Patrol duty is a security and stability maintenance operation of great significance， but the patrol environment is complex， the object are diverse， and the problem of difficult detection is very prominent， so how to accurately and real-time detect patrol duty objects is of great practical significance.In order to improve the accuracy and real-time detection of patrol duty objects， the YOLOv5 algorithm is improved. In order to suppress the interference caused by the patrol environment， the ECA-Net attention mechanism is combined to improve the saliency of the detected object； and the introduction of BiFPN structure ensures better real-time performance and multi-scale object detection capabilities of the algorithm.Comparing the improved algorithm with the original algorithm， the mAP is improved by 3.51% ； comparing with four algorithms， the results show that the algorithm can better reduce the impact of patrol object detection of due to the problems of similar detection，diverse scales and light interference， which further verifies the effectiveness of the proposed algorithm in the task of patrol duty object detection.

At present,the impact of long-term natural environmental effects on missile equipment is getting increasingly attention by more and more equipment development affiliations,and a large number of natural environmental tests have been carried out for multi-level products to verify and evaluate the adaptability of natural environment.In order to more effectively implement and promote the natural environmental test work for equipment,the natural environmental test requirements,test types,test technology development and its application of typical missile equipment are demonstrated on the basis of both characteristics and weak links of typical missile equipment.Moreover,as to the problems encountered in the implementation of current natural environmental test,the development suggestions of missile equipment natural environmental test technology are put forward in terms of system planning,data mining,research and application of accelerated test technology.

The long term natural environment adaptability of missile cannot be evaluated completely in the short term due to the low degeneration of natural environmental effects,though extremely limited environmental tests have been carried out in the missile laboratory in response to various environmental factors in the natural environment.A set of comprehensive evaluation methods is provided for long-term natural environmental effects,which defines the natural environment adaptability verification method for different types of missile products.Through the comprehensive utilization of the basic data of natural environment adaptability and various test verification information,the systematic,comprehensive and rapid evaluation of the missile's natural environment adaptability is realized.

At present,military equipment,systems and civil infrastructure are facing increasingly serious electromagnetic pulse (EMP) threat.The United States has been strengthening the assessment and defense of EMP threat.To fully un-derstand and analyze the current situation,problems and policies of EMP defense in the United States,the series of assessment reports issued by EMP Commission,the president executive order and important documents issued by the United States government such as “National Defense Authorization Act” are researched.The EMP threat environ-ment,scenes and responsive strategies in the United States,and the roles,responsibilities and tasks of relevant de-partments and heads of the federal government are analyzed.It is noted that the U.S. currently aims to ensure U.S. security by establishing strong national executive leadership,organizing and coordinating government and private sector relationships,and promoting technology information sharing to strengthen U.S. critical infrastructure and improve U.S. resilience to EMP threats.

Air-to-ground target detection plays an important role in performing typical military and civilian tasks on air-based unmanned platforms such as drones and missiles.Aiming at the problems of fewer effective features and high false detection rate of the air-to-ground target intelligent detection method,an air-to-ground target intelligent detection algorithm based on the dual attention mechanism is proposed.First,a channel attention mechanism is established,focusing on the important channels in the feature layer that contain the effective features of the target.Second,the spatial attention mechanism is used to enable the network to focus on local key target areas.The dual attention mechanism combines the advantages of the channel attention mechanism and the spatial attention mechanism to improve the efficiency of target detection.A loss function that couples the dual attention mechanism and target detection is also designed,which realizes the synchronous optimization of the loss function.Finally,a comparative experiment is performed using the air-to-ground target detection data set.The experimental results show that the proposed algorithm has higher target detection accuracy and training speed than other algorithms in the air-to-ground scenario.

Facing the problems of complex types of peacekeeping equipment,complex and harsh peacekeeping environment,and prominent contradiction in support maintenance,it is necessary to strengthen the demand prediction of spare parts for peacekeeping equipment support before the start of the mission.Firstly,the characteristics of peacekeeping mission are analyzed,and the concept of peacekeeping equipment support is put forward.Secondly,the steps of peacekeeping equipment support demand prediction are proposed,and the prediction model of peacekeeping equipment support based on particle swarm optimization (PSO)-back propagation (BP) neural network is studied.Finally,the effectiveness of the algorithm is verified by experiments based on actual data.The experimental results show that the prediction model of peacekeeping equipment support based on PSO-BP neural network can effectively predict the demand for spare parts of peacekeeping equipment support and improve the efficiency of peacekeeping equipment support.

Considering the characteristics of the uniform motion of the missile and target before intersection,the target image measured with infrared seeker was used to analyze the passive ranging method based on target image area and target image gray-scale.The target image model was established.Two ranging equations based on image area gradient and image gray-scale gradient were deduced without target parameter.The correctness of the two ranging methods were verified by simulations.These two methods provide references for passive infrared image ranging.

Rapid and efficient implementation of dynamic scheduling of battlefield repair tasks is one of the important tasks for rush-repair force to achieve task differentiation and command control in wartime. The research status about battlefield repair at home and abroad is summarized from 8 aspects including basic research, legislation, team building, training and so on. The task dynamic scheduling is reviewed from 3 aspects: application, solving thinking and solving method. Suggestions and development directions about dynamic scheduling of battlefield rush-repair tasks are put forward, which provides direction guidance for solving the dynamic scheduling of battlefield repair tasks.