Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/9203
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dc.contributor溫志煜zh_TW
dc.contributor.author廖士寬zh_TW
dc.contributor.authorLiao, Shih-Kuanen_US
dc.contributor.other電機工程學系所zh_TW
dc.date2013en_US
dc.date.accessioned2014-06-06T06:42:50Z-
dc.date.available2014-06-06T06:42:50Z-
dc.identifierU0005-1608201313401500en_US
dc.identifier.citation1. Wen, C.-Y. and W.A. Sethares, “Automatic Decentralized Clustering for Wireless Sensor Networks”, EURASIP Journal on Wireless Communications and Networking, 2005. 5: p. 686-697. 2. Chen, Y.-C. and C.-Y. Wen, “Decentralized Cooperative TOA/AOA Target Tracking for Hierarchical Wireless Sensor Networks”, Sensors, 2012. 12(11): p. 15308-15337. 3. Li, J. and Q. Ren, “Compressing Information of Target Tracking in Wireless Sensor Networks”, Wireless Sensor Network, 2011. 3(2): p. 73-81. 4. Heinzelman, W.R., A. Chandrakasan, and H. Balakrishnan. “Energy-efficient communication protocol for wireless microsensor networks”, in System Sciences, 2000. Proceedings of the 33rd Annual Hawaii International Conference on. 2000. IEEE. 5. Chen, W.-P. and J.C. Adviser-Hou,“A Data-quality Driven Framework for Data Dissemination in Wireless Sensor Networks”. 2004: PhD Dissertation, University of Illinois at Urbana-Champaign. 6. Al Aghbari, Z., I. Kamel, and W. Elbaroni, “Energy-efficient distributed wireless sensor network scheme for cluster detection”, International Journal of Parallel, Emergent and Distributed Systems, 2013. 28(1): p. 1-28. 7. Kim, W., et al. “On target tracking with binary proximity sensors”, in Information Processing in Sensor Networks, 2005. IPSN 2005. Fourth International Symposium on. 2005. IEEE. 8. Shrivastava, N., R.M.U. Madhow, and S. Suri. “Target tracking with binary proximity sensors: fundamental limits, minimal descriptions, and algorithms”, in Proceedings of the 4th international conference on Embedded networked sensor systems. 2006. ACM. 9. Singh, J., et al. “Tracking multiple targets using binary proximity sensors”, in Proceedings of the 6th international conference on Information processing in sensor networks. 2007. ACM. 10. Wang, Z., E. Bulut, and B.K. Szymanski, “Distributed energy-efficient target tracking with binary sensor networks”, ACM Transactions on Sensor Networks (TOSN), 2010. 6(4): p. 32. 11. Arulampalam, M.S., et al., “A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking”, Signal Processing, IEEE Transactions on, 2002. 50(2): p. 174-188. 12. Gordon, N.J., D.J. Salmond, and A.F. Smith. “Novel approach to nonlinear/non-Gaussian Bayesian state estimation”, in IEE Proceedings F (Radar and Signal Processing). 1993. IET. 13. Savvides, A., C.-C. Han, and M.B. Strivastava. “Dynamic fine-grained localization in ad-hoc networks of sensors”, in Proceedings of the 7th annual international conference on Mobile computing and networking. 2001. ACM. 14. Bravos, G. and A.G. Kanatas. “Energy consumption and trade-offs on wireless sensor networks”, in Personal, Indoor and Mobile Radio Communications, 2005. PIMRC 2005. IEEE 16th International Symposium on. 2005. IEEE. 15. Heinzelman, W.B., A.P. Chandrakasan, and H. Balakrishnan, “An application-specific protocol architecture for wireless microsensor networks”, Wireless Communications, IEEE Transactions on, 2002. 1(4): p. 660-670. 16. Wang, A., et al., “Energy-scalable protocols for battery-operated microsensor networks”, Journal of VLSI signal processing systems for signal, image and video technology, 2001. 29(3): p. 223-237.en_US
dc.identifier.urihttp://hdl.handle.net/11455/9203-
dc.description.abstract在無線感測網路環境中,目標追蹤是一個常見的應用,如何在有限的資源下組織感測器網路,並讓感測器在感測器網路中能夠彼此合作以用來追蹤並定位目標,以及如何將資訊在傳輸之前先進行壓縮處理以達到節能的效果是本篇論文的主要議題。本篇論文提出一種在雙層叢集式網路中經由資訊壓縮的合作式目標追蹤的方法,我們利用一種叢集式網路拓樸(CAWT)[1]來組織第一層網路拓樸,接著利用另一種因應事件發生並以領導節點為基礎的第二層分散式網路(TCAT)[2]來追蹤目標,並以資訊壓縮的觀念來處理感測器的估測結果。模擬結果顯示,我們所提出的資料處理方法較其他兩種方法(TCAT[2]與DCTTP[3])在定位精確度、傳輸的資料大小、以及耗能上有較佳的系統平衡表現。zh_TW
dc.description.tableofcontents誌謝辭 i Abstract iii Contents iv List of Tables vi List of Figures vii 1. Introduction 1 1.1. Motivation 1 1.2. Relative Works 1 1.3. Contribution 3 1.3.1. Position Estimation Refinement 3 1.3.2. Proposed Data Processing Scheme 3 1.4. Organization of Thesis 4 2. Distributed Target Tracking System Configuration 5 2.1. Tasking Leader Selection 6 2.2. Choosing the Sub-Cluster Members 9 2.3. Target Positioning 11 2.3.1. Geometrical Positioning with Particle Filtering 11 3. Data Processing Schemes 13 3.1. TCAT 14 3.2. DCTTP 20 3.3. CTCI: Cooperative tracking via compressing information 24 3.4. Data Size Estimation 32 4. Simulation 33 4.1. The relationship between the simulation parameters in TCAT and CTCI 34 4.2. The Initial Simulation Setting 35 4.2.1. Average Error Distance, Average Energy Consumption and Average Data Size 36 4.3. Influence of Simulation Parameters 37 4.3.1. Number of Sensor Nodes 37 4.3.2. Transmission Range 40 4.3.3. Compressing Bound 42 4.3.4. Number of Sampling Points 47 4.3.5. Noise 49 4.3.6. Number of Sub-cluster Size 51 5. Conclusions 53 References 54zh_TW
dc.language.isoen_USen_US
dc.publisher電機工程學系所zh_TW
dc.relation.urihttp://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-1608201313401500en_US
dc.subject資訊壓縮zh_TW
dc.subjectinformation compressionen_US
dc.subject目標追蹤zh_TW
dc.subject粒子濾波器zh_TW
dc.subject無線感測網路zh_TW
dc.subjecttarget trackingen_US
dc.subjectparticle filteren_US
dc.subjectwireless sensor networken_US
dc.title在叢集式無線感測網路中實現合作式目標追蹤之資訊壓縮研究zh_TW
dc.titleCompressing Information of Cooperative Target Tracking for Hierarchical Wireless Sensor Networksen_US
dc.typeThesis and Dissertationzh_TW
item.cerifentitytypePublications-
item.grantfulltextnone-
item.languageiso639-1en_US-
item.fulltextno fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeThesis and Dissertation-
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