| 研究生: |
徐翊嘉 Yi-Jia Hsu |
|---|---|
| 論文名稱: |
無線感測網路旋轉指向天線定位法 Localization with Rotatable Antennas for Wireless Sensor Networks |
| 指導教授: |
江振瑞
Jehn-Ruey Jiang |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
資訊電機學院 - 資訊工程學系 Department of Computer Science & Information Engineering |
| 畢業學年度: | 98 |
| 語文別: | 中文 |
| 論文頁數: | 47 |
| 中文關鍵詞: | 無線感測網路 、指向天線 、定位 |
| 外文關鍵詞: | Wireless Sensor Network, Localization, Directional |
| 相關次數: | 點閱:14 下載:0 |
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本論文提出一個利用指向性天線(Directional antenna)特性來完成無線感測器定位的新方法。在我們的方法中,使用兩個錨節點(Anchor node),裝置可旋轉的指向性天線,錨節點不斷旋轉並送出信標(beacon),感測器觀察錨節點送出信標的接收訊號強度(received signal strength Indicator, RSSI)變化,獲取本身與錨節點的角度,進而計算出位置。根據指向天線的特性,我們提出五種計算角度的方式,並透過實驗來分析各種方法的優缺點,找出其中最佳的方法-最強訊號強度法-用以完成定位方法實作。我們在室內體育館中實際測量定位方法的精確程度,實驗分成角度測量以及位置測量,在角度測量的部分,80%的誤差在6度以內;位置測量部分,在一個長寬各10公尺的環境下,定位的平均位置誤差是70~90公分左右。最後,為了進一步增加定位的精確程度,我們利用增加錨節點的方式,提出兩種修正方法,尋找距離線段和最小的位置。第一個方法是田字型逼近法,利用畫分隔點的方式,在畫分的格點中選擇最佳點,並繼續逼近;另一個是向量逼近法,求出起始點與其它線的法向量和,沿求出向量的方向步步逼近,求出修正後的位置,我們將角度誤差測量的誤差百分比模擬修正方法,發現修正方法能夠對原始誤差有10%的修正效果。
In this paper we show the design and implementation of a novel localization scheme, called Rotatable Antenna Localization (RAL), for wireless sensor networks with anchor nodes with directional antennas which rotate regularly. An anchor node periodically sends beacon signals containing its position and antenna direction. By observing the variation of the received signal strength indicator (RSSI) values of the beacon signals, a sensor node can estimate its orientation relative to the anchor node. With the estimated angles to two distinct anchor nodes, a sensor can calculate its own location. Four methods are implemented for the sensor node to estimate its orientations. Among them, the strongest signal (SS) method has the most accurate orientation estimation. With SS method, we implement RAL scheme and apply it to a WSN in a 10- by 10-meter indoor environment with two anchor nodes at two ends of a side. Our experiment demonstrates that the average position estimation error of RAL scheme is 70~90 centimeters. We further propose two methods, namely grid-based approximation and vector-based approximation methods, to improve RAL by installing more than two anchor nodes. We show by simulation that the improvements can reduce about 10% of the position estimation error
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