Presentation + Paper
21 October 2016 Identification, regression and validation of an image processing degradation model to assess the effects of aeromechanical turbulence due to installation aircraft
M. Miccoli, A. Usai, A. Tafuto, A. Albertoni, F. Togna
Author Affiliations +
Proceedings Volume 9989, Technologies for Optical Countermeasures XIII; 99890I (2016) https://doi.org/10.1117/12.2241514
Event: SPIE Security + Defence, 2016, Edinburgh, United Kingdom
Abstract
The propagation environment around airborne platforms may significantly degrade the performance of Electro-Optical (EO) self-protection systems installed onboard. To ensure the sufficient level of protection, it is necessary to understand that are the best sensors/effectors installation positions to guarantee that the aeromechanical turbulence, generated by the engine exhausts and the rotor downwash, does not interfere with the imaging systems normal operations.

Since the radiation-propagation-in-turbulence is a hardly predictable process, it was proposed a high-level approach in which, instead of studying the medium under turbulence, the turbulence effects on the imaging systems processing are assessed by means of an equivalent statistical model representation, allowing a definition of a Turbulence index to classify different level of turbulence intensities.

Hence, a general measurement methodology for the degradation of the imaging systems performance in turbulence conditions was developed. The analysis of the performance degradation started by evaluating the effects of turbulences with a given index on the image processing chain (i.e., thresholding, blob analysis). The processing in turbulence (PIT) index is then derived by combining the effects of the given turbulence on the different image processing primitive functions.

By evaluating the corresponding PIT index for a sufficient number of testing directions, it is possible to map the performance degradation around the aircraft installation for a generic imaging system, and to identify the best installation position for sensors/effectors composing the EO self-protection suite.
Conference Presentation
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. Miccoli, A. Usai, A. Tafuto, A. Albertoni, and F. Togna "Identification, regression and validation of an image processing degradation model to assess the effects of aeromechanical turbulence due to installation aircraft", Proc. SPIE 9989, Technologies for Optical Countermeasures XIII, 99890I (21 October 2016); https://doi.org/10.1117/12.2241514
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CITATIONS
Cited by 1 scholarly publication.
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KEYWORDS
Turbulence

Imaging systems

Medium wave

Sensors

Image processing

Directed infrared countermeasures

Systems modeling

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