Taking UAV's patrol shooting of fan blades as the application background， the image stitching method of fan blade images is studied， a method of background segmentation and image gridding stitching is proposed. Through in-depth learning of U-Net algorithm， the main part of the fan is extracted from the image， which can effectively deal with the difficult problem of fan blade splicing caused by large parallax and uneven distribution of target background feature points. In the process of image grid optimization， the energy function is designed based on the strategy of protecting the global linearity of the fan blade， and the grid vertex is optimized to the edge of the fan. Linear features are effectively protected. The natural stitching of several fan blades is realized. The stitching image has small distortion and continuous reality.

In order to satisfy impact angle constraints and reduce energy cost under salvo attacks against high-speed non-maneuvering targets， a three-dimensional coupled model is established， and a 3D energy optimal guidance law for non-linear systems with large constrained impact angles is proposed. The reasons for the low accuracy of 3D decoupled model are discussed， and a 3D coupled model is established. Based on this model， the appropriate control variables are chosen， and the 3D energy optimal guidance law under large impact angle constraints is derived， based on minimum principle. Experimental results indicate that the performance of the proposed coupled model on miss distance， impact angle error and energy cost has improved 0.7 m，1.1°，200 g compared with decoupled model. It can prove the advantages of the guidance law on control precision and energy cost.