A unified infrared and radio frequency simulation environment

Keith F. Prussing; Christopher E. Cordell Jr.; Daniel Levy

doi:10.1117/12.3013502

7 June 2024 A unified infrared and radio frequency simulation environment

Keith F. Prussing, Christopher E. Cordell Jr., Daniel Levy

Proceedings Volume 13035, Synthetic Data for Artificial Intelligence and Machine Learning: Tools, Techniques, and Applications II; 1303507 (2024) https://doi.org/10.1117/12.3013502
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

It is becoming more common for search and track algorithms to need to account for observations that can arise from both radio frequency (RF) and electro-optical infrared (EO/IR) measurements in the same scenario. Development of novel algorithms for search and track applications requires measured or synthetically generated data, and frequently only considers one or the other. Historically, the synthetic data generation process for RF and EO/IR developed independent of one another and did not share a common sense of “truth” about the environment or the objects within the simulation. This lack of a common framework with a consistent environment and platform representation between the two sensing modalities can lead to errors in the algorithm development process. For example, if the RF data assumed one set of atmospheric conditions while the EO/IR assumed a different set of conditions, the RF modality could over or under perform compared to the EO/IR. To address this issue, Georgia Tech Research Institute (GTRI) has developed General High-fidelity Omni-Spectrum Toolbox (GHOST) as a plug and play simulation architecture to generate high-fidelity EO/IR and RF synthetic data for search and track algorithm development. Additionally, because GHOST is plug and play, it can potentially provide synthetic or measured result to developmental algorithms without needing to change the algorithm’s interface. This paper presents the efforts GTRI has put into extending GHOST into the RF domain and presents sample results from search and track algorithm development. It also presents a look forward into how GHOST is being adapted to accommodate measured data alongside synthetic data for improved algorithm development.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Keith F. Prussing, Christopher E. Cordell Jr., and Daniel Levy "A unified infrared and radio frequency simulation environment", Proc. SPIE 13035, Synthetic Data for Artificial Intelligence and Machine Learning: Tools, Techniques, and Applications II, 1303507 (7 June 2024); https://doi.org/10.1117/12.3013502

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