摘要
基于RSSI(接收信号强度指示)的测距技术是一种低成本、低复杂度的距离测量技术,被广泛应用于基于测距的无线传感器网络定位技术中。由于室内环境存在非视距和多径传输的影响,导致测距误差较大。针对此问题,本文提出采用粒子滤波模型对RSSI值进行预处理,再利用BP人工神经网络进行距离估计的方法优化RSSI测距。实验表明,通过合理的RSSI值预处理和距离估计算法,RSSI测距的精度和抗干扰能力能得到明显的提高,与传统的RSSI测距算法相比,最大测距误差由2.56m降到1.06m。
Ranging technology based on RSSI（received signal strength indication）is a distance measurement technique with the features of low cost and low complexity.It is widely used in indoor wireless location.Ranging error is relatively large with the impact of NLOS indoor and multipath transmission.For this reason the paper presents preprocessing the received signal strength values with Particle Filter and using BP artificial neural network to measure the distance.According to the result of the experiments,RSSI ranging accuracy and anti-jamming capability have been significantly improved by this method.Compared with the traditional algorithm,the maximum measuring precision is reduced from 2.56 mto 1.06 m.
出处
《电子测量技术》
2016年第3期122-126,共5页
Electronic Measurement Technology
