IRST infrared background analysis of bay environments

Abstract

Present-day naval operations take place in coastal environments as well as narrow straits all over the world. Coastal environments around the world are exhibiting a number of threats to naval forces. In particular a large number of asymmetric threats can be present in environments with cluttered backgrounds as well as rapidly varying atmospheric conditions. During trials executed in False Bay a large amount of target, background and atmosphere data was gathered that is of use in analysis of optical characteristics of targets and backgrounds. During the trials a variety of backgrounds were recorded. We have used these backgrounds to validate the TNO background model MIBS to incorporate also coastal backgrounds and sunlit sea backgrounds. In the paper we show results of the background analysis, for coastal bay backgrounds. In particular the detection of small targets by automatic system may be hampered by small surface structure variations at the surface and near the horizon. The data that we analyzed are sea surface structure, temporal behaviour, and spectral differences during different environmental conditions that occurred during the trials. This data is essential to feed detection algorithms, and performance models for the assessment of sensor performance in coastal environment. Some sensor management approaches for application in IRST systems is discussed.

Ship recognition for improved persistent tracking with descriptor localization and compact representations

“…In this method, the background is assumed to have properties that are constant per image line (corrected for rotation) and to vary only smoothly from line to line. This assumption is sufficiently accurate for various levels of sea state, in open ocean as well as in bay environments, as known from infrared statistical background analysis work by Schwering [23]. Pixels that are statistically unlikely to be background are clustered in a segmentation of possible ships.…”

Recognition of ships for long-term tracking

“…In this method, the background is assumed to have properties that are constant per image line (corrected for rotation) and to vary only smoothly across the lines. From infrared statistical background analysis work of Schwering [20][21] [22] we know that this assumption is sufficiently accurate for various levels of sea state, in open ocean as well as in bay environments. Pixels that are statistically unlikely to be background are clustered in a segmentation of possible ships.…”

Variation analysis of 24 hour winter infrared images for small target detection

“…In the infrared small target detection community, back-2008, the team analyzed the variations in the vertical profile ground subtraction-based approaches are well-established and radiance and clutter in a coastal environment [9]. threshold-based target detection method [3].…”

“…He measured the thermal variations in various environments. Recently, the TNO research team char acterized small surface targets in coastal environments [8], [9], [1]. In 2007, the TNO team introduced the measurement environment and examined the target contrast, and contrast features of a number of small sea surface vessels [8].…”