RSSI融合RBF改善测距精度的研究

Study on Ranging Accuracy Improvement Based on RSSI Fusing RBF

由于室内环境中存在非视距和多径传输的影响,基于RSSI的测距技术的测距误差比较大。针对这个问题,提出一种采用RBF前馈神经网络补偿RSSI测距受外部环境影响而引起误差的方法,详细介绍了如何利用RBF神经网络数据融合方法补偿RSSI测距传感器误差的实现方法,给出了该方法在室内测距中的应用实例。实际应用表明:该补偿方法明显提高了测距的精度,适用于高精度要求或复杂环境下的RSSI测距。

Ranging technology based on RSSI has quite large ranging error,since there are existing impacts of wireless location in indoor environment and multi-path transmission. Aiming at this problem,a method using RBF feedforward neural network to com-pensate RSSI ranging error affected by the external environment was proposed. The method how to take advantage of the RBF neural network data fusion method to compensate the RSSI ranging sensor error was introduced. Indoor ranging instance was given. The practi-cal application shows that the compensation method significantly improves the accuracy of the distance measurement,it is suitable for RSSI ranging with high precision requirements or in complex environment.