With the rapid development of deep learning， the object detection network model hsa achieved great success in ship detection from synthetic aperture radar （SAR） images. In order to achieve better results， a large detection network is usually adopted， which requires more computing resources and slower inference. Knowledge distillation can effectively compress the network， but most of them are for image classification. Considering the difference between ships and background in SAR images， this paper proposes a combining local and global distillation method for ship detection. Considering the scattering characteristics of ships in SAR images， slice preprocessing in the amplitude direction is performed on the ship sample data constructing a separate data channel with more significant scattering characteristics， which improves the quality of input data fed to the network. Experimental results based on SAR ship detection dataset （SSDD） show that the proposed approach can effectively reduce the price of the network model and improve the detection performance， achieving 90.7% mAP.

The features of the aerospace defense equipment system include the large quantity of its elements， the large space of the deployment， the deep cross-linking of the coordination， and the strong game confrontation. The battle management of the equipment elements is a necessary tool for the improving of the combat effectiveness， and is also proven to be one of the most effective tools by the practice at home and abroad. This paper shows the basic connotation， the features and the abroad development status of the battle management of the aerospace defense equipment system， and provides some thoughts and advices on the subsequent development.

With the gradual maturity of unmanned underwater vehicle（UUV）， the study of its application in modern underwater warfare is an important basis for improving the theory of future underwater warfare. This paper analyzes the operational requirements of UUV about covert pursuit，launching a surprise attack and confusing enemy and attack， and researches three operational modes of UUV： passive centralized type， semi-active distribution type and resident distribution type， from the perspective of improving underwater combat capabilities. In addition， in order to adapt to the future underwater high-intensity warfare， the key technologies such as deep-diving communication， autonomous control and underwater distribution and recovery of UUV are proposed to provide an important practical basis for the development of UUV combat theory.

Based on the research of the structure and process of unmanned aerial swarm operation,by means of words and figures,four operational concepts that can exist in the future unmanned aerial vehicle (UAV) operations are conceived,namely,to the ground,to the air,to the sea and to the city,as well as possible operational tasks and operational patterns in operations,on which the key technologies of UAV system for completing combat task are analyzed,in order to provide reference for the demonstration and development of UAV equipment.