A method for evaluating nearest-neighbor queries in moving object environments

Data uncertainty is often involved in moving object tracking applications due to reasons such as imprecise measurement or sampling errors. The nearest-neighbor queries in moving object environments are important in the applications of moving object tacking. A probabilistic method for evaluating nearest-neighbor queries for moving object tracking in moving object environments is proposed, based on the pruning and sorting of uncertain data. Simulation result shows that the proposed method outperforms other evaluating method we knew for moving objects in the times of evaluations of integrals needed and efficiency of evaluating.