NLOS环境下基于WSN的救援人员定位系统研究

Research on the location system of rescuers based on WSN in NLOS environment

在大型建筑灾难发生过程中,由于受到有毒烟雾、噪声、大火、漏电、光线等不利因素影响,加上大型建筑内部结构复杂,很多救援人员难以获得可靠的信息。针对上述情况,无线传感器网络在室内复杂环境定位方面可以发挥其优势作用,但目前面临的挑战就是在LOS环境下其定位精度非常高,然而在NLOS环境下其测量可能会受到非视距传播的污染,从而导致定位精度下降。针对这一现象,提出一种改进的无迹卡尔曼滤波(MKF)定位方法。首先,采用检验统计方法识别移动节点和信标节点之间的传播状态。然后,利用线性卡尔曼滤波器(LKF)平滑测量距离,在此基础上利用MKF削弱NLOS对于测量产生的影响。之后,采用无迹卡尔曼滤波(UKF)方法来确定未知移动节点的位置信息。最后通过数值仿真实验验证了所提算法的有效性。

During the process of large building disaster,due to the adverse effects of toxic smoke,noise,fire,electricity leakage,light and other factors,as well as the complex internal structure of large buildings,it is difficult for many rescuers to obtain reliable information.Considering the above situation,wireless sensor networks can play their advantages in positioning indoor complex environments.But there is a challenge.Although their positioning accuracy is very high in the LOS environment,their measurement may be polluted by non-line-of-sight propagation in the NLOS environment,which results in a decrease in positioning accuracy.To solve this problem,we propose an improved location method based on unscented Kalman filter(UKF).Firstly,the propagation state between mobile node and beacon node is identified by means of test statistics.Secondly,the linear Kalman filter(LKF)is used to measure the distance smoothly.On this basis,a modified Kalman filter(MKF)is used to weaken the influence of NLOS on the measurement.Then,the UKF method is used to determine the location information of the unknown mobile node.Finally,the effectiveness of the proposed algorithm is verified by numerical simulation.