摘要
为了对无线传感器网络中随机分布的节点进行更精确的定位,提出了一种基于改进粒子群算法和增强定位机制的新型定位算法。新算法先提出竞争进化思想和自适应权重,使得改进后的粒子群算法在加快收敛速度的同时增强了算法的全局和局部搜索能力;增强定位机制使得算法对锚节点信息的使用更加充分,而且极大缩小可行解空间,进一步加快了算法的搜索速度。仿真结果表明:所提定位算法具有更低的定位成本和更高的定位精度,同时具有对测距误差鲁棒性强的优点。
In order to obtain the geographic positions of random nodes in wireless sensor network (WSN) more ac- curately, a new localization algorithm is proposed based on improved Particle Swarm Optimization (PSO) and the usage mode of the algorithm is improved. The new algorithm proposes the idea of competition evolution and adaptive weighting; this can enhance the global and local search ability and meanwhile can improve convergence speed. And the new usage mode makes full use of anchor node information. Simulation results and their analysis show preliminarily that the new algorithm is less costly, gives higher location accuracy, and shows robustness to measurement error.
出处
《西北工业大学学报》
EI
CAS
CSCD
北大核心
2013年第4期633-638,共6页
Journal of Northwestern Polytechnical University
基金
中国博士后科学基金项目(2012M512026)
陕西省自然科学基金(2012JQ8005)资助
关键词
无线传感器网络
节点定位
优化算法
粒子群优化
wireless sensor networks, localization, particle swarm optimization(PSO)
improved PSO