Research On Trajectory Planning Of Multiple Air Vehicles Based On Time Collaboration

With the development of information technology, because of its unique advantages, unmanned aircraft is more and more attention in the war. In modern warfare, with the improved of air defense system , use one aircraft to perform the task can't meet the requirements—maximize to destruction the enemy. Single aircraft disadvantage in: First, the task will be failure if it is destroy by enemy air defense system, and this destroy probability is increase with the improvement of air defense system; Second, the destroy capacity is limited, one aircraft can't completely destroy enemy targets. Therefore, research the more unmanned aircraft cooperative combat will be the trend of development in the future wars .As the core technology of unmanned aerial vehicles, route planning is research by more and more domestic and foreign experts. By far, most studies is focused on single vehicle route planning, for the multi-aircraft cooperative path planning is few studies.Existing multi-path planning algorithms including evolutionary algorithms, sparse A *algorithm and the Voronoi diagram method, and so on. There are have some problems in the search space and in time space, when use these algorithms to solve the multi-vehicle route planning. This paper presents a improved Sparse A * algorithm on the basis of Sparse A * algorithm, and use the improved sparse A * algorithm will be to single-vehicle route planning. On the basis of single-vehicle route planning, design of a time-varying collaborative voyage, combine the time-varying collaborative voyage and improvement sparse A * algorithm propose a new Collaborative sparse A* algorithm. Specific research results are as follows:(1)Improved Sparse A * algorithm. Improved Sparse A * algorithm is based on the original algorithm, introduced the shrinkage factor and use the shrinkage factor to cut operation search space of the algorithm, which makes the speed of convergence of the algorithm to dramatically improve. In order to the planning track more realistic,the improve Spares A* algorithm use the attitude matrix method to calculation extension point coordinate.(2)Time-varying collaborative voyage. During operation of the algorithm, since each node and the track number of the current track segment is known. Time-varying collaborative voyage is the maximum of all track from the starting point to the current node and the current node has extended the range of the target point and the straight line distance. The value of time-varying collaborative voyage is change by current node updated. This design of time-varying collaborative voyage is calculate and update in the algorithm, so the association of algorithm is more closer, meanwhile the collaborative performance of the algorithm is better. When faced the complexity environment, time-varying collaborative voyage can changed by algorithm, and avoid the complexity computing compared to the original collaborative voyage.(3)Collaborative sparse A * algorithm. This algorithm is combined with improved Sparse A * algorithm and time-varying collaborative voyage, the new algorithm have the advantages of both. The algorithm is able to find time collaborative track in a very short period of time, meanwhile, these time collaborative track have a higher collaborative rate.(4) For the above have a lot of simulation, the results of simulation show that that the proposed method is correct and is achievable.