HE Junyi, GUO Kai, ZHANG Min. Indoor positioning algorithm based on improved IMM motion model[J]. 2021, (5): 150-153. DOI: 10.13873/J.1000-9787(2021)05-0150-04.
基于改进IMM运动模型的室内定位算法
摘要
针对目标运动状态改变会导致目标跟踪算法精度下降甚至发散的问题
提出了一种基于交互式多模型(IMM)的目标跟踪算法。首先
IMM改进算法融合了非机动模型和Singer模型
Singer模型通过改变机动频率和加速度方差可以较好地适应强机动目标。其次
针对初始定位数据精度低的问题
采用到达时间差(TDOA)算法对定位数据进行初步估计
TDOA算法在视距环境下具有较高精度和较低的计算复杂度。实验结果表明:相比于传统IMM滤波算法
改进后的IMM算法能有效提高定位精度
实现了对目标的稳定跟踪。
Abstract
Aiming at the problem that the target motion state changes the accuracy or even the divergence of the target tracking algorithm
an object tracking algorithm based on interactive multiple model(IMM) is proposed.First
the IMM improvement algorithm combines the non-maneuver model with the Singer model.The Singer model can better adapt to the strong maneuvering target by changing the maneuver frequency and acceleration variance.Secondly
for the problem of low accuracy of initial positioning data
the time difference of arrival(TDOA)algorithm is used to estimate the positioning data.The TDOA algorithm has higher precision and lower computational complexity in the line-of-sight environment.The experimental results show that compared with the traditional IMM filtering algorithm
the improved IMM algorithm can effectively improve the positioning accuracy and achieve stable tracking of the target.