Research On Trajectory Models And Queries Of Moving Objects In Spatial Database

Research on querying technology for moving objects in spatial database is significant. To improve spatial database’s ability of managing spatio-temporal objects, this paper systematically investigates the indexing, querying and intellectual analysis technology for moving objects’location and trajectory in spatial database. The main research is as follows.The paper systematically investigates advanced indexing technology for moving objects. The paper presents complex spatial indexing structure such as Hiber R tree, X tree, TR tree and LUR tree, etc. It investigates principle of total-temporal indexing structure, and gives the TB+_TPR*-tree indexing structure which can support total-temporal information management. Based on TB+_TPR*-tree, highly efficient updating, insertion and deletion algorithms are designed. It further gives the two-level indexing structure’s model and operation algorithms. The structure can preferably query moving objects’past, current and future trajectory.The paper investigates moving queries with restrictions in moving environment, presents mapping method for network and trajectory, analyzes query mapping idea. It also introduces efficient quadtree for future trajectory, adopts new insertion, deletion and updating algorithms, greatly improves the query efficiency of moving objects.It’s important to investigate the spatio-temporal nearest neighbors in moving environment. This paper introduces heuristic-rule to compute the nearest neighbors in spatio-temporal road network, detailedly analyzes the query mode and route query cost. It introduces heuristic-rule to select moving query point and its nearest neighbors, sets forth the concepts of p-region and r-region and develops the efficient arithmetic to deal with the nearest neighbors query for the moving objects in the spatio-temporal road network. It also discusses the method of computing moving objects’nearest neighbors using Voronoi diagram in spatio- temporal road network. These researches improve the abilities to query spatio-temporal moving object database and supervise the moving objects in road network.This paper futher extendly investigates spatio-temporal object’s query method. It presents method and ideas of the nearest neighbor queries on the typical curved surface. It perfectly turns the spatial queries on cylinder and cone into computing the nearest neighbors of the data point aggregate in limitary plane. The paper gives reverse furthest neighbors’filter and query method, constructs new spatial indexing structure suitable for reverse furthest neighbors’query. This section extends the spatio-temporal database’s ability to manage more complex query requirement. It has higher theoretical and practical significance.