The targets have strong infrared radiation near the 2.7 and 4.3 μm bands, so these two bands are also the best bands to detect the flying target, but since these two bands are not atmospheric windows, they are not included in most remote sensors. It is of great value to study the typical features of infrared absorption spectrum. However, due to the lack of necessary data acquisition ability, it often faces the problem of lack of data. There are frequent volcanic eruptions in various parts of the world. Whether volcanic eruptions have an impact on typical target detection or not is lacking in relevant analysis and research. In this paper, we get the data which transformed from the meteorological satellite data, through the wave band conversion model, based on the theory of atmospheric radiation transmission and the multivariate statistical analysis. The High temperature pixel is regarded as a mixed pixel of flame and background, and the target radiation is separated from the background to describe the thermal radiation of high temperature target pixel. When the aerosol mode is fixed, the observation zenith angle, atmospheric precipitation and the atmospheric profile are the influencing factors of the independent variable. For the background radiation brightness, the observation zenith angle, atmospheric precipitation in the atmosphere, atmospheric profile and background temperature are the influential factors of independent variables, and multivariate statistics are used to establish the relevant models. The volcano was detected by using the statistical characteristics of the third channel data of the FY-3 VIRR to obtain the apparent multidimensional features and quantitative analysis in time dimension, and the data of the same volcano are analyzed at different times. In spatial dimension, the spatial distribution characteristics of radiation brightness and luminance temperature of the crater are statistically calculated. The resolution of normal meteorological satellite is quite low, if we use pixel resolution to represent the volcanic area, the actual area of the volcano will be significantly exaggerated. So in this paper we propose a sub-pixel characteristics analysis method to increase the quantitative analysis accuracy. A combination of a mixture of pixels is considered as a combination of flame and background, and a linear spectral mixture model is used to accurately calculate the area and temperature of a volcano’s high temperature point by the emissivity of the mixed pixel. The results show that the 2.7~2.95 μm crater may interfere with the high temperature target in the weak background environment. In 4.2~4.45 μm band, the crater has been proved to be a potential disturbance that can not be ignored. Its energy is much higher than the general surface type.