基于粒子群优化的无线传感器网络非视距节点定位算法

针对室内环境中传感器节点间的非视距传播会降低定位精度的情况，研究基于无线传感器网络的非视距节点定位方法。根据不同环境下信标节点的测量模型和视距传播概率建立目标函数，采用粒子群优化算法估计出未知节点的位置，将利用最小二乘法计算出的节点位置作为粒子的初始位置。仿真结果表明，通过与最小二乘法、残差加权和RANSAC算法相比较，所提出算法能够较好地削弱非视距误差，且具有更高的定位精度。

Non-line of sight node localization algorithm based on particle swarm optimization for wireless sensor networks

The localization accuracy can be degraded considerably due to the existence of non-line of sight(NLOS) propagation between the sensor nodes in indoor environment. Therefore, the NLOS node localization method is investigated for wireless sensor networks. The objective function is established according to the measurement models of beacon nodes and LOS(line of sight) propagation probability in different environment. The particle swarm optimization method is employed to estimate the position of the unknown node, and the least square method is used to compute the node position as the initial position of the particle. The simulation results show that the proposed method has higher localization accuracy in comparison with the least square method, the residual weighting algorithm(Rwgh) and random sample consensus(RANSAC) methods.