基于动态PSO的WSNs发音节点定位研究

Pronunciation WSNs Node Localization Based on Dynamic PSO

发音节点定位是无线传感器网络(WSN)一项重要的监控任务。为定位发音节点位置的极大似然估计解(MLE),通过分析栅格策略,基于此提出了动态粒子群优化(PSO)的算法,该算法在降低计算量的同时,减少了损失函数局部最优解的影响。另外,相对于原始数据,节点仅仅将信号的能量量测发送到融合中心,大大降低了对通信带宽和能量的消耗。在多种场景下进行了对比仿真,实验结果验证了该算法的优越性能。

To ensure pronunciation node localization is an important monitoring task for WSN. By using maxi- mum likelihood estimation（MLE） to locate pronunciation node position and analyzing grid strategy, the algo- rithm of dynamic PSO is proposed. The amount of calculation is reduced, at the same time, the influence on the local optimal solution loss function is also reduced. In addition, comparing with original data, the energy meas- urement of signals is merely sent to the fusion center by nodes, which greatly reduces the consumption of com- munication bandwidth and energy. Comparative simulation is conducted in various scenarios, and the experi- ment results prove the superior performance of the algorithm.