基于以未知节点为中心的散射体圆盘模型,通过测量电波到达时间和电波达到角信息,对未知节点及其周围的散射体进行初步估计,然后通过反算得出估计的距离值,选取含较小NLOS误差的TOA测量值组,进行数值修正处理,并建立以未知节点为变量的似然函数,最后利用遗传算法对此非线性似然函数寻优求解得到未知节点坐标。计算机仿真结果表明,所提定位方法能有效地抑制NLOS误差,较传统定位方法提高了定位精度,且鲁棒性较好。
One localization method based on the genetic algorithm is proposed in the Unknown Node-oriented Disk of Scatterers Model(UN-DSM)environments for wireless sensor networks. Firstly, the method uses the TOA(Time Of Arrival)and AOA(Angle Of Arrival)measurement information to estimate the positions of scatterers which located in the areas around the estimated node. Secondly, it selects the TOA information sets which consider existing less errors and performs parameters’value modification. Then the math function is built after the value modification. Finally, it solves the non-linear function by genetic algorithm to get the position of the unknown node. Simulation results show that the pro-posed location method can restrain NLOS error effectively, and has better location accuracy than the traditional location methods with good robustness.