Positioning and Calibration Method of Underground Personnel Based on Priori Features
YUAN Yazhou①② SUN Xiaoqin① LI Yuefeng① GUAN Xinping③
①(School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China) ②(Key Laboratory for Industrial Computer Control Engineering of Hebei Province, Qinhuangdao 066004, China) ③(Institute of Electronic Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai 200240, China)
Abstract：Focusing on the problem that the personnel positioning methods are seriously influenced by the indoor environment, big cumulative error and other issues, a method is proposed to correct the position, which combines the prior knowledge of the map and the heading recognition. Firstly, the dimension of the feature set is reduced by Linear Discriminant Analysis (LDA). Then, the heading of the underground personnel is classified and the special points are marked through combining Random Forest (RF) and the method of setting a threshold value. Finally, the movement trajectory of the underground personnel, which is obtained by the Pedestrian Dead Reckoning (PDR) algorithm, is corrected and updated by matching the special point with the prior knowledge of the roadway structure. The experimental results show that the pre-processing method of LDA can effectively improve the precision of the classifier by more than 6%. The proposed method can effectively reduce the cumulative error, with high accuracy and robustness. The activity recognition accuracy can reach 98%, which can achieve reliable real- time location.
袁亚洲,孙小芹,李岳峰,关新平. 基于先验特征的矿下人员定位校准方法[J]. 电子与信息学报, 2018, 40(6): 1323-1329.
YUAN Yazhou, SUN Xiaoqin, LI Yuefeng, GUAN Xinping. Positioning and Calibration Method of Underground Personnel Based on Priori Features. JEIT, 2018, 40(6): 1323-1329.
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