A Kalman filter updating method for the indoor moving object database
Expert Systems with Applications: An International Journal
| Hi-index | 0.00 |
With the development of wireless communication and mobile spatial information services, there is an increasing demand for current applications to have the capability of processing spatio-temporal data. Typical applications include intelligent transport systems, digital battlefield, location e-commerce, and so forth. Moving Objects Database, which manages dataset of moving objects, serves as an essential underlying technique towards this goal. One of the unique characters for such applications is to answer queries that must be evaluated for a time interval, namely continuous query. However, existing updating strategy for moving objects is designed for the general purpose of location management and works well for instantaneous queries, when applied to continuous queries, the result is hardly satisfactory. In this paper, we propose a new dead-reckoning updating policy based on the unique character of continuous query, which improves the quality of query results and at the same time reduce information cost.