模糊识别算法在导弹尾焰光谱识别中的应用

目前基于天基高光谱图像的导弹识别算法都是从光谱曲线的整体分析考虑，所需数据量大，算法处理冗余。为弥补算法不足，首先从导弹尾焰光谱的影响因素考虑，分析了导弹发动装置，燃料成分及温度压强对尾焰光谱的影响，得出在一定假设条件下，使用特征段处的辐射数据即可达到导弹识别的结论。在此基础上引入模糊识别算法，算法充分利用辐射强度与光谱线型信息，识别结果是各型号导弹的隶属概率。通过对光谱角测度分析，发现其过于依赖线型，对线型相近的谱线识别效果不佳，将模糊识别结果与光谱角测度识别结果对比，证实了模糊算法在光谱识别中的优越性。

Application of fuzzy recognition algorithm in the spectrum identification of missile tail flame

At present, the missile recognition algorithm based on the space-based hyperspectral image is considered from the overall analysis of the spectral curve. The required data is large and the algorithm is redundant. In order to solve the problem of insufficient algorithm, the influence of missile launching device, fuel composition and temperature pressure on the tail flame spectrum from the influence factors of missile tail flame spectrum was analyzed firstly, and the radiation data at the characteristic interval under certain assumptions was used to obtain the conclusion of missile identification. On this basis, the fuzzy recognition algorithm was introduced. The algorithm made full use of the radiation intensity and the spectral line information. The recognition result is the membership probability of each type missile. Through analyzing the spectral angle, it is found that it is too dependent on the line type, and the effect of the line recognition is poor by comparing the fuzzy recognition result with the spectral angle measurement, the superiority of the fuzzy algorithm in the spectral recognition is proved.