DV-HOP和接收信号强度指示结合的改进算法

An improved algorithm for combination of DV-HOP and RSSI

由于DV-HOP算法易受网络拓扑的影响,定位精度不高,以及噪声和障碍对RSSI算法影响较大,由此会导致估计误差的产生,为提高定位精度以及鲁棒性,本文提出了一种DVHOP和RSSI结合的改进算法。首先,计算未知节点和锚节点间的距离,再将其输入到单隐层前馈神经网络训练好的网络模型,实现完整的拓扑训练集,取代网络拓扑结构,进而得到未知节点的位置信息。在MATLAB中做仿真实验,结果表明:与传统的DV-HOP算法和改进的DV-HOP算法相比,DV-HOP和RSSI结合的改进算法具有良好的定位效果和一定的抗干扰性,而且定位误差相对较小。

The DV-Hop algorithm has low positioning accuracy and the Received Signal Strength Indicator(RSSI)algorithm is greatly affected by environmental factors,which lead to the generation of estimation error.To overcome these weaknesses and improve positioning accuracy and robustness,an improved algorithm combining DV-HOP and RSSI(DV-HOP-RSSI)is presented in this paper.The core ideas of the DV-HOP RSSI algorithm are as follows.First,the single hidden layer feedforward neural network is used to obtain the trained network model instead of network topology,to achieve complete topology of the training set.Then the distance between unknown nodes and anchor nodes is calculated using the DV-HOP-RSSI algorithm.Furthermore,the location information of unknown nodes can be obtained by entering this distance into a trained network model.The simulation experiments were carried out in MATLAB,and the results show that the DV-HOP-RSSI algorithm not only has small positioning error,but also has good positioning effect and certain anti-interference,compared with the traditional DV-HOP algorithm and the improved DV-HOP algorithm.