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首页> 外文期刊>International Journal of Pattern Recognition and Artificial Intelligence >Research on an Adaptive Algorithm for Indoor Bluetooth Positioning
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Research on an Adaptive Algorithm for Indoor Bluetooth Positioning

机译：室内蓝牙定位的自适应算法研究

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摘要

Building structure and other factors lead to the performance deterioration of global postioning system (GPS) positioning systems indoors. An adaptive model for Bluetooth-based indoor positioning is proposed in this paper, targeting at the complex indoor environment, to improve the performance of Bluetooth-oriented indoor positioning systems. More accurate Received Signal Strength Indicator (RSSI) calibration which is optimized via Gaussian filtering, together with the environment-dependent attenuation coefficient optimization, results in a more precise hybrid model in the complicated indoor environment. Experiment results show that the difference between the estimated results and the measured samples is less than 0.25m as the target node and reference node is less than 1.5m far from each other. As the distance increases to more than 1.5m, the relative difference between the estimated values and the measured ones decreases to 7.8% at most, satisfying the requirements for indoor positioning applications.
机译：建筑结构和其他因素导致室内全球定位系统（GPS）定位系统的性能下降。针对复杂的室内环境，提出了一种基于蓝牙的室内定位自适应模型，以提高面向蓝牙的室内定位系统的性能。通过高斯滤波优化的更精确的接收信号强度指示器（RSSI）校准，以及与环境有关的衰减系数优化，可在复杂的室内环境中提供更精确的混合模型。实验结果表明，当目标节点与参考节点相距小于1.5m时，估计结果与实测样本之差小于0.25m。当距离增加到大于1.5m时，估计值与测量值之间的相对差最大减少到7.8％，满足了室内定位应用的要求。

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