本文提出了一种基于捕获特征的集中式算法来设计3x3场景中的协同分配策略

This paper proposes a centralized algorithm based on capturing features to design cooperative allocation strategies and guiding laws in 3x3 scenarios (potentially extended to NxP conventions). Capturability characteristics. The involvement of cooperative defense missiles in ground/naval defense systems illustrates this approach. We implement the flight mission payment (IFA) plan to design late hospitalization guidance. The IFA algorithm adopts a mid-course guidance strategy based on the earliest intercept geometry (EIG) guidance law. <br>In general, other NEZ and other methods use nonlinear kinematics (level set method, victory domain of survival theory) to solve the problem of calculation or approximate reachable set. In addition, we can also apply these techniques Design of decision-making systems for other types of autonomous vehicles (ie autonomous vehicles). <br>In addition, we can also apply these technologies to the design of decision-making systems for other types of autonomous vehicles (ie autonomous vehicles).

In this paper, a centralized algorithm based on capture characteristics is proposed to design the co-allocation strategy and guiding law (potentially extending to the NxP convention) in a 3x3 scenario. The capturability feature. This approach is illustrated by the involvement of cooperative defence missiles in ground/navy defence systems. We carry out the Mission Section (IFA) program to design a late-term hospital guidance method. The IFA algorithm uses a mid-segment guidance strategy based on the earliest intercept geometry (EIG) guidance law.<br> In general, other NEZ and other methods using nonlinear kinestology (horizontal set method, survival theory of the victory field) to solve computational or approximate uptoset problems may be associated with it. In addition, we can apply these technologies to the design of decision-making systems for other types of autonomous vehicles, i.e. autonomous vehicles.<br>In addition, we can apply these technologies to the design of decision-making systems for other types of autonomous vehicles, i.e. autonomous vehicles.

This paper proposes a centralized algorithm based on capture features to design collaborative allocation strategy and guidance law (potentially extended to NXP) in 3x3 scenarios. This method is illustrated in the case of cooperative defense missile in ground / naval defense system. We implement the mission payment (IFA) program and design the late hospitalization guidance method. IFA algorithm adopts the midcourse guidance strategy based on the earliest intercept geometry (eig) guidance law.<br>In general, other Nez and other methods use nonlinear kinematics (level set method, victory region of existentialism) to solve the problem of calculating or approximating reachable sets. In addition, we can also apply these techniques to the design of decision systems for other types of autonomous vehicles.<br>In addition, we can also apply these technologies to the design of decision-making system for other types of autonomous vehicles.<br>