Díez-González Javier, Álvarez Rubén, Sánchez-González Lidia, Fernández-Robles Laura, Pérez Hilde, Castejón-Limas Manuel
Department of Mechanical, IT and Aerospace Engineering, Universidad de León, 24071 León, Spain.
Positioning Department, Drotium, Universidad de León, 24071 León, Spain.
Sensors (Basel). 2019 Jun 29;19(13):2892. doi: 10.3390/s19132892.
Time difference of arrival (TDOA) positioning methods have experienced growing importance over the last few years due to their multiple applications in local positioning systems (LPSs). While five sensors are needed to determine an unequivocal three-dimensional position, systems with four nodes present two different solutions that cannot be discarded according to mathematical standards. In this paper, a new methodology to solve the 3D TDOA problems in a sensor network with four beacons is proposed. A confidence interval, which is defined in this paper as a sphere, is defined to use positioning algorithms with four different nodes. It is proven that the separation between solutions in the four-beacon TDOA problem allows the transformation of the problem into an analogous one in which more receivers are implied due to the geometric properties of the intersection of hyperboloids. The achievement of the distance between solutions needs the application of genetic algorithms in order to find an optimized sensor distribution. Results show that positioning algorithms can be used 96.7% of the time with total security in cases where vehicles travel at less than 25 m/s.
在过去几年中,到达时间差(TDOA)定位方法因其在本地定位系统(LPS)中的多种应用而变得越来越重要。虽然确定一个明确的三维位置需要五个传感器,但具有四个节点的系统存在两种不同的解决方案,根据数学标准无法舍弃。本文提出了一种新的方法来解决具有四个信标的传感器网络中的三维TDOA问题。本文定义了一个置信区间,将其定义为一个球体,用于使用具有四个不同节点的定位算法。事实证明,四信标TDOA问题中解之间的分离使得该问题能够转化为一个类似的问题,由于双曲面相交的几何特性,该问题涉及更多的接收器。要实现解之间的距离,需要应用遗传算法来找到优化的传感器分布。结果表明,在车辆行驶速度小于25米/秒的情况下,定位算法可以在96.7%的时间内完全安全地使用。