主要针对高光谱红外图像中弱小目标的检测方法进行研究，根据目标检测的RX 算法模型，给出了算法在高光谱目标检测中的性能评价，分析了检测器像元数、光谱波段数对算法性能的影响，在RX 算法及相关改进算法的基础上，通过对AVIRIS 数据的仿真实验，分析了相关矩阵在高光谱目标检测中算法的应用优势，提出了一种目标自动检测方法，验证了UTD 算法对有特定波段依赖性的小目标有良好检测效果。理论分析和仿真实验证明了RX 算法在红外高光谱目标自动检测中的有效性。

In this paper, an automatic dim small target detection for hyperspectral IR imagery is researched, according to target detection RX algorithm model, the algorithm performance evaluation index in point target detection for hyperspectral is presented, the pixel number of detector, the number of bands which affect the algorithm performance are analyzed. based on RX algorithm and RX improved algorithm, in experiments on AVIRIS hyperspectral IR imagery, the correlation matrix application advantage in hyperspectral target detection algorithms is analyzed, Automatic detection of a target is proposed, UTD algorithm is verified to have a good detection results with specific band dependence in the target detection. Theoretical analysis and simulation results showed that the RX algorithm is Effective in automatic target detection for Hyperspectral IR Imagery.