一种采用距离/距离变化率的室内跟踪算法

A New Approach for Indoor Tracking Using Range and Range Rate

为了提高室内跟踪模型的精度和可靠性,本文提出了一种采用距离/距离变化率的改进型模型。这种模型采用扩展卡尔曼滤波(EKF)对盲节点的位置和速度进行最优估计,并且盲节点到参考节点的距离及其对应的距离变化率作为EKF的观测量。同时,本文还将提出模型的能观性与传统模型进行了比较分析。仿真结果表明,与传统模型相比较,本文提出的模型对位置和速度的预估精度有明显提高。

In order to improve the accuracy and reliability of indoor tracking model, this paper presents an improving model using range and range rate. In this mode, the Extended Kalman Filter （EKF） is used to provide optimal estimation of position and velocity for Blind Node （BN）, and the distance between the Reference Nodes （RNs） and the BN as well as its changing rate are used as observables for EKF. Meanwhile, the analysis of observability of the proposed mode and the traditional model is proposed. The simulation results show that the proposed model has better performance in the estimation for the position and velocity, compared with the traditional model.