f ) = exp [ 2.2 log 2 ( ξ f ) ] ,
TTP = f lo f limit C t CTF sys ( f ) d f ,
CTF sys ( f ) | f lo , f limit = C t  , f limit > f lo .
V ( R ) = A t R TTP ,
P task = ( V ( R ) V 50 ( task ) ) E { 1 + ( V ( R ) V 50 ( task ) ) E } ,
E = 1.51 + 0.24 ( V ( R ) V 50 ) .
H diff ( ξ ) = 2 π { cos 1 ( ξ ξ cut ) ( ξ ξ cut ) [ 1 ( ξ ξ cut ) 2 ] 1 / 2 } , ξ ξ cut ,
ξ cut = D ap / ( λ × 1000 ) .
H det _ sp ( ξ ) = sinc ( DAS x ξ ) ,
sinc ( π x ) = sin ( π x ) / π x ,
H det _ sp ( ρ ) = 2 J 1 ( 2 π ρ r ) 2 π ρ r ,
A eff = G max λ 2 4 π ,
H disp ( ξ ) = sinc ( X angle ξ ) ,
H disp ( ξ ) = Gaus ( σ angle ξ ) ,
S n = ( NEP det ) 2 P sp _ bw ,
L = P det _ IFOV η ant ,
t scale = t eye t act ,
t eye = 0.0192 + 0.0633 ( L ) 0.17
E tgt _ plane = P source τ atm τ obsc A i ,
A i ( R ) = π ( α 2 × R + B d 2 ) 2 ,
P refl = E tgt _ plane A do ( R ) R normal ,
A do ( R ) = π ( IFOV 2 R ) 2 ,
E aperture = P refl × τ atm × τ obsc 4 π R 2 × Gain   ,
Gain = 4 π Ω refl
P det _ IFOV = E aperture × A aperture × τ aperture ,
Contrast image = | P det _ IFOV ( Target ) - P det _ IFOV ( Background ) | P det _ IFOV ( Target ) + P det _ IFOV ( Background ) .

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