Recent guided missiles equipped with the IR sensor system detect or identify target objects by using the infrared signal contrast between the object and the background within the infrared image obtained from the IR sensor. In either situations requiring for high detectability or requiring for low observability, it is important to obtain information about infrared signatures of the object under various environmental conditions prior to the applications. Infrared signal analyses can be performed in two different ways either by direct measurements or by computer simulations. However the methods by direct measurements can be a costly or unavailable way when the object is located on a hardly reachable area under various environmental conditions while a computer simulation software can be a versatile and useful tool in analyzing IR signals from the object under those harsh situations. Demands for versatile infrared signature simulation tools have been a recent upsurge over many countries for military or commercial applications. In this study, we are introducing a general purpose simulation software developed for IR image generation and analysis. The software is developed for unsteady state thermal analyses of 3-D objects constructed by using different materials coated with various paints under varying environmental conditions. Also the software has the capabilities of analyzing the CRI, the detection probability and the detection range information from the images generated.
Infrared (IR) signal emitted from objects over 0 degree Kelvin has been used to detect and recognize the characteristics of those objects. Recently more delicate IR sensors have been applied for various guided missiles and they affect a crucial influence on object’s survivability. Especially, in marine environment it is more vulnerable to be attacked by IR guided missiles since there are nearly no objects for concealment. To increase the survivability of object, the IR signal of the object needs to be analyzed properly by considering various marine environments. IR signature of a naval ship consists of the emitted energy from ship surface and the reflected energy by external sources. Surface property such as the emissivity and the absorptivity on the naval ship varies with different paints applied on the surface and the reflected IR signal is also affected by the surface radiative property, the sensor’s geometric position and various climatic conditions in marine environment. Since the direct measurement of IR signal using IR camera is costly and time consuming job, computer simulation methods are developing rapidly to replace those experimental tasks. In this study, we are demonstrate a way of analyzing the IR signal characteristics by using the measured background IR signals using an IR camera and the estimated target IR signals from the computer simulation to find the seasonal trends of IR threats of a naval ship. Through this process, measured weather data are used to analyze more accurate IR signal conditions for the naval ship. The seasonal change of IR signal contrast between the naval ship and the marine background shows that the highest contrast radiant intensity (CRI) value is appeared in early summer.
Infrared signals are widely used to discriminate objects against the background. Prediction of infrared signal from an
object surface is essential in evaluating the detectability of the object. Appropriate and easy method of procurement of
the radiative properties such as the surface emissivity, bidirectional reflectivity is important in estimating infrared signals.
Direct measurement can be a good choice but a costly and time consuming way of obtaining the radiative properties for
surfaces coated with many different newly developed paints. Especially measurement of the bidirectional reflectivity
usually expressed by the bidirectional reflectance distribution function (BRDF) is the most costly job. In this paper we
are presenting an inverse estimation method of the radiative properties by using the directional radiances from the
surface of concern. The inverse estimation method used in this study is the statistical repulsive particle swarm
optimization (RPSO) algorithm which uses the randomly picked directional radiance data emitted and reflected from the
surface. In this paper, we test the proposed inverse method by considering the radiation from a steel plate surface coated
with different paints at a clear sunny day condition. For convenience, the directional radiance data from the steel plate
within a spectral band of concern are obtained from the simulation using the commercial software, RadthermIR, instead
of the field measurement. A widely used BRDF model called as the Sandford-Robertson(S-R) model is considered and
the RPSO process is then used to find the best fitted model parameters for the S-R model. The results obtained from this
study show an excellent agreement with the reference property data used for the simulation for directional radiances. The
proposed process can be a useful way of obtaining the radiative properties from field measured directional radiance data
for surfaces coated with or without various kinds of paints of unknown radiative properties.
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