非视距环境下的协作定位节点选择算法

Node Selection Algorithm for Cooperative Localization in NLOS Conditions

协作网络中终端节点的广泛协作容易引起定位误差的大规模扩散和非线性累积.在非视距环境下,为了使待定位的终端节点可以从周围节点中选择最佳的节点进行协作,提出了基于费舍尔信息矩阵的协作节点选择算法.该算法所使用的节点评估标准可以衡量参考节点对待定位节点位置估计精度的影响,从而使终端节点可以选择合适的子集进行协作,以减小定位误差和定位消耗的系统资源,包括消耗的能量、信道利用率等.仿真验证了该选择算法通过选择少量的节点就可以实现高精度的定位,并提高了协作定位算法的收敛速度.

The extensive cooperation of terminal nodes in cooperative network can easily cause large-scale diffusion and nonlinear accumulation of positioning errors.In the NLOS environment,in order to en-able the terminal node located to select the better nodes from surrounding nodes to cooperate,a coopera-tive node selection algorithm is proposed based on Fisher information matrix.The algorithm can make the target that to be located select partial nodes from surrounding nodes to take part in cooperation.The selec-tion metric used in the algorithm can evaluate the influence of reference nodes on the accuracy of position estimation.Thus,the terminal nodes can choose the appropriate subset to minimize the positioning error and positioning consurmption of the system resources,including the consumed energy,channel utilization and so on.Simulation results show that the proposed algorithm can achieve high precision positioning by selecting a few of nodes,and improve the convergence speed of cooperative localization algorithm.