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题名: ZigBee indoor positioning system precision parameter study based on BP neural network
作者: Zeng Wenxiao ; Wang Yanen ; Wang Meng ; Guo Ye
会议名称: International Conference on Computer, Networks and Communication Engineering (ICCNCE)
会议日期: MAY 23-24, 2013
出版日期: 2013
会议地点: Beijing, PEOPLES R CHINA
关键词: CC2431 ; Zigbee location ; BP Neural Network ; Euclidian distance centroid algorithm ; multi-target detection indoor
出版地: ATLANTIS PRESS
ISSN: 1951-6851
ISBN: 978-90-78677-67-3
部门归属: [Zeng Wenxiao
摘要: With the developing of wireless sensor networks (WSNs), more application approach have greatly encouraged the use of sensors for multi-target tracking. The high efficiency detection and location monitoring are crucial requirements for multi-target tracking in a WSN of indoor environment, especially the situation without the GPS application. In this paper, we proposed an indoor tracking model using Zigbee of IEEE 802.15.4 compliant radio frequency to monitor targets in a special way. Our motivation is to manipulate the erratic or unstable received signal strength indicator (RSSI) signals to deliver the stable and precise position information in the indoor environment. Based on BP neural network methodology, the selective algorithm for WSN parameters A and n values is demonstrated in this paper. An improvement Euclidian distance centroid location algorithm based on statistical uncorrelated vectors to minimize the noise in RSSI values has also been proposed here. Much more experiments about multi-target detection and location to verify the BPNN methodology can effectively improve selecting those A and n parameters in the WSN network. The system architecture, hardware and software organization, as well as the solutions for multiple-targets tracking, RSSI interference and location accuracy have been introduced in details.
语种: 英语
内容类型: 会议论文
URI标识: http://ir.xjipc.cas.cn/handle/365002/3593
Appears in Collections:多语种信息技术研究室_会议论文

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