Due to physical structures and motion attitudes, the IR radiative properties of ballistic targets are different during their flights. However, such differences cannot be easily detected by high-speed observing platform under the influence of detector noise, consequently causing difficulties with the classification and recognition of targets. This paper presents a modeling and simulation of the IR radiative properties of ballistic targets, provides a discussion on the variations in the IR radiative properties among different targets, and proposes a method for a parametric expression of the grayscale time series of the targets under noise. The experimental result indicates that by constructing a hybrid model of tendency, period and noise, an effective feature of the time series can be extracted using de-noising, curve-fitting, and frequency transformation, which ultimately contributes to the classification of targets.
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