ZigBee indoor positioning system precision parameter study based on BP neural network
文献类型：会议论文
| 作者 | Zeng Wenxiao ; Wang Yanen ; Wang Meng ; Guo Ye |
| 出版日期 | 2013 |
| 会议名称 | International Conference on Computer, Networks and Communication Engineering (ICCNCE) |
| 会议日期 | MAY 23-24, 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 |
| 页码 | 339-342 |
| 中文摘要 | 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. |
| 会议录出版地 | ATLANTIS PRESS |
| 语种 | 英语 |
| ISSN号 | 1951-6851 |
| ISBN号 | 978-90-78677-67-3 |
| 源URL | [http://ir.xjipc.cas.cn/handle/365002/3593]  |
| 专题 | 新疆理化技术研究所_多语种信息技术研究室 |
| 推荐引用方式 GB/T 7714 | Zeng Wenxiao,Wang Yanen,Wang Meng,et al. ZigBee indoor positioning system precision parameter study based on BP neural network[C]. 见:International Conference on Computer, Networks and Communication Engineering (ICCNCE). Beijing, PEOPLES R CHINA. MAY 23-24, 2013. |
入库方式： OAI收割
来源：新疆理化技术研究所
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