Kalman滤波在井下人员跟踪定位中的应用

基金项目:

国家自然科学基金资助项目（60850004）

详细信息

Application of Kalman filter in underground personnel tracking and positioning

1.
School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454003, China
2.
School of Safety Science and Engineering, Henan Polytechnic University, Jiaozuo 454003, China

摘要: 针对基于RSSI定位算法在定位过程中不具备连续性问题，提出了一种基于Kalman滤波的连续性井下人员定位方法。采用Kalman滤波对基于RSSI定位算法估算出的井下人员位置坐标进行滤波处理，在此坐标的基础上，建立Kalman滤波模型，利用Kalman滤波实现对井下人员的实时跟踪。实验结果表明，基于Kalman滤波的定位方法对井下人员的跟踪效果较好，提高了系统的实时性和跟踪精度。
- 煤矿井下 /
- 人员定位 /
- RSSI定位算法 /
- Kalman滤波定位 /
- 实时跟踪
Abstract: In view of problem that RSSI location algorithm does not have continuity in positioning process, the paper proposed an underground personnel positioning method with continuity based on Kalman filter. The method adopts Kalman filter to filter processing position coordinates of underground personnel estimated by RSSI location algorithm, and established a Kalman filter model on the basis of this coordinate in order to real-timely track underground personnel. The experimental results show that the positioning method based on Kalman filter has accurate tracking effect, and can improve real-time performance and tracking accuracy of underground personnel tracking and positioning system.
- coal mine underground /
- personnel positioning /
- RSSI location algorithm /
- Kalman filter location /
- real-time tracking