無線感測網路為基礎之空間平面圖自動建構之技術

Technology of Automatic Floor Plan Construction Using Wireless Sensor Networks

龍冠志(Kuan-chih Lung)

指導教授 ： 許獻聰

國立中央大學/資訊電機學院/通訊工程學系/碩士(2008年)

摘要

無線感測網路是近年來相當熱門的研究課題，尤其是對於室內定位的應用。 定位的方式有相當多，舉凡GPS、AOA、TOA、TDOA 與RSS 等等，然而訊號的反射以及對牆的衰減等等因素影響，前四者較適用於室外定位，加上需要額外硬體成本，RSS 反而成功吸引眾人目光。 以往定位應用專注於給予數個已知參考座標，藉由與參考點之間訊號強度關聯性來估計出待測目標相對座標。然而我們提出一個新的想法，希望藉由無線感測節點相互溝通建構出未知空間之平面圖。據我們所知，此項應用研究於感測網路領域實屬相當新奇創新。當空間平面圖成功建構並顯示後，我們能詳細了解各個感測點位置；透過螢幕圖像清楚地管理及操控室內空間中任一個節點的狀態，例如回報溫濕度或開關啟動等等。 論文當中，我們將量測觀察接收訊號強度與距離比之特性與衰減關係、探討空間建構演算法並列舉多種定位方式之利弊。最後使用本實驗室空間當作範例進行佈點實測、展示結果並分析比較。

關鍵字

室內定位 ； 無線感測網路 ； 接收訊號強度 ； 三點定位 ； 最大似然估計

並列摘要

Wireless Sensor Network (WSN) is one of the popular research subjects in recent years, especially for the indoor positioning application. Many solutions are applied in the following, for instances, Global Positioning System (GPS), Angle-Of-Arrival (AOA), Time-Of-Arrival (TOA), Time-Difference-Of-Arrival (TDOA) and Received Signal Strength (RSS), etc. Because of signal reflection, wall attenuation and extra hardware required, frontal four methods are suitable for outdoors only. On the contrary, RSS is an instinct approach and attractive for indoor environment.
In the past years, the application of location estimation focuses on locating an observed target by given several reference landmarks. However, we bring up a fascinating idea of using wireless sensor nodes to automatically construct the floor plan of an unknown indoor space. To our best knowledge, this is the first investigation to this field. Once floor plan is constructed and displayable, we can then precisely know the location of deployed sensor nodes and control/monitor any sensor node,
such as temperature/humidity reporting or on-off switching, by selecting/observing the location GUI window.
In the thesis, we first measure the characteristics of RSS as a function of the distance. After then, we introduce the room construction algorithm. As the floor plan construction is done, the methods of location positioning are addressed. For evaluations, we use MWNL (Mobile and Wireless Network Lab) Lab in NCU (National Central University) as an experimental example to show the derived results.

並列關鍵字

indoor location ； wireless sensor network ； received signal strength ； maximum likelihood estimation

參考文獻

Zigbee Alliance, http://www.Zigbee.org. Zigbee Specification 1.0, Dec. 2004.

P. Bahl and V. N. Padmanabhan. “RADAR: An in-building RF-based user location and tracking system.” In Proc. IEEE Infocom, pages 775–784, Tel-Aviv, Israel, April 2000.

C. Hyunggi, K. Myungseok, P. Jonghyuk, P. Byungsung, K. Hagbae,“Performance Analysis of Location Estimation Algorithm in Zigbee Networks Using Received Signal Strength.” AINAW. May. 2007.

T. S. Rappaport, Wireless Communications: Principles and Practice,Englewood Cliffs, NJ: Prentice-Hall, 1996.

A. Sikora and V. F. Groza, “Coexistence of IEEE802.15.4 with other Systems in the 2.4 GHz-ISM-Band.” IMTC. May 2005.