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Application of Improved Ant Colony Algorithm in Indoor Location

机译:改进蚁群算法在室内定位中的应用

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Due to geomagnetic properties being disturbed by the environment, the accuracy of indoor location based on geomagnetic field is lower. The paper improves the ant colony algorithm by adding elite strategy during pheromones update in indoor location, and then the positioning accuracies of a series of ant colony algorithms and KNN method are compared by experiments, the results of which show: (1) the improved algorithm is superior to the other methods based on the different combinations of parameters, especially for the easily confused and disturbed locations. (2) KNN method is suitable for the following occasions: the attributes of different locations are independent, and the attributes of the same location at different times are consistent. (3) The geomagnetic properties of different locations at different times are subject to diverse interference so that the positioning accuracies are also affected; the positioning accuracies of working hours are lower than that of non-working hours, and the positioning accuracies of the clean locations in a quiet environment are higher.
机译:由于地磁特性受到环境的干扰,基于地磁场的室内定位精度较低。通过在室内信息素更新过程中加入精英策略对蚁群算法进行改进,然后通过实验比较了一系列蚁群算法和KNN方法的定位精度,结果表明:(1)改进算法基于参数的不同组合,它优于其他方法,尤其是对于容易混淆和受干扰的位置。 (2)KNN方法适用于以下场合:不同位置的属性是独立的,并且同一位置在不同时间的属性是一致的。 (3)在不同时间,不同地点的地磁特性会受到多种干扰,因此也会影响定位精度;工作时间的定位精度低于非工作时间,并且在安静环境中清洁位置的定位精度较高。

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