摘要
在物联网时代,跟踪定位室内环境中物体至关重要。针对接收信号强度指示(RSSI)定位方差大和惯性测量单元(IMU)定位存在累积误差的问题,研究并实现了一种使用容积卡尔曼滤波算法对RSSI定位和IMU定位进行数据融合的方法。以ZigBee开发板为RSSI的硬件载体,采用质心定位法将RSSI转换为坐标信息;待测目标搭载MPU9250提供IMU数据,并进行室内跟踪定位实验;使用容积卡尔曼滤波算法对实验数据进行改进,并与原坐标信息数据进行对比。结果显示,使用了容积卡尔曼滤波算法后的改进数据相比原数据在精确度上提高了20.8%。该定位系统具有一定的实用价值。
In the era of Internet of Things,tracking and locating objects in the indoor environment is very important.Aiming at the problem of large variance of received signal intensity indication(RSSI)location and cumulative error of Inertial measurement unit(IMU)location,a data fusion method for RSSI location and IMU location using volumetric Kalman filter algorithm was studied and implemented.Using the ZigBee development board as the hardware carrier of RSSI,the centroid positioning method is used to convert RSSI into coordinate information.The target to be tested is equipped with MPU9250 to provide IMU data and conduct indoor tracking and positioning experiments.Volume Kalman filter algorithm is used to improve the experimental data and compare with the original coordinate information data.The results show that the accuracy of the improved data after using the volumetric Kalman filter filter algorithm is 20.8%higher than that of the original data.This positioning system has certain practical value.
作者
沈东徽
卜雄洙
SHEN Donghui;BU Xiongzhu(School of Mechanical Engineering,Nanjing University of Technology,Nanjing 210094,China)
出处
《仪表技术》
2024年第1期48-52,69,共6页
Instrumentation Technology
