Application of improved particle filter algorithm in RFID indoor target tracking

LI JIN-jie; CUI Ying-hua

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Application of improved particle filter algorithm in RFID indoor target tracking

更新时间：2026-09-04

- Application of improved particle filter algorithm in RFID indoor target tracking
- Vol. 36, Issue 6, Pages: 88-92(2019)
- 作者机构：
  
  北京信息科技大学信息与通信工程学院,北京,100101
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2019
- 稿件说明：
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李金杰, 崔英花. 改进的粒子滤波算法在RFID室内目标跟踪中的应用[J]. 微电子学与计算机, 2019, 36(6): 88-92.

LI JIN-jie, CUI Ying-hua. Application of improved particle filter algorithm in RFID indoor target tracking[J]. 2019, 36(6): 88-92.
李金杰, 崔英花. 改进的粒子滤波算法在RFID室内目标跟踪中的应用[J]. 微电子学与计算机, 2019, 36(6): 88-92. DOI：

LI JIN-jie, CUI Ying-hua. Application of improved particle filter algorithm in RFID indoor target tracking[J]. 2019, 36(6): 88-92. DOI：

摘要

针对复杂室内环境下

现有的RFID目标跟踪方法容易受到多径效应和非视距等因素影响

采用典型的粒子滤波算法估计精度低的问题

提出了一种改进的粒子滤波算法.该算法利用了无迹卡尔曼滤波来构造粒子滤波的重要性分布函数

使得重要性分布函数融入最新的观测信息.根据运动模型建立了动态目标的状态方程

将阅读器接收到的信号强度作为观测值建立了观测方程.通过该算法与其他滤波算法相比较

仿真结果表明

该算法有效提高了目标跟踪的精度

增强了目标跟踪系统的稳定性.

Abstract

For the complex indoor environment

the existing RFID target tracking method is easily affected by multipath effect and non-line of sight

The typical particle filter algorithm is used to estimate the low precision

An improved particle filter algorithm is proposed. The algorithm utilizes the unscented Kalman filter to construct the importance distribution function of the particle filter

so that the importance distribution function is integrated into the latest observation information. The state equation of the dynamic target is established according to the motion model

and the observation equation is established by taking the signal strength received by the reader as the observation value. Compared with other filtering algorithms

the simulation results show that the algorithm effectively improves the accuracy of target tracking and enhances the stability of the target tracking system.

关键词

Keywords

references

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