摘要
针对传统定位技术误差较大且无法预测目标位置等问题,提出了一种结合运动方程与卡尔曼滤波的动态目标追踪预测算法ME-KF。通过运动方程模拟动态目标运动特性,利用卡尔曼滤波来减小干扰噪声对测量结果的影响,并预测下一时刻的目标位置。该算法在辽宁排山楼矿井的人员定位系统中得到了实际应用,并取得了显著成果。实验结果表明,该方法提高了定位精度,能够对人员位置进行预测以及对危险区域进行预警,并且成功地分析判断了障碍物的分布状况。
In the view of problem that the traditional location technology is erroneous greatly, and can not predict the position of the target, this paper presented a dynamic target tracking and predicting algorithm ME-KF combining motion equation and Kalman filter, which simulates the motion characteristics of dynamic target by motion equation, reduces the influence of noise on the measurement results and predicts the position of the target in the next moment. This algorithm has been practically applied to personnel location system of Liaoning Paishanlou mine and has made remarkable achievements. The experimental results show that this method improves the precision of location, predicts people positions, makes early warning of possibly dangerous areas, and can also successfully analyze the distribution of obstacles.
出处
《计算机科学》
CSCD
北大核心
2015年第12期76-81,共6页
Computer Science
基金
国家自然科学基金(61472072)
国家科技支撑计划(2012BAF13B08)
国家"九七三"重点基础研究发展计划前期研究专项(2014CB360509)
辽宁省科学事业公益研究基金项目(2015003003)资助
关键词
无线定位
运动方程
卡尔曼滤波
动态目标
Wireless location, Motion equation, Kalman filter, Dynamic target
