Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/6259
標題: 在無線感測網路中應用分散式粒子濾波器實現合作式目標追蹤之研究
Cooperative Target Tracking in WSNs with Distributed Particle Filtering
作者: 尤淑孟
Yu, Su-Mong
關鍵字: Particle Filter;粒子過濾器(Particle Filter);Wireless Sensor Networks;Target Tracking;Covariance Intersection;無線傳感器網絡(Wireless Sensor Networks);目標物追蹤(Target Tracking);協方差交集(Covariance Intersection)
出版社: 電機工程學系所
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摘要: 
本論文提出在無線傳感器網絡( Wireless Sensor Networks)中把目標物放在兩個不同的拓樸中去追蹤目標物(Target Tracking)的方法。我們利用平面式網路拓樸( Flat Network)與叢集式網路拓樸( Cluster-based Network)進行目標追蹤,並且以領導節點為基礎(leader-based)的演算法來追蹤目標物。在平面式網路(Flat Network)中使用計時器(timer)來建立叢集(Cluster),而在叢集式網路(Cluster-based Network)中則用The clustering algorithm via waiting timer (CAWT)提供叢集模型(Cluster Model)。對於目標物追蹤(Target Tracking)部分採用粒子過濾器(particle filter)]估測目標物的路徑,把得到的數據再經由協方差交集(Covariance Intersection)做數據間的融合(Data Fusion )。最後,我們將比較此兩種不同網路拓樸之追蹤的精準度,並分別比較這兩種拓樸的效能。

This thesis presents distributed methods for target tracking in wireless sensor networks. We consider flat network and cluster-based network topologies for target tracking and provide leader-based information processing to track the target. The method with a flat network uses a timer to create clusters dynamically and the method with a cluster-based network uses the Clustering Algorithm via Waiting Timer (CAWT) to create the cluster model. Particle filtering is applied to estimate the location of the target, and then Covariance Intersection algorithm is used to make data fusion with local estimates. Finally, we compare the estimation accuracy with the two different network topologies.
URI: http://hdl.handle.net/11455/6259
其他識別: U0005-0808201111015500
Appears in Collections:電機工程學系所

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