一种具有阶段优势的无锚点定位算法

An Anchor-Free Localization Algorithm with Phase Advantages

经典元锚点定位算法存在定位误差大和节点坐标易陷入局部最优的问题.本文提出一种包含两个阶段的无锚点定位算法:第一阶段采用跳数量化方法将节点的通信半径长度量化为多跳,从而建立更小误差的坐标系;第二阶段采用自适应质点弹簧优化算法优化节点的坐标,防止节点坐标在迭代优化时陷入局部最优.仿真结果表明,本文的算法具有阶段优势,比传统算法定位精度高,收敛速度快.

The existing classic anchor-free localization（AFL） algorithms have relatively large localization error and tend to get local optimal value.Therefore,a two-phase improved anchor-free localization（I-AFL） algorithm with phase advantages is proposed.In the first phase of the I-AFL algorithm,a precise coordinate system is established through hop-count quantization,which uses the measured distance information to break the length of node communication radius into multiple hops.The second phase of the I-AFL algorithm uses an adaptive mass-spring optimization algorithm to optimize the node position and prevent the position from falling into local optimum value during the iterative optimization process.Both the theoretical analysis and simulation results show that compared with the traditional algorithm,the proposed algorithm is more precise,robust and converges faster.