In order to solve the problem of typical target recognition, the method of aerial target detection and recognition based on hyperspectral characteristics is proposed. First, the minimum noise separation transform is performed on the hyperspectral image to calculate the intrinsic dimension, and at the same time, the image is denoised. Then, the information divergence is used as the projection index, and the projection index value is adaptively segmented to obtain the spectral curve to be extracted. Finally, the target and its position are identified by spectral angle matching. The results show that the intrinsic dimension of the image is 35 by MNF transform. The projection image is obtained by sequential projection pursuit. Through the adaptive threshold judgment, the value 0.2475 corresponding to the slope of - 1 in the projection index value curve is selected as the threshold to eliminate the background, and then the projection pursuit method is used to extract the end element spectral curve from the projection image. The algorithm in this paper can effectively suppress the influence of background and noise, and can recognize typical targets in the airport more effectively.