A Kalman filter updating method for the indoor moving object database
Expert Systems with Applications: An International Journal
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To find similar trajectories of a moving object has been recently an interesting issue in moving object databases due to its diverse application fields (e.g., traffic control systems, meteorology monitoring systems, etc.). In this work, trajectories are first modeled based discrete grid cells. Then, the similarity between trajectories is defined by introducing a new distance function. Furthermore, a novel nearest neighbor query for trajectory of moving objects, i.e. Set Nearest Neighbor (SNN) query is presented, and an efficient shape-based similarity algorithm for SNN is given. The performance study shows the proposed query method is efficient.