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An All-Time-Domain Moving Object Data Model, Location Updating Strategy, and Position Estimation

机译:全时域运动对象数据模型,位置更新策略和位置估计

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To solve the problems from the existing moving objects data models, such as modeling spatiotemporal object continuous action, multidimensional representation, and querying sophisticated spatiotemporal position, we firstly established an object-oriented all-time-domain data model for moving objects. The model added dynamic attributes into object-oriented model, which supported all-time-domain data storage and query. Secondly, we proposed a new dynamic threshold location updating strategy. The location updating threshold was given dynamically in accordance with the velocity, accuracy, and azimuth positioning information from the GPS. Thirdly, we presented several different position estimation methods to estimate the historical location and future location. The cubic Hermite interpolation function is used to estimate the historical location. Linear extended positioning method, velocity mean value positioning method, and cubic exponential smoothing positioning method were designed to estimate the future location. We further implemented the model by abstracting the data types of moving object, which was established by PL∖SQL and extended Oracle Spatial. Furthermore, the model was tested through the different moving objects. The experimental results illustrate that the location updating frequency can be effectively reduced, and thus the position information transmission flow and the data storage were reduced without affecting the moving objects trajectory precision.
机译:为了解决现有的运动对象数据模型存在的时空对象连续动作建模,多维表示以及查询复杂的时空位置等问题,我们首先建立了面向对象的运动对象全时域数据模型。该模型将动态属性添加到了面向对象的模型中,该模型支持全时域数据存储和查询。其次,我们提出了一种新的动态阈值位置更新策略。根据来自GPS的速度,精度和方位角定位信息动态地给出位置更新阈值。第三,我们提出了几种不同的位置估计方法来估计历史位置和未来位置。三次Hermite插值函数用于估计历史位置。设计了线性扩展定位方法,速度平均值定位方法和三次指数平滑定位方法来估计未来位置。我们通过抽象运动对象的数据类型进一步实现了该模型,该对象是由PL∖SQL和扩展的Oracle Spatial建立的。此外,该模型是通过不同的移动对象进行测试的。实验结果表明,可以有效地降低位置更新频率,从而在不影响运动物体轨迹精度的情况下,减少了位置信息的传输流量和数据存储量。

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