Refining Atmosphere Profiles for Aerial Target Detection Models

Atmospheric path radiance in the infrared is an extremely important quantity in calculating system performance in certain infrared detection systems. For infrared search and track (IRST) system performance calculations, the path radiance competes with the target for precious detector well electrons....

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Autores principales:	Robert Grimming, Patrick Leslie, Derek Burrell, Gerald Holst, Brian Davis, Ronald Driggers
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	infrared detection atmospheric radiation path radiance sky temperatures Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/7f0d5a84d36c476195e29b6e12bfee72
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id	oai:doaj.org-article:7f0d5a84d36c476195e29b6e12bfee72
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spelling	oai:doaj.org-article:7f0d5a84d36c476195e29b6e12bfee722021-11-11T19:05:36ZRefining Atmosphere Profiles for Aerial Target Detection Models10.3390/s212170671424-8220https://doaj.org/article/7f0d5a84d36c476195e29b6e12bfee722021-10-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7067https://doaj.org/toc/1424-8220Atmospheric path radiance in the infrared is an extremely important quantity in calculating system performance in certain infrared detection systems. For infrared search and track (IRST) system performance calculations, the path radiance competes with the target for precious detector well electrons. In addition, the radiance differential between the target and the path radiance defines the signal level that must be detected. Long-range, high-performance, offensive IRST system design depends on accurate path radiance predictions. In addition, in new applications such as drone detection where a dim unresolved target is embedded into a path radiance background, sensor design and performance are highly dependent on atmospheric path radiance. Being able to predict the performance of these systems under particular weather conditions and locations has long been an important topic. MODTRAN has been a critical tool in the analysis of systems and prediction of electro-optical system performance. The authors have used MODTRAN over many years for an average system performance using the typical “pull-down” conditions in the software. This article considers the level of refinement required for a custom MODTRAN atmosphere profile to satisfactorily model an infrared camera’s performance for a specific geographic location, date, and time. The average difference between a measured sky brightness temperature and a MODTRAN predicted value is less than 0.5 °C with sufficient atmosphere profile updates. The agreement between experimental results and MODTRAN predictions indicates the effectiveness of including updated atmospheric composition, radiosonde, and air quality data from readily available Internet sources to generate custom atmosphere profiles.Robert GrimmingPatrick LeslieDerek BurrellGerald HolstBrian DavisRonald DriggersMDPI AGarticleinfrared detectionatmospheric radiationpath radiancesky temperaturesChemical technologyTP1-1185ENSensors, Vol 21, Iss 7067, p 7067 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	infrared detection atmospheric radiation path radiance sky temperatures Chemical technology TP1-1185
spellingShingle	infrared detection atmospheric radiation path radiance sky temperatures Chemical technology TP1-1185 Robert Grimming Patrick Leslie Derek Burrell Gerald Holst Brian Davis Ronald Driggers Refining Atmosphere Profiles for Aerial Target Detection Models
description	Atmospheric path radiance in the infrared is an extremely important quantity in calculating system performance in certain infrared detection systems. For infrared search and track (IRST) system performance calculations, the path radiance competes with the target for precious detector well electrons. In addition, the radiance differential between the target and the path radiance defines the signal level that must be detected. Long-range, high-performance, offensive IRST system design depends on accurate path radiance predictions. In addition, in new applications such as drone detection where a dim unresolved target is embedded into a path radiance background, sensor design and performance are highly dependent on atmospheric path radiance. Being able to predict the performance of these systems under particular weather conditions and locations has long been an important topic. MODTRAN has been a critical tool in the analysis of systems and prediction of electro-optical system performance. The authors have used MODTRAN over many years for an average system performance using the typical “pull-down” conditions in the software. This article considers the level of refinement required for a custom MODTRAN atmosphere profile to satisfactorily model an infrared camera’s performance for a specific geographic location, date, and time. The average difference between a measured sky brightness temperature and a MODTRAN predicted value is less than 0.5 °C with sufficient atmosphere profile updates. The agreement between experimental results and MODTRAN predictions indicates the effectiveness of including updated atmospheric composition, radiosonde, and air quality data from readily available Internet sources to generate custom atmosphere profiles.
format	article
author	Robert Grimming Patrick Leslie Derek Burrell Gerald Holst Brian Davis Ronald Driggers
author_facet	Robert Grimming Patrick Leslie Derek Burrell Gerald Holst Brian Davis Ronald Driggers
author_sort	Robert Grimming
title	Refining Atmosphere Profiles for Aerial Target Detection Models
title_short	Refining Atmosphere Profiles for Aerial Target Detection Models
title_full	Refining Atmosphere Profiles for Aerial Target Detection Models
title_fullStr	Refining Atmosphere Profiles for Aerial Target Detection Models
title_full_unstemmed	Refining Atmosphere Profiles for Aerial Target Detection Models
title_sort	refining atmosphere profiles for aerial target detection models
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/7f0d5a84d36c476195e29b6e12bfee72
work_keys_str_mv	AT robertgrimming refiningatmosphereprofilesforaerialtargetdetectionmodels AT patrickleslie refiningatmosphereprofilesforaerialtargetdetectionmodels AT derekburrell refiningatmosphereprofilesforaerialtargetdetectionmodels AT geraldholst refiningatmosphereprofilesforaerialtargetdetectionmodels AT briandavis refiningatmosphereprofilesforaerialtargetdetectionmodels AT ronalddriggers refiningatmosphereprofilesforaerialtargetdetectionmodels
_version_	1718431655050346496

Refining Atmosphere Profiles for Aerial Target Detection Models

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