无线传感器网络中基于RSSI算法的优化

摘要

研究表现煤矿井下巷道狭长、信号多径效应明显、通信条件差，井下无线传感器节点定位对环境敏感，导致节点定位误差较大。基于传统的 RSSI 算法基础上，提出一种给出衰减校正因子的三边加权质心定位算法。算法通过对 RSSI 衰减测量值补偿校正，近似接近节点间实际真实值；取任意的三点的校正距离算出未知节点的估计值后，求估计值的加权质心坐标为节点估计坐标。仿真结果表明，在相同的实验环境下，该改进的算法比传统的 RSSI 算法有更小的定位误差，提高算法对环境的适应性和定位精度，为井下无线传感器网络节点定位提供了依据。%The researches show that there are various questions in the coal mine, such as the long-narrow underground roadway, significant the signal multipath effect, poor communication conditions, and so on. Underground wireless sensor is sensitive to the environment which will lead large error to the node location. On the basis of traditional RSSI algorithm, this paper proposed a trilateral weighted centroid location algorithm with a given attenuation calibration factor. Firstly, the measured attenuation value of RSSI is compensated to approximate the actual between the nodes. Secondly, the weighted centroid coordinates of estimates are calculated to be node coordinates after obtaining the estimates of unknown nodes by taking any three of the calibration distance. Simulation results demonstrate that, in the same experimental environment, the proposed RSSI algorithm performs smaller location error than the traditional, improves the adaptability to environment and positioning accuracy, and provides the basis for underground wireless sensor network node location.