基於磁場感測陣列的室內定位系統

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：24

、訪客IP：18.221.129.19

姓名

劉宗鑫(Tzung-Hsin Liu) 查詢紙本館藏

畢業系所

資訊工程學系在職專班

論文名稱

基於磁場感測陣列的室內定位系統
(An Indoor Positioning System based on Geomagnetic Sensor Array)

相關論文

★ 整合GRAFCET虛擬機器的智慧型控制器開發平台	★ 分散式工業電子看板網路系統設計與實作
★ 設計與實作一個基於雙攝影機視覺系統的雙點觸控螢幕	★ 智慧型機器人的嵌入式計算平台
★ 一個即時移動物偵測與追蹤的嵌入式系統	★ 一個固態硬碟的多處理器架構與分散式控制演算法
★ 基於立體視覺手勢辨識的人機互動系統	★ 整合仿生智慧行為控制的機器人系統晶片設計
★ 嵌入式無線影像感測網路的設計與實作	★ 以雙核心處理器為基礎之車牌辨識系統
★ 基於立體視覺的連續三維手勢辨識	★ 微型、超低功耗無線感測網路控制器設計與硬體實作
★ 串流影像之即時人臉偵測、追蹤與辨識─嵌入式系統設計	★ 一個快速立體視覺系統的嵌入式硬體設計
★ 即時連續影像接合系統設計與實作	★ 基於雙核心平台的嵌入式步態辨識系統

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

至系統瀏覽論文 (2024-7-2以後開放)

摘要(中)

室內定位技術目前仍難以廣泛被導入使用，主要原因在於定位精度的需求、佈署困難度及感測器成本。基於地球磁場感測是新興的室內定位技術，具備無需事先進行環境佈建及感測器成本較低的優勢，但卻存在精度不足的問題。本研究提出一個基於地磁感測器陣列的室內定位方法，我們使用三個磁場感測器構成感測器陣列，以量測室內空間的磁場分布。感測器擷取的原始磁場感測訊號X / Y / Z 被轉換成磁場強度、磁傾角、和磁偏角，我們使用這些感測資料和感測器之間空間差分作為室內空間位置辨識的特徵向量。並透過機率神經網路的辨識模型來推估座標位置。最後我們在11.4m x 6.6m 的實驗場域中驗證本方法定位的準確性，實驗結果顯示使用本研究所提出之作法，其誤差量90%皆能維持在1m 以內，相較於傳統方法，可大幅降低定位座標的誤差。

摘要(英)

An indoor position system has not been widely applied in life, the main reason are the demand of accuracy, the difficulties of disposal and the cost of sensor. It is a new technology about an indoor positioning system based on geomagnetic sensor array, it is an advantage that we don’t need to dispose the environment and we have the lower sensor cost, but it has a problem about the insufficient accuracy. The research provide an indoor positioning method
based on geomagnetic sensor array, we use three geomagnetic sensor to compose the geomagnetic sensor array, therefore we can measure the geomagnetic disposal indoors. The original geomagnetic sensor signal X / Y / Z from sensor are transferred to magnetic field,magnetic dip and magnetic declination, we use the data and the disparity between the space of sensor as vector of position determination, and we estimate the coordinate by the recognition of probabilistic neural network. Finally, we verify the accuracy at 11.4m x 6.6m platform, the experimental results indicated that we can maintain the 90% error within 1m by this method,it can reduce the coordinate error compare to the traditional method.

關鍵字(中)

★ 機率神經網路
★ 室內定位

關鍵字(英)

★ pnn
★ indoor positioning

論文目次

摘要 I
Abstract II
致謝 III
目錄 IV
圖目錄 VI
表目錄 VIII
第一章、緒論 1
1.1 研究背景 1
1.2 研究目的 3
1.3 論文架構 3
第二章、技術回顧 5
2.1 地球磁場量測 5
2.2 磁場感測訊號前處理 8
2.3 磁場定位 10
2.4 神經網路 11
2.4.1 機率神經網路 11
2.4.2 改良式機率神經網路(MPNN) 14
第三章、磁場感測陣列室內定位系統設計 16
3.1 磁場感測陣列室內定位系統架構 16
3.2 座標系統 17
3.2.1 感測器陣列作業流程 18
3.2.2 卡爾曼濾波 19
3.3 磁場資料庫 21
3.4 座標辨識 22
第四章、實驗分析與結果 24
4.1 實驗平台24
4.1.1 STM32F7 微控制器 24
4.1.2 磁場感測器模組 25
4.1.3 磁場感測器陣列模組介紹 26
4.1.4 軟體開發工具 27
4.2 磁場特徵實驗 28
4.2.1 相同環境不同時間之磁場變化狀況 28
4.2.2 磁場感測陣列之輸出數據差異分析 29
4.3 感測器陣列定位實驗 32
4.3.1 不同帄滑參數預測誤差分析 33
4.3.2 單顆感測器與感測器陣列之定位精度比較 34
4.3.3 各種磁力定位之精確度比較 38
第五章、結論與未來展望 40
5.1 結論 40
5.2 未來展望 41
參考文獻 42

參考文獻

[1]D. B. Cox, "Integration of GPS with Inertial Navigation System, " Navigation, Journal of institute of Navigation, 1978.
[2] H. Liu, H. Darabi, P. Banerjee, and J. Liu, "Survey of Wireless Indoor Positioning Techniques and Systems," IEEE Transactions on Systems, vol. 37, no. 6, pp. 1067-1080, 2007.
[3] F. Palumbo, P. Barsocchi, S. Chessa, and J. C. Augusto, "A Stigmergic Approach to Indoor Localization Using Bluetooth Low Energy Beacons," IEEE International Conference on Advanced Video and Signal Based Surveillance.(AVSS), pp. 1-6, 2015, Karlsruhe, Germany
[4] M. G. Dissanayake, P. Newman, S. Clark, H. Durrant-Whyte, and M. Csorba, "A Solution to the Simultaneous Localization and Map Building (SLAM) Problem," IEEE Transactions on Robotics Automation, vol. 17, no. 3, pp. 229-241, 2001.
[5] N. Karlsson, E. di Bernardo, J. Ostrowski, L. Goncalves, P. Pirjanian, and M.E. Munich, "The vSLAM Algorithm for Robust Localization and Mapping," Proceedings of the IEEE International Conference on Robotics and Automation , pp. 24-29, 2005, Barcelona, Spain.
[6] B. Li, T. Gallagher, A. G Dempster, and C. Rizos, "How feasible is the use of magnetic field alone for indoor positioning?," IEEE International Conference on Indoor Positioning and Indoor Navigation. IPIN, pp. 1- 9, 2012, Sydney, NSW, Australia.
[7] P. Pivato, L. Palopoli, and D. Petri, "Accuracy of RSS-based centroid localization algorithms in an indoor environment," IEEE Transactions on Instrumentation and Measurement, vol. 60, no. 10, pp. 3451-3460, 2011.
[8] L. Wang, T. K. Hon, J. Reiss, and A. Cavallaro, "Self-localization of ad-hoc arrays using time difference of arrivals," IEEE Transactions on Signal Processing, vol. 64, no. 4, pp. 1018-1033, 2016.
[9] W. Storms, J. Shockley, J. Raquet, "Magnetic field navigation in an indoor environment," IEEE International Conference on Ubiquitous Positioning Indoor Navigation and Location Based Service, pp. 1-10, 2010.
[10] A. Saxena, M. Zawodniok, "Indoor Positioning System Using Geo-Magnetic Field," Proceedings of the IEEE International Instrumentation and Measurement Technology Conference. (I2MTC), pp. 572-577, 2014.
[11] B. Kim, and S. H. Kong, "A Novel Indoor Positioning Technique Using Magnetic Fingerprint Difference," IEEE Transactions on Instrumentation and Measurement, vol. 65, no. 9, pp. 2035-2045, 2016.
[12] H. Xie, T. Gu, X. Tao, H. Ye, and J. Lu, "A Reliability-Augmented Particle Filter for Magnetic Fingerprinting Based Indoor Localization on Smartphone," IEEE Transactions on Mobile Computing, vol. 15, no. 8, pp. 1877-1892, 2016.
[13] J. Chung, M. Donahoe, C. Schmandt, I. J. Kim, P. Razavai, and M. Wiseman, "Indoor location sensing using geo-magnetism," Proceedings of the ACM international conference on Mobile systems, applications, and services, pp. 141-154, 2011, New York, USA.
[14] Geomagnetic storm. [Online]Available: https://en.wikipedia.org/wiki/Geomagnetic_storm
[15] V. V. Meleshko, S. L. Lakoza, and S. A. Sharov, "Method of identifying and eliminating magnetic compass deviation," IEEE First Ukraine Conference on Electrical and Computer Engineering. UKRCON, pp. 288-291, 2017, Kiev, Ukraine.
[16] Y. Shu, C. Bo, G. Shen, C. Zhao, L. Li, F. Zhao, "Magicol: Indoor Localization Using Pervasive Magnetic Field and Opportunistic WiFi Sensing," IEEE Journal on Selected Areas in Communications, vol. 33, no. 7, pp. 1443-1457, 2015.
[17] Indooratlas. [Online] Available: https://www.indooratlas.com/
[18] C. Zhang, K. P. Subbu, J. Luo, and J. Wu, "GROPING: Geomagnetism and cROwdsensing Powered Indoor NaviGation," IEEE Transactions on Mobile Computing, vol. 14, no. 2, pp. 387-400, 2015.
[19] B. Li, T. Gallagher, A. G. Dempster, C. Rizos, "How feasible is the use of magnetic field alone for indoor positioning?" IEEE International Conference on Indoor Positioning and Indoor Navigation. (IPIN), pp. 1-9, 2012, Australia.
[20] W. Shao, H. Luo, F. Zhao, Y. Ma, Z. Zhao, A. Crivello, "Indoor Positioning Based on Fingerprint-Image and Deep Learning. " IEEE Access,vol. 6, pp. 74699–74712, 2018.
[21] W. Dyason, T. Niekerk, R. Phillips, R. Stopforth, "Performance evaluation and comparison of filters for real time embedded system applications" IEEE Pattern Recognition Association of South Africa and Robotics and Mechatronics. (PRASA-RobMech), pp.242-248,2017.

指導教授

陳慶瀚(Ching-Han chen)

審核日期

2019-7-3

推文