臺灣博碩士論文加值系統

在無線感知網路相關的應用及協定中，位置資訊佔有很重要地位。無線感知網路中，每一個裝置在傳送資訊時，資料中通常伴隨著位置資訊，以增加資料的可用度。較容易取得位置資訊的方法是利用手動設定和在感知器上安裝GPS接收器，但容易花費較多的時間以及資源。所以較好的做法是利用定位演算法進行位置估測。在室外的環境中，無線感知網路通常散佈於非凸面型的區域內，容易影響位置估測的精確度，我們將網路分割為階層式架構，以分散集中式演算法所需消耗的資源以及減少非凸面型區域所造成的影響，並使用多元尺度法來取得感知器之間的相對位置，在這個方法中我們只需要區域性資訊而不需要使用全域性資訊；在室內的環境中，訊號強度容易遭受障礙物的遮蔽或多重路徑的衰減，導致無法依靠訊號強度取得感知器之間精確的距離。利用Sequence-based定位演算法可以有效的避免障礙物的遮蔽以及多重路徑的衰減所造成的影響，我們提出將訊號強度切割為數個階層，利用區分感知器所接收到的訊號強度，以增進Sequence-based定位演算法的精確度。由模擬實驗中可以發現，我們所提出來的定位演算法可以有效的提高定位的精確度。

There are many applications and protocols of wireless sensor network, location information has taken an increasingly important seat. The general way to obtain location information is either to set up manually or to install GPS. Prior to deploying sensors, manual setting will waste a vast amount of time and human resources. However, expenses for making sensors increase due to GPS and GPS can't be utilized indoor although GPS can gather precise location information. A better way to get location information is to use the localization algorithm. Consumed resources of the centralized algorithm are distributed through network clusetering, and relative locations of sensors are recorded by using Multi-Dimensional Scaling, MDS. Consequently, all we require is only local information so that we are able to decrease consumption of resources and improve localization accuracy.

1. 簡介 1
1.1 背景 1
1.1.1 無線感知網路 1
1.1.2 無線感知網路的應用 3
1.1.3 無線感知網路的定位 6
1.2 研究動機 9
1.3 研究目的及方法 10
1.4 章節安排 11
2. 相關研究 12
2.1 PROPERTIES OF LOCALIZATION AND POSITIONING PROCEDURES 12
2.2 距離估測 13
2.3 HOP-COUNT BASED APPROACHES 17
2.4 MDS-BASED APPROACHES 20
2.5 SEQUENCE-BASED APPROACHES 22
2.6 BOUNDING BOX-BASED APPROACH 23
3. 室外定位: A HIERARCHICAL MDS-BASED LOCALIZATION ALGORITHM IN WIRELESS SENSOR NETWORKS 25
3.1 多元尺度法 25
3.2 HIERARCHICAL MDS-BASED LOCALIZATION ALGORITHM 27
3.2.1 Clustering Phase 32
3.2.2 Intra-cluster Localization Phase 33
3.2.3 Merge Phase 35
3.3 模擬實驗 41
3.4 總結 45
4. 室內定位: PLACE: POWER-LEVEL AWARE SEQUENCE-BASED LOCALIZATION ESTIMATION ALGORITHM IN WIRELESS SENSOR NETWORKS 47
4.1 SEQUENCE-BASED LOCALIZATION ALGORITHM 49
4.2 INDOOR LOCALIZATION: PLACE 50
4.2.1 Power-level Determination Phase 51
4.2.2 Anchor Information Collection Phase 53
4.2.3 Scan and Location Estimation Phase 67
4.3 模擬實驗 71
4.4 總結 76
5. 結論 77
REFERENCE: 79

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