Comparison of analytical parametric models and measured data dependent models for EO system performance prediction

Yücel Cengiz Özer; Özgür Murat Polat

doi:10.1117/12.2665640

14 June 2023 Comparison of analytical parametric models and measured data dependent models for EO system performance prediction

Yücel Cengiz Özer, Özgür Murat Polat

Author Affiliations +

Proceedings Volume 12533, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXXIV; 125330K (2023) https://doi.org/10.1117/12.2665640
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Abstract

Electro-Optical (EO) system performance prediction requires physically validated system models, atmosphere/clutter models, and target signature models. These models in general include radiometric equations and measured data. The main model of such a performance prediction simulation is EO model. EO model’s subsystem models are optical system and detector system models. One approach for EO modeling is parametric model approach which is constructed via solving radiometric equations by using optics and detector model parameters. The other approach is to use the measured system data in order to simulate the systems. The measurement includes system temporal/spatial noise, intensity response, and spatial response. In this paper, these two methods are compared via measurements collected with a generic electro-optical camera. The results show that the measured data methodology is reliable for a system simulation, whereas parametric model approach can be reliable provided that the parameters are correctly defined in their physical boundaries.

Conference Presentation

Citation Download Citation

Yücel Cengiz Özer and Özgür Murat Polat "Comparison of analytical parametric models and measured data dependent models for EO system performance prediction", Proc. SPIE 12533, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXXIV, 125330K (14 June 2023); https://doi.org/10.1117/12.2665640

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available