- 學位論文
具誤差校正之無線感測網路室內定位
Implementation of Wireless Sensor Network for Indoor Localization with Error Calibration Algorithms
摘要
無線感測網路應用已經有越來越多研究人員投入相關的研究，定位技術為其中非常重要的領域。無線定位應用的領域非常廣，例如居家照護、醫院病患安全監控系統、工廠人員門禁監控等，如何將定位結果計算的精準，是許多定位技術相關研究的發展方向。本論文提出利用無線電接收強度RSS(Received Signal Strength )為依據進行室內定位。無線電波本身有因距離而衰退的特性，利用此特性對於接收到的無線電波強度進行距離推測，再結合蜜蜂演算法進行最佳化的定位推估，而無線電接收強度RSS值於各種環境中量測容易產生誤差而影響定位結果，因此本論文提出兩種方法校正RSS量測誤差。其中一種為環境定值校正誤差；另一種為加強最大RSS影響力，來改善因RSS量測誤差影響定位結果的問題。 本論文利用德州儀器(TI)公司ZigBee協定規範/802.15.4晶片CC2430的RSS無線電波接收強度來完成定位結果。系統架構由1個協調器(Coordinator)、4個參考節點(Reference Node)與1個目標節點(Target Node)構成。系統一開始由協調器建置一個無線感測網路，參考節點固定架設於室內空間的四個角落，待目標節點加入網路之後，就進行RSS值量測，電腦接收完RSS量測資料後，利用RSS與距離比例適應函式配合蜜蜂演算法將定位資訊算出，最後再利用RSS量測校正誤差的方法改善定位結果。
並列摘要
Localization is one of the most important research topics in the wireless sensor network applications. The localization technique can be applied in several fields, including the fire location identification, home automation, environment monitoring and so on. Recently, how to achieve the most precise localization performance is an important research issue. GPS is not suitable for indoor localization because of the poor availability of RF signals and the large power consumption. Several alternatives can be used for indoor localization. The Received Signal Strength (RSS) based approach can be used due to its simplicity. The RSS-based approach can be used for localization since the RSS value decays when the distance increases. However, errors can be influenced by various environmental issues. Hence, in this thesis, a ZigBee-based approach with two novel error calibration algorithms for indoor localization is proposed to diminish the influence from the environment to further improve the localization performance. The proposed localization algorithms run on a Personal Computer. The measured RSS information is transmitted to the PC to calculate the target’s location. In this thesis, the Artificial Bee Colony Algorithm (ABC) is employed to compute the location of an unknown target. Two calibration algorithms are used to increase the precision of localization results. In summary, the experimental results confirm that the proposed approach is able to improve the localization performance to precisely locate the target.