無線感測網路室內自動化定位系統研究

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2008

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目前室內定位系統沒有被廣泛地應用,關鍵問題如下。第一是建立定位系統,必須耗費人力取得環境參數才能順利運作。第二是無線網路設備訊號接收的靈敏度高,造成接收訊號不穩定,對於採用此訊號定位的系統會造成影響。第三是目前的定位方法,定位誤差仍不到實用階段。本論文針對以上問題,提出解決方案,本研究首要目標是使系統能自動將環境參數求出,並且能因應環境變化,校正環境參數。對於接收訊號不穩定的問題,採用指數加權移動平均處理接收訊號,讓所得到的訊號較平滑,降低訊號不穩定的情形。 定位演算法部份,本論文採用最大近似值估計法與順序式定位法的概念,提出整合式定位法,利用區域分割與比較訊號強度大小的方式,不但減少運算的複雜度,還可以減低定位上的誤差。實驗結果顯示,本系統除了能夠自動化求出環境參數以及改善接收訊號的不穩定情況,整合式定位法也能提供良好的定位準確度,未來若能進一步研究細部的參數影響效應,定位精度有機會獲得提昇。本論文所建立的室內定位系統,具備自動化定位功能,使得室內定位系統更趨於實用性的目標。
Car navigation system is based on Global positioning system and provides us outdoor location information. Instead, indoor positioning system will help us find the right way and reach our destination easily. The indoor positioning system is not an popular application right now. There are some factors hinder the application of indoor positioning systems. 1. difficult to obtain environment parameters, 2. instability of RF signals, 3. the positioning error is not good enough for application. The methodology developed in this thesis can compute the environment parameters automatically and lower positioning errors. It also can smooth the unstable received signals. The experiment results indicate that our indoor positioning system is able to improve the positioning error to an acceptable resolution. We are looking forward to more and more applications of indoor positioning system in the near future.

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室內定位系統, 最大近似值估計法, 指數加權移動平均, indoor positioning system, maximum likelihood estimation, exponential weighted moving average

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