近年來手機定位技術的研究與應用的發展相當熱門，在美國FCC制定E911服務後，歐盟也相繼開始制定E112救難服務相關技術與法規，因此手機定位功能將是每隻手機必備的功能之一，目前的主流技術主要是在手機上加裝GPS定位晶片，或是由網路端來做定位的計算，再將定位的結果回傳給手機。前者需要修改手機的硬體以及增加零件成本，而後者的定位精確度誤差較大而且需要額外的資料傳輸費用。
本論文主要目的在介紹CDMA手機的定位方法與如何實作，在以不修改目前手機的硬體，只修改手機韌體的情況下透過量測基地台的廣播訊號，利用3個基地台的到達訊號時間差計算出2D座標定位。此外在論文中，主要解決了三個實作手機定位所需解決的問題。
第一，當量測訊號受到非視線傳播NLOS的干擾時，我們使用滑動視窗找最小值後再以平滑處理來改善NLOS干擾。第二在實作演算法在手機上時，我們將複雜的矩陣運算做分割與簡化，以避免超過手機運算能力，當量測到的基地台數目k大於3個時，重複取 次三角定位運算後再加權平均。最後，經過實驗當量測的基地台數目增加時，將所有基地台組合所計算出的定位座標直接平均座，可提高量測的精確度，若進一步將計算結果乘上三角形重心與預估距離的反比，經過此加權法總和所求的座標精確度，誤差有明顯的較直接平均來的好。
在實際的網路測試時，我們分別作靜態與動態的定位測試，其中靜態測試結果可以符合FCC的要求。

The mobile location positioning technology has been developed and widely used in recent years. After the US FCC mandates the E911 emergency service to be provided by all wireless service providers, the European Commission also starts to work out the E112 relative standards and regulations. Therefore positioning will be one of the essential features in cellular phones. The current main stream technology is to build-in a GPS chip for satellite positioning or via network based wireless location sending back result to the handset. The prior solution requires modifying the handset and increases bill of material (BOM) cost, and the later one has lower accuracy problem and requires additional data transmission fee to users.
The main purpose of this thesis is to implement a positioning algorithm on a CDMA compatible cellular phone. In the condition of no hardware modification, but only modifying the firmware, the handset measures time difference of the base stations’ broadcast signal and locate the 2D position via trilateration method. Besides, there are 3 main issues are resolved in our implementation. First, when the measured signal is interfered by NLOS (Non-Sight-of-Light) effect, we utilize a sliding window to look up the minimum value and adopt a smoothing method to improve the NLOS effect. Second, for the implementation of algorithm on the embedded system, we simplify the complex matrix computation to use only 2 x 2 matrix form instead of k x k matrix in order not to overrun the system ability. When the number of the received BS signals, k, is greater than 3, all location estimates of the combinations are computed. Then these estimates are either directly averaged or weighted summed to compute a final estimate. In order to evaluate the system performance, we ran the static and dynamic tests on the live network. The results show the static tests can pass the FCC’s requirement.

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