基于混合群智能算法优化的RSSI质心定位算法

RSSI-based Centroid Localization Algorithm Optimized by Hybrid Swarm Intelligence Algorithm

传感器节点的自身定位是无线传感器网络中最为关键的技术之一。针对无线传感器网络的定位问题,提出了粒子群结合模拟退火算法优化(Particle Swarm Optimization and Simulated Annealing algorithm,PSO-SA)的RSSI测距模型质心定位算法。该方法首先利用RSSI测距模型计算出传感器网络中节点间的距离,然后选取距离未知节点最近的3个参考节点和已被定位的节点建立以未知节点坐标为参数的数学模型,在求解的过程中采用粒子群结合模拟退火算法进行优化。为了评估所提方法的性能,以传统的质心定位算法、基于RSSI的加权质心定位算法和基于粒子群算法优化的RSSI质心定位算法为对比进行实验。结果表明,较其他3种算法,基于PSO-SA的RSSI质心定位算法具有较高的定位精度、较强的泛化性能。

Sensor nodes self-positioning is one of the most critical technologies in wireless sensor network.Aiming at the localization problem of wireless sensor network,this paper proposed the centroid localization algorithm with particle swarm optimization and simulated annealing algorithm (PSO- SA) based on RSSI.Firstly,the distance between nodes in the wireless sensor network is calculated by using the RSSI ranging model in the method .Secondly,a mathematical model with unknown node coordinates as parameters is established by selecting three reference nodes closest to the unknown node and the nodes that have been located,and PSO-SA is used in the process of solution.To evaluate the performance of the proposed method,a comparison experiment was carried out with the traditional centroid localization algorithm,the RSSI-based weighted centroid localization algorithm and the centroid localization algorithm based on PSO.Experiment results indicate that the RSSI centroid localization algorithm based on PSO-SA has higher localization accuracy and stronger generalization performance than the others.