Research on Aerospace Cooperative Continuation Observation Strategy for Maritime Moving Target

Abstract

Abstract. Maritime moving targets continuation observation has important implications to maintain the safety of the navigation barrier. Existing methods either rely on satellite observations, or only rely on UAV observations. Even though the two cooperative observations, it confined to a simple task allocation. They did not solve the problem of maritime moving targets continuation observation. On the basis of difference between satellites observation and UAV observation, we constructed the aerospace collaborative continuation observation model for maritime moving target, and put forward aerospace collaborative continuation observation strategy (ACCOS) to reduce the complexity of solving the model. According to the spatial and temporal characteristics of the task, ACCOS extracted five sub problems to solve the model: Satellite planning, UAV flight plan, UAV observation sequence, target potential area and distribution probability density prediction, UAV path planning. In order to realize the optimization goal of the model, the five sub problems are modelled and solved in turn. Finally, the simulation results show that the proposed method can greatly reduce the average observation period of the target, and effectively solve the problem of the continuous observation of maritime moving target.

Complex Task Planning Method of Space-Aeronautics Cooperative Observation Based on Multi-Layer Interaction

“…Among the constraints, constraint (5) indicates the ratio of the number of planned meta-tasks to the total number of meta-tasks in any task. That is, the task coverage prob must be greater than the system set value prob.…”

“…In response to the above problems, many researchers have also conducted related research. In terms of models, Morris et al [3,4] and Herold et al [5] proposed a distributed framework by constructing a collaborative task allocation method. They divided the multi-platform collaborative task planning problem into multiple singleplatform task planning problems, and then formed multiple sub-planning centers.…”