[1]倪云峰,石小红.RSSI的室内人员卡尔曼滤波定位算法[J].西安科技大学学报,2020,(01):167-172.
 NI Yun-feng,SHI Xiao-hong.Indoor staff kalman filter location algorithm based on RSSI[J].Journal of Xi'an University of Science and Technology,2020,(01):167-172.
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RSSI的室内人员卡尔曼滤波定位算法(/HTML)
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西安科技大学学报[ISSN:1672-9315/CN:61-1434/N]

卷:
期数:
2020年01期
页码:
167-172
栏目:
出版日期:
2020-02-15

文章信息/Info

Title:
Indoor staff kalman filter location algorithm based on RSSI
文章编号:
1672-9315(2020)01-0167-06
作者:
倪云峰石小红
(西安科技大学 通信与信息工程学院,陕西 西安 710054)
Author(s):
NI Yun-fengSHI Xiao-hong
(College of Communication and Information Engineering,Xi'an University of Science and Technology,Xi'an 710054,China)
关键词:
室内人员定位 接收信号强度 卡尔曼滤波 六点定位
Keywords:
indoor personnel positioning RSSI Kalman filtering six o'clock position
分类号:
TN 929.5
文献标志码:
A
摘要:
RSSI定位技术的室内定位算法中,由于室内环境的复杂性及人员的随机性等因素可能会带有噪声影响,所以需要加以抑制。本次设计的室内定位算法首先根据室内特殊环境设计出定位算法流程图,建立算法模型并用卡尔曼滤波算法来抑制环境中噪声因素所引起的误差,然后结合改进的RSSI算法实现室内移动人员的定位,使得定位的结果更接近于真实值。重点研究将卡尔曼滤波算法与改进的RSSI算法相结合估算出更精确的室内人员位置信息。通过实验表明,结合卡尔曼滤波改进的室内人员定位算法的定位精确度有明显的提升,误差相比于文献9所提出的定位算法有所降低。
Abstract:
Due to the complexity of the indoor environment and the randomness of personnel,there may be noise effects in the indoor positioning algorithm based on RSSI positioning technology,so it needs to be suppressed.In this design,the indoor positioning algorithm firstly designs the positioning algorithm flow chart according to the special environment of the room,establishes the algorithm model and uses the Kalman filter algorithm to suppress the error caused by the noise factor in the environment,and then combines the improved RSSI algorithm to realize the positioning of indoor mobile personnel,which makes the result of the positioning closer to the true value.This paper focuses on the estimation of more accurate indoor position information by combining the Kalman filter algorithm with the improved RSSI algorithm.Experiments show that the positioning accuracy of the improved indoor personnel positioning algorithm combined with Kalman filtering is significantly improved,and the error is reduced compared with the positioning algorithm proposed in literature 9.

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备注/Memo

备注/Memo:
收稿日期:2019-06-12 责任编辑:高 佳
基金项目:国家自然科学基金(61603295); 陕西省自然科学基础研究计划(2018JM6003)
通信作者:邵小强(1976-),男,陕西商州人,博士,副教授,E-mail:shaoxq@xust.edu.cn
更新日期/Last Update: 2020-02-15