Aircraft vulnerability analysis by modeling and simulation

Willers, Cornelius J.; Willers, Maria S.; Waal, Alta de

doi:10.1117/12.2073751

Cited by 7 publications

(4 citation statements)

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“…However, the study on the radiation signature difference of stealth aircraft over various spectrum ranges is minimal. Many studies have focused on several specific broad-spectrums, such as 1.8~2.4μm, 2.5~3.57μm, 4~4.76μm, etc., covering two aircraft plume peak spectra along with the skin reflection radiation spectra that has high atmospheric transmittance (Willers, C. J. et al 2014;Pan, X. et al 2015;Mahulikar, S. P. et al 2015;Wang, Y. et al 2016;Gu, B. et al 2017;. The results show that the above spectra can make significant contributions to aircraft detection.…”

Section: Introductionmentioning

confidence: 83%

Detection spectrum optimization of stealth aircraft targets from a space-based infrared platform

et al. 2022

Opt Quant Electron

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Advances in infrared detection techniques require novel spectrum dynamicmodification strategies capable of sensing unprecedentedly low target radiant intensities. A conventional fixed-spectrum detection system cannot satisfy the effective detection of stealth aircraft targets due to complex Earth background clutter and atmospheric attenuation. Therefore, a detection method that can highlight aircraft targets is urgently needed to enhance stealth aircraft detectability. In this research, a spectrum set consisting of different bandwidths associated with a central wavelength is established. Furthermore, a signal-to-noise ratio of the stealth aircraft is computed using the established spectrum set. Finally, the optimal spectrum is selected according to the maximal signal-to-noise ratio from the spectrum set. Our numerical experiments and simulations further demonstrate that the proposed methodology can substantially strengthen the detection performance of stealth aircraft compared with traditional fixed-spectrum detection systems. This work on detection spectrum optimization paves the way to stealth aircraft detection and opens new vistas in the field of target detection technology.

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Section: Introductionmentioning

confidence: 83%

Detection spectrum optimization of stealth aircraft targets from a space-based infrared platform

et al. 2022

Opt Quant Electron

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“…Each polygon is assigned spectral radiometric properties, temporally variable spatial texture properties and radiometric properties. Polygons can also be partially transparent to represent gas clouds, countermeasure flares or aircraft plumes [13][14][15][16].…”

Section: Optronic Scene Simulator (Ossim)mentioning

confidence: 99%

An End-to-End Hyperspectral Scene Simulator with Alternate Adjacency Effect Models and Its Comparison with CameoSim

et al. 2019

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In this research, we developed a new rendering-based end to end Hyperspectral scene simulator CHIMES (Cranfield Hyperspectral Image Modelling and Evaluation System), which generates nadir images of passively illuminated 3-D outdoor scenes in Visible, Near Infrared (NIR) and Short-Wave Infrared (SWIR) regions, ranging from 360 nm to 2520 nm. MODTRAN TM (MODerate resolution TRANsmission), is used to generate the sky-dome environment map which includes sun and sky radiance along with the polarisation effect of the sky due to Rayleigh scattering. Moreover, we perform path tracing and implement ray interaction with medium and volumetric backscattering at rendering time to model the adjacency effect. We propose two variants of adjacency models, the first one incorporates a single spectral albedo as the averaged background of the scene, this model is called the Background One-Spectra Adjacency Effect Model (BOAEM), which is a CameoSim like model created for performance comparison. The second model calculates background albedo from a pixel’s neighbourhood, whose size depends on the air volume between sensor and target, and differential air density up to sensor altitude. Average background reflectance of all neighbourhood pixel is computed at rendering time for estimating the total upwelled scattered radiance, by volumetric scattering. This model is termed the Texture-Spectra Incorporated Adjacency Effect Model (TIAEM). Moreover, for estimating the underlying atmospheric condition MODTRAN is run with varying aerosol optical thickness and its total ground reflected radiance (TGRR) is compared with TGRR of known in-scene material. The Goodness of fit is evaluated in each iteration, and MODTRAN’s output with the best fit is selected. We perform a tri-modal validation of simulators on a real hyperspectral scene by varying atmospheric condition, terrain surface models and proposed variants of adjacency models. We compared results of our model with Lockheed Martin’s well-established scene simulator CameoSim and acquired Ground Truth (GT) by Hyspex cameras. In clear-sky conditions, both models of CHIMES and CameoSim are in close agreement, however, in searched overcast conditions CHIMES BOAEM is shown to perform better than CameoSim in terms of ℓ 1 -norm error of the whole scene with respect to GT. TIAEM produces better radiance shape and covariance of background statistics with respect to Ground Truth (GT), which is key to good target detection performance. We also report that the results of CameoSim have a many-fold higher error for the same scene when the flat surface terrain is replaced with a Digital Elevation Model (DEM) based rugged one.

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“…The development of effective OCM techniques and their implementation into a system to protect a platform requires the analysis of the platform's susceptibility of being engaged by a missile in a hostile environment, accurate modelling of the behaviour of a launched missile, the evaluation of target detection and tracking algorithms, and the analysis of the sur- III vivability of the platform once a damage has occurred. Several conference papers and references therein provide unclassified data and models based on elementary physics as a starting point for further analysis [13,14,15,16,17,18].…”

Section: Optical Countermeasure Systemsmentioning

confidence: 99%