基于散射体信息的室内NLOS单基站定位算法

Ya Wang, Zenshan Tian, Ze Li, Sheng Li
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引用次数: 1

摘要

针对室内非视距(NLOS)环境下的定位问题,提出了一种基于散射体信息的单基站定位算法。首先,根据室内场景的先验信息,得到散射体的分布范围;其次,选取一条路径的飞行时间TOF (Time of Flight TOF, TOF)作为参考,将剩余路径的TOF相减,构成差分TOF,从而消除了因收发端异步引起的相位误差。同时,根据各路径的AOA和散射体的分布范围,进一步确定散射体的位置范围。然后,利用差分TOF构造非线性定位目标方程,并将其转化为非线性最小二乘优化问题。最后,采用遗传算法(GA)对目标进行初步定位,并采用改进的高斯牛顿(G-N)算法对目标进行精确定位;仿真结果表明,该算法能有效解决室内近距离定位环境下的单站定位问题。
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Indoor NLOS Single Base Station Localization Algorithm Based on Scatterer Information
Aiming at the localization problem of indoor Non-Line-of-Sight (NLOS) environment, a single base station localization algorithm based on scatterers information is proposed in this paper. Firstly, according to the priori information of indoor scene, the distribution range of scatterers is obtained. Secondly, the Time of Flight TOF (TOF) of a path is selected as a reference, the TOF of the remaining path subtract it to construct difference TOF, thus eliminating the phase error caused by asynchronous receiver and transmitter. At the same time, the location range of the scatterers is further determined according to the AOA of each path and the distribution range of the scatterers. Then, the nonlinear localization target equation is constructed by the difference TOF, and the equation is further transformed into a nonlinear least squares optimization problem. Finally, Genetic Algorithm (GA) was used to preliminarily locate the target, and the modified Gaussian Newton (G-N) algorithm was used to accurately locate the target; Simulation results show that this algorithm can effectively solve the problem of single station Localization in indoor NLOS environment.
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