Development of an inverse distance weighted active infrared stealth scheme using the repulsive particle swarm optimization algorithm.

Treatments for detection by infrared (IR) signals are higher than for other signals such as radar or sonar because an object detected by the IR sensor cannot easily recognize its detection status. Recently, research for actively reducing IR signal has been conducted to control the IR signal by adjusting the surface temperature of the object. In this paper, we propose an active IR stealth algorithm to synchronize IR signals from the object and the background around the object. The proposed method includes the repulsive particle swarm optimization statistical optimization algorithm to estimate the IR stealth surface temperature, which will result in a synchronization between the IR signals from the object and the surrounding background by setting the inverse distance weighted contrast radiant intensity (CRI) equal to zero. We tested the IR stealth performance in mid wavelength infrared (MWIR) and long wavelength infrared (LWIR) bands for a test plate located at three different positions on a forest scene to verify the proposed method. Our results show that the inverse distance weighted active IR stealth technique proposed in this study is proved to be an effective method for reducing the contrast radiant intensity between the object and background up to 32% as compared to the previous method using the CRI determined as the simple signal difference between the object and the background.

Study on inverse estimation of radiative reflection properties in mid-wavelength infrared region by using the repulsive particle swarm optimization algorithm.

In this study, we develop software that estimates radiative properties of painted surfaces in the mid-wavelength infrared (MWIR) region inversely from the measured temperature and radiance variations with time by applying the repulsive particle swarm optimization algorithm. In this study the radiance in the MWIR region and surface temperature are obtained from a commercial software considering winter weather, and these results are used to estimate radiative reflection properties. Surface radiative reflection properties for three different paints are estimated by using the predetermined radiance in the MWIR region and surface temperature. This finding suggests that the process for obtaining surface radiative properties proposed in this study could be a useful way to obtain infrared signatures from objects with various surface coatings of unknown radiative properties.