助推段导弹有高温、大面积的尾焰,根据尾焰光谱特征可准确识别导弹。将其应用到天基预警系统能够使导弹防御系统趋于完善,但光谱信息数据量庞大,从获取光谱信息到识别光谱信息需要耗费大量时间。为此,寻找能够代表导弹尾焰光谱的特征光谱,使用模糊算法对特征光谱进行数据处理,以达到准确、快速识别的目的。利用已有的红外图像和大气、云层、导弹及飞机尾焰光谱数据进行特征光谱图像拟合,经信噪比分析后可知,特征光谱图像比全波段红外光谱图像的信噪比高。分别使用模糊算法和光谱角测度对拟合图像进行处理,结果表明模糊算法的实时性和准确性优于光谱角测度。

The missile boost section has high temperature and large area of plume. The missile can be accurately identified according to the spectrum characteristics of the plume. Applying the plume spectrum into the space-based early warning system can improve the missile defense ability, but the huge spectral information results in a lot of time from obtaining spectral information to identifying spectral information. So, we find the characteristic spectrum which can represent the spectrum of the missile plume, and use fuzzy algorithm to process the characteristic spectrum data, so as to achieve the purpose of accurate and rapid identification. Analysis shows that the characteristic spectrum image has higher signal-to-noise ratio than full band infrared image, and fuzzy algorithm is better than spectral angle measurement (SAM) on real-time and accuracy.