摘要
针对目前的被动式目标人员轨迹跟踪方法计算开销大,算法复杂度高等问题,提出了一种基于信道状态信息CSI(Channel State Information)的被动式目标人员跟踪方法。该方法在离线阶段采集细粒度的CSI数据,建立离线指纹数据库;在线阶段,将实时数据与离线数据库中的数据利用融合了卡尔曼滤波的KNN位置指纹算法进行匹配,实现目标人员轨迹跟踪。实验结果表明该方法可以更精确的跟踪目标人员的轨迹,跟踪可靠性更高。
The current target for passive personnel tracking method for calculating the cost of large,high complexity algorithm and other issues,this paper presents passive target trajectory personnel based channel state information(Channel State Information,CSI)tracking method. The method collects fine-grained CSI data in the off-line phase,uses Kalman constructive filtering algorithm to perform filtering processing,and establishes an offline fingerprint database. In the online phase,the Kalman filter is combined with real-time data and data utilization in the offline database. KNN position of fingerprint matching algorithm to achieve trajectory tracking personnel. The experimental results show that the trajectory of the target personnel can be tracked more accurately in this method,and the tracking reliability is higher.
作者
郝占军
颜丽华
党小超
HAO Zhanjun;YAN Lihua;DANG Xiaochao(College of Computer Science and Engineering,Northwest Normal University,Lanzhou 730070,China;Gansu Province Internet Of Things Engineering Research Center,Lanzhou 730070,China)
出处
《传感技术学报》
CAS
CSCD
北大核心
2019年第7期1063-1069,共7页
Chinese Journal of Sensors and Actuators
基金
国家自然科学基金项目(61762079,61662070)