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An Improved RSSI-Based Positioning Method Using Sector Transmission Model and Distance Optimization Technique

机译:基于扇区传输模型和距离优化技术的基于RSSI的改进定位方法

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This paper focuses on the positioning algorithm suitable for harsh indoor environment such as manufacturing workshop in which the interferences from different directions cannot be neglected. The positioning algorithm is an improved Received Signal Strength Indication- (RSSI-) based ranging method. To preprocess the RSSI data Gaussian filter and mean filter are adopted. A sector transmission model is constructed and applied to divide the area around the anchor node into several sectors, and the shadowing model of each sector is measured. Then the average of all RSSI values in a particular sector is considered as the final RSSI value for distance calculation. The calculated distances designated for trilateration are also optimized to eliminate the abnormal distances from positioning calculations. Positioning experiment is designed via ZigBee facilities. The results show that the proposed algorithm greatly improves the positioning accuracy and stability; for instance, the average positioning error is reduced from 1.32 m to 0.79 m. Moreover, this study also proves that the node position has great influence on the positioning accuracy.
机译:本文重点研究了适用于恶劣室内环境的定位算法,例如在制造车间中,可以忽略来自不同方向的干扰。定位算法是一种改进的基于接收信号强度指示(RSSI-)的测距方法。对RSSI数据进行高斯滤波和均值滤波进行预处理。构建并应用扇区传输模型以将锚节点周围的区域划分为几个扇区,并测量每个扇区的阴影模型。然后,将特定扇区中所有RSSI值的平均值视为距离计算的最终RSSI值。还指定了用于三边测量的计算距离,以从定位计算中消除异常距离。定位实验是通过ZigBee设施设计的。结果表明,该算法大大提高了定位精度和稳定性。例如,平均定位误差从1.32 m降低到0.79 m。此外,该研究还证明节点位置对定位精度有很大影响。

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