基于量子粒子群优化的WSN节点定位改进

Improvement of Node Localization in Wireless Sensor Networks Based on Quantum-behaved Particle Swarm Optimization

针对无线传感器网络定位低成本、低功耗和高精度的要求,在基于接收信号强度(RSSI)测距的基础上,提出了一种量子粒子群优化(QPSO)的改进加权质心定位算法,即采用QPSO优化WCLA的估计坐标来改善定位误差,并改进收缩扩展系数增强QPSO算法的收敛速度。仿真表明,改进的算法与WCLA算法和经过粒子群优化的WCLA算法相比,其节点定位精度得到显著提高,且能克服粒子群优化算法的收敛速度慢、易陷入局部极小值的缺点。

Focusing on the requirements of low cost and high accuracy in wireless sensor network（WSN）, an improvement method of weighted centroid localization algorithm was introduced based on received signal strength indicator（RS- SI） which used the quantum-behaved particle sSwarm optimization（QPSO） to optimize WCLA evaluation coordinates to decrease the localization error,moreover, the convergence rate was quicken by improving expand/contract coefficient. The simulation shows that the localization accuracy of the new algorithm is significantly superior to that of weighted centroid localization algorithm and weighted centroid localization optimized by PSO, and it could also overcome the short-coming of PSO that convergent slowly and easy to fall into local minimum.