Source: http://aoot.osa.org/ao/abstract.cfm?uri=ao-57-21-6017
Timestamp: 2019-04-26 05:43:49+00:00

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We present a theoretical evaluation of a subterahertz (subTHz) system to image through a scattering medium composed of scatterers of sizes close to the wavelength. We specifically study the case of sand grain clouds created by helicopter rotor airflow during landing in arid areas. The different powers received by one pixel of a matrix made of subTHz sensors are identified. Photometric and antenna-based sensors are considered. Besides the thermal contribution to the noise, we focus our attention on the radiation backscattered by the brownout. It appears that a configuration where the source and the camera are distant is the most promising configuration and is realistic for embedded systems.
A. Davis, “The use of commercial remote sensing predicting helicopter brownout conditions,” Master’s thesis (Naval Postgraduate School, 2007), http://www.dtic.mil/dtic/tr/fulltext/u2/a473870.pdf .
D. A. Wachspress, G. R. Whitehouse, J. D. Keller, K. Yu, P. Gilmore, M. Dorsett, and K. McClure, “A high fidelity brownout model for real-time flight simulations and trainers,” presented at the American Helicopter Society 65th Annual Forum, Grapevine, Texas, 2009.
B. A. Swanson, “Investigating the impacts of particle size and wind speed on brownout,” Master’s thesis (Air Force Institute of Technology, 2015), http://www.dtic.mil/dtic/tr/fulltext/u2/a614925.pdf .
R. C. Allen, W. B. Blanton, E. Schramm, and R. Mitra, “Strategies for reducing SWAP-C and complexity in DVE sensor systems,” Proc. SPIE 10197, 101970M (2017).
A. Stambler, S. Spiker, M. Bergerman, and S. Singh, “Toward autonomous rotorcraft flight in degraded visual environments: experiments and lessons learned,” Proc. SPIE 9839, 983904 (2016).
S. T. Fiorino, P. M. Grice, M. J. Krizo, R. J. Bartell, J. D. Haiducek, and S. J. Cusumano, “Lab measurements to support modeling terahertz propagation in brownout conditions,” Proc. SPIE 7671, 76710W (2010).
M. Hagelen, G. Briese, H. Essen, T. Bertuch, P. Knott, and A. Tessmann, “A millimetrewave landing aid approach for helicopters under brown-out conditions,” in IEEE Radar Conference (IEEE, 2008), pp. 1–4.
H. O. Everitt, W. D. Caraway, and J. T. Richard, “Terahertz (THz) radar: a solution for degraded visibility environments (DVE),” (Army Research, Development and Engineering Command Redstone Arsenal United States, 2016).
T. E. Dillon, C. A. Schuetz, R. D. Martin, D. G. Mackrides, S. Shi, P. Yao, K. Shreve, C. Harrity, and D. W. Prather, “Passive, real-time millimeter wave imaging for degraded visual environment mitigation,” Proc. SPIE 9471, 947103 (2015).
A. Wright, R. Martin, C. Schuetz, S. Shi, Y. Zhang, P. Yao, K. Shreve, T. E. Dillon, D. G. Mackrides, C. E. Harrity, and D. W. Prather, “Module integration and amplifier design optimization for optically enabled passive millimeter-wave imaging,” Proc. SPIE 9830, 98300C (2016).
S. Sarkozy, J. Drewes, K. M. Leong, R. Lai, X. G. Mei, W. Yoshida, M. D. Lange, J. Lee, and W. R. Deal, “Amplifier based broadband pixel for sub-millimeter wave imaging,” Opt. Eng. 51, 091602 (2012).
V. Radisic, K. Leong, C. Zhang, K. K. Loi, and S. Sarkozy, “Demonstration of a micro-integrated sub-millimeter-wave pixel,” IEEE Trans. Microwave Theory Tech. 61, 2949–2955 (2013).
M. I. B. Shams, Z. Jiang, S. Rahman, J. Qayyum, L. J. Cheng, H. G. Xing, P. Fay, and L. Liu, “Approaching real-time terahertz imaging with photo-induced coded apertures and compressed sensing,” Electron. Lett. 50, 801–803 (2014).
C. A. Schuetz, E. L. Stein, J. Samluk, D. Mackrides, J. P. Wilson, R. D. Martin, T. E. Dillon, and D. W. Prather, “Studies of millimeter-wave phenomenology for helicopter brownout mitigation,” Proc. SPIE 7485, 74850F, 2009.
D. Wikner, “Millimeter-wave propagation through a controlled dust environment,” Proc. SPIE 6548, 654803 (2007).
R. Ceolato, B. Tanguy, C. Martin, T. Huet, P. Chervet, G. Durand, N. Riviere, L. Hespel, N. Diakonova, D. But, W. Knap, J. Meilhan, B. Delplanque, J. Oden, and F. Simoens, “Performance evaluation of active sub-terahertz systems in degraded visual environments (DVE),” Proc. SPIE 9839, 983906 (2016).
C. Phillips, Computational Study of Rotorcraft Aerodynamics in Ground Effect and Brownout (Defense Advanced Research Projects Agency, 2010).
K. Sudhakar and M. V. Subramanyam, “Evaluation of atmospheric attenuation due to various parameters,” in International Conference on Information Communication and Embedded Systems (ICICES) (IEEE, 2013), pp. 609–612.
K. Sudhakar and M. Subramanyam, “Propagation power loss analysis and evaluation under variant atmospheric conditions,” Glob. J. Res. Eng. 13, 17–20 (2013).
R. Ceolato, N. Diakonova, J. Meilhan, and W. Knap, “Determination of the sub-terahertz attenuation of brownout clouds generated by rotorcraft,” in 42nd International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz) (IEEE, 2017), pp. 1–2.
S. L. Marek, “A computational tool for evaluating THz imaging performance in brownout conditions at land sites throughout the world,” Master’s thesis (Air Force Institute of Technology, 2009), http://www.dtic.mil/dtic/tr/fulltext/u2/a494962.pdf .
S. T. Fiorino, R. J. Bartell, M. J. Krizo, S. L. Marek, M. J. Bohn, R. M. Randall, and S. J. Cusumano, “A computational tool for evaluating THz imaging performance in brownout or whiteout conditions at land sites throughout the world,” Proc. SPIE 7324, 732410 (2009).
V. Belov, “Statistical modeling of imaging process in active night vision systems with gate-light detection,” Appl. Phys. B 75, 571–576 (2002).
V. V. Belov, V. N. Abramochkin, Y. V. Gridnev, A. N. Kudryavtsev, V. S. Kozlov, R. F. Rakhimov, V. P. Shmargunov, and M. V. Tarasenkov, “Experimental study of the influence of optical characteristics of a medium on the image quality in optoelectronic systems with backscattered noise signal selection,” Atmos. Ocean. Opt. 30, 429–434 (2017).
J. M. Hammersley and D. C. Handscomb, Monte Carlo Methods (Chapman & Hall, 1964).
G. S. Fishman, Monte Carlo Concepts, Algorithms and Applications (Springer-Verlag, 1996).
Radiocommunication Sector ITU, “Recommendation ITU-R P. 676–11: attenuation by atmospheric gases,” (International Telecommunication Union, 2016).
C. Cowherd, “Sandblaster 2 support of see-through technologies for particulate brownout,” (Midwest Research Institute, 2007).
H. van de Hulst, Light Scattering by Small Particles (Dover Publications, 1981).
H. Koschmieder, “Measurements of visibility at Danzig,” Mon. Weather Rev. 58, 439–444 (1930).
W. E. K. Middleton, Vision Through the Atmosphere (Springer Berlin Heidelberg, 1957), pp. 254–287.
D. W. Prather, N. Alexander, R. Appleby, C. Callejero, R. Gonzalo, D. Nötel, N. Salmon, B. Wallace, M. Peichl, and C. Schuetz, “High-performance passive/active radiometric mmw imaging using thinned arrays (set-135),” (NATO, 2015).
F. Taillade, E. Belin, and E. Dumont, “An analytical model for backscattered luminance in fog: comparisons with Monte Carlo computations and experimental results,” Meas. Sci. Technol. 19, 055302 (2008).
A. Marshak and A. Davis, 3D Radiative Transfer in Cloudy Atmospheres (Springer, 2005), Chap. 3, p. 213.
Fig. 1. Schematic view of the active imaging system. The source of half-aperture θ0 illuminates the scene that is located at a distance D+z0 from the imaging system. The detection system consists in a matrix of pixels located in the image plane of the optical system, which pupil is located at z=0. The half-aperture of one pixel is θr. Only the pixel centered on the optical axis is represented. The distance between the axes of the source and the optical system is ds−d. The brownout is in contact with the ground, and its thickness is D. The volume from which the backscattered noise hails is shown in green. It is the intersection between the cones of illumination and detection.
Fig. 2. Distribution of brownout particle density with respect to particles’ radii for a large military helicopter .
Fig. 3. Scattering efficiencies for three frequencies (94 GHz, 0.35 THz, and 0.94 THz) for silica spheres with index of refraction of 1.96.
Fig. 4. Scattering and extinction mean free paths for a brownout made of silica spheres deduced from Eqs. (1) and (2) and Mie scattering model for a brownout distribution shown in Fig. 2.
Fig. 5. Radiance of the backscattered signal—comparison between Monte Carlo simulation (+ and ×) and analytical model (○ and □). Parameters: P0=1 W, ds−c=0, D=30 m, Ag=0.1. (a) Varying θ0 (z0=3 m) 0.28%≤ϵ≤7%; (b) varying z0 (θ0=25°) 0.28%≤ϵ≤8%.
Fig. 6. Radiance of the backscattered noise—comparison between Monte Carlo simulations (+ and ×) and analytical model (○ and □). Parameters: P0=1 W, ds-c=0, D=30 m, Ag=0.1. (a) Varying θ0 (z0=3 m) 0.18%≤ϵ≤38%; (b) varying z0 (θ0=25°) 0.18%≤ϵ≤27%.
Fig. 7. Radiance of the ground, Lg, and the sky, Lsky, per hertz with respect to the frequency.
Fig. 8. Power balance for (a) a photometric pixel and (b) an antenna. The backscattered signal, the backscattered noise, and the thermal noise are, respectively, represented with +, ×, and ∗. Parameters: P0=1 W, θ0=25°, z0=3 m, ds-c=0, p=570 μm, Δf=1 GHz.
Fig. 9. Comparison of the contrasts between a monostatic (ds-c=0, +) and a bistatic (ds-c=1 m, ×) system and for two values of z0. Parameters: V=30 m, D=30 m, P0=1 W, θ0=25°, p=570 μm. (a) z0=0. (b) z0=3 m.
Fig. 10. Comparison of the contrasts between a monostatic (ds-c=0, +) and a bistatic (ds-c=1 m, ×) system and for two values of z0. Parameters: V=10 m, D=30 m, P0=1 W, θ0=25°, p=570 μm. (a) z0=0. (b) z0=3 m.
(B5) Ls(r,u^)=Gs(−u^)P04π|r|2 cos θu^ exp(−|r|ℓtot)δ(u^+r|r|).
(D5) Sd(r,u^)=p(−r^→u^)4πℓscaGs(r^)P04π|r|2 cos θ−r^ exp(−|r|ℓtot).

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