COG Analysis And Attack Strategy Generation Of Multiple Targets Network In Battlefield

The morden warfare could be regarded as the counterwork between the military forces in both sides. To analyze the contrary targets, attack the critical target, and get the superiority in information, firepower, and flexibility are in the first consideration of power nation to carry out the attack operation. So it is meaningful to analyze characteristics of multiple targets network in battlefield, summarize the transformation rules of its elements, and explore its center of gravity (COG) and vulnerability. This paper focused on the attacking problem of multiple targets network in battlefield, analyzed the COG of this multiple targets network, and studied the method of attack strategy generation. This paper contains these works listed below.Firstly, this paper carried out the theoretical study on multiple targets network in battlefield. It analyzed targets in battlefield, relationships between targets, and transformation rules of targets. Then two transformation rules (backup rule and self-repair rule) were outlined that based on the former analysis. Then, the mode l of multiple targets network in battlefield was built that based on the graph theory model. This model afforded supports for later studies on the COG analysis and the attack strategy generation process.Secondly, this paper proposed the COG analysis framework, which based on the Multi-Entity Bayesian Networks (MEBNs) theory. This framework used MEBNs to describle the uncertain information such as the uncertainty in target choosing and the evolution of targets, and analyzed the effects of every target on the COG in a multiple targets network. During this study, we introduced the basic theory and inference algorithm of MEBNs, and proposed the COG selection method and the combination algorithm of MFrags.Thirdly, this paper proposed the method of attack strategy generation, which based on the MDP. As there are so many successful applications that applied MDP in military planning domain, this paper also applied this method in attack strategy generation process of multiple targets network in battlefield. We built the stochastic system of this problem, the state set composed of targets'states, the action set composed of attacks on every target, the transition function based on the transition of targets'states, and value function based on the former results of COG analysis. Then we outlined the algorithm to slove this problem.Finally, in the case study, we implemented all parts of this COG analysis process, which tested the feasibility of this method. What's more, we also got the specific impact values of every element on COG from it. These values were transformed into the rewards in Markov Decision Process (MDP), which was the input of attack strategy generation. Then, this MDP mode l of this problem was built that based on the former COG analysis. With the policy-iteration algorithm, we got the optimization attack strategy, which contained different actions refer to different states.Attacking multiple targets network in battlefield is really a difficult problem in campaign. This paper explored the attack strategy generation problem which based on the COG analysis. The results could afford supports for staff to choose appropriate target or generate optimum attack strategy.