![]() It is difficult to describe the characteristic information of the shape and micro-motion states of the targets and to discriminate different targets effectively by the characteristic information. Thus the generated images can satisfy the needs of algorithms validation for tracking and recognition.Įxo-atmospheric infrared (IR) point target discrimination is an important research topic of space surveillance systems. And the correlative parameters of simulation can be set according to the given scene. Finally, the IR image sequence of high fidelity is obtained. The proposed method considers two critical factors of the pixel plane, occupy-empty ratio and defect elements, which affect the imaging of targets markedly but are neglected in previous work. In order to obtain IR images of high fidelity, especially that the fluctuation of the target signal-to-noise ratio (SNR) is reasonably similar to the actual one, this paper proposes an improved IR imaging simulation method. In imaging modeling, the staring focal plane is taken into account due to its wide employment. ![]() ![]() ![]() The proposed framework includes three steps, target characteristic modeling, motion modeling, and imaging modeling. It overcomes the shortcoming of the existing algorithms, which cannot simulate IR imaging from the entire midcourse process. An infrared (IR) imaging simulation framework based on the strap-down platform is proposed for midcourse ballistic targets. ![]()
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