基于几何约束关系的ML模型求解三维坐标定位问题研究

为了提高三维空间位置定位算法的性能和准确性,提出了以3个基站定位原理为基础的基于几何约束关系的ML模型.通过设计基站位置、到达时间(time of arrival,TOA)数值、手持终端位置之间的几何关系,估计得到手持终端的全部可能位置,通过最大似然算法,以最大可能的估计值确定为定位结果.经过仿真计算验证了算法能有效抑制非视距环境(non-line of Sight,NLOS)误差和测量误差,并且能够得到最佳估计值,具有计算量小、精度高等优点.仿真结果表明了该方法的有效性,在各类室内定位系统中具有很强的实用性.

Research on 3D Coordinate Localization based on ML Model with Geometric Constraint Relation

In order to improve the performance and accuracy of the 3D spatial location algorithm,this paper proposes a ML model based on the geometric constraint relationship based on the positioning principle of three base stations.Through the design of base station location,TOA,handheld terminal numerical geometric relationship between locations,estimated by the handheld terminal all possible position,through the maximum likelihood algorithm to estimate the maximum possible value to determine the positioning results.The simulation results show that the algorithm can effectively suppress the NLOS error and the measurement error,and can get the best estimation value.The simulation results show the effectiveness of the proposed method,and it has strong practicability in various indoor positioning systems.