在這個研究中，手機定位估測問題以資料整合為基礎在嚴重無線環境中可以被形成如同非線性濾波器問題在直射可見光（LOS）或非直射可見光（NLOS）選擇模式。資料整合是用接收信號強度量測信號和時間抵達量測信號所組合合成一個量測信號，這可使我們所量測到信尋更充裕去估測手機定位估測。一般在無線傳輸中，有直射可見光（LOS）或非直射可見光（NLOS）兩種電磁波。後者是因為波傳過程中沒有直接直射波，這將造成我們手機定位估測上不精切。在上述這些問題中，我們將遇到非線性選擇模式問題。以下我們將提起一個整合方法去解結這問題。模糊濾波器和互相反應多個模型（IMM）技術可以被應用去處理非線性多個模式濾波器問題。模糊濾波器被提起去內插幾各線性濾波器去處理非線性狀態估測問題在不同運用區域和IMM技術被使用去平穩選擇估測在LOS和NLOS之中被依賴可能性函數。我們提起方法整合技術資料整合，模糊濾波器和IMM方法去改善手機定位估測精切度在嚴重無線環境中。論文最後，一個模擬例子在一個都市街道通信傳輸環境中可以被使用去說明設計程序和去證實我們提起方法的精切度上性能。

In this study, data fusion-based mobile location estimation problem in the rough environment is formulated as an augmented nonlinear filtering problem under line-of-sight(LOS) and non line-of-sight(NLOS) switching modes. Fuzzy filtering and interactive multiple model (IMM) scheme are employed to treat the nonlinear multiple mode filtering problem. Fuzzy filter is proposed to interpolate several linear filters to treat the nonlinear state estimation problem at different operation regions and IMM scheme is used to smooth the switching estimation between LOS and NLOS modes based on the likelihood function. The proposed method integrates the technique of data fusion, fuzzy filtering and IMM scheme to improve the accuracy of mobile location estimation in rough wireless environment. Finally, a simulation example in an urban radio propagation environment is given to illustrate the design procedure and to confirm the performance of the proposed method.

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