ISSN 1000-1239 CN 11-1777/TP

• 网络技术 •

### 基于时间序列启发式信息的室内轨迹跟踪算法

1. 1(东北大学计算机科学与工程学院 沈阳 110819); 2(内蒙古工业大学信息工程学院 呼和浩特 010080) (qinjunping30999@sina.com)
• 出版日期: 2017-12-01
• 基金资助:
国家自然科学基金项目(61472072，61540004)；内蒙古自然科学基金项目(2015MS0619，2013MS0920)；内蒙古高等学校科学研究项目(NJZY091)

### Indoor Trajectory Tracking Algorithm Based on Time Series Heuristic Information

Qin Junping1,2, Deng Qingxu1, Sun Shiwen2, Renqing Daoerji2, Tong Haibin1, Su Xianli1

1. 1(School of Computer Science and Engineering, Northeastern University, Shenyang 110819); 2(College of Information Engineering, Inner Mongolia University of Technology, Hohhot 010080)
• Online: 2017-12-01

Abstract: Existing indoor trajectory tracking algorithms on wireless sensor network are based on continuous localization and can not make use of the heuristic information of RSSI time series within a certain temporal and spatial range. The heuristic information of RSSI time series is a key factor of trajectory tracking procedure. This paper proposes a new trajectory tracking algorithm on spatiotemporal correlation model based on heuristic information. According to the heuristic information related to moving trajectory, the new method contains the following essential phases. Firstly, we model the trajectory tracking model reflecting spatiotemporal correlation and statistical characteristics. Secondly, we detect spanning boundary event and judge which subarea the unknown node was in by means of information fusion of RSSI time series and moving least square method. Finally, the moving trajectory of unknown node is formed by means of dynamic time warping fingerprinting matching algorithm with heuristic information constraints. The principles of information fusion are strictly proved in mathematics. The field experiments and the simulation experiments show that the algorithm has good environment adaptability, smooth trajectory and the error does not accumulate among the subareas. Compared with the existing methods, the accuracy of trajectory tracked is improved.