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GPS接收機的定位精確度對於使用者而言是很重要的，特別是使用C/A
碼的單一接收機。在本論文中，將提出應用模糊理論於全球定位系統以改
善定位精確度的方法。 針對衛星幾何分佈所造成的精確釋
度(Dilution of Precision, DOP)及接收機通道之訊號雜訊比(Signal-
Noise Ratio, SNR)對於定位誤差所造成的影響，於文中將有詳細的探討
。然而，PDOP和SNR之間的關係會彼此矛盾，且具有一定的模糊性，這也
就是為什麼引用模糊方法的原因。實驗的方法大致為，利用定位資料的
PDOP值、SNR值作為模糊處理單元( Fuzzy Processing Unit )的輸入，用
以推論計算該筆定位資料的信賴度因子 (Reliable Factor)。再者，
將此信賴度因子和一預先設定的臨界值比較，若信賴度因子大於該值，則
選用此定位資料。經由此方法，而可以從原始資料中，篩選出較為精確的
定位資料，達到精度改善的目的。
本實驗的方法將分別用於C/A碼單機及DGPS接收機。從實驗的結果可知，
以此方法改善GPS定位的精度，是確實可行的。而其改進之程度對C/A碼單
機是較具效果的。
The positioning accuracy of the GPS receiver is important to
the users, especially for those who use the C/A code stand
alone receiver. In this thesis,an application of fuzzy set
theory to the problem of GPS positioning accuracyimprovement is
proposed.
The effects of DOP ( Dilution Of Precision ) , SNR (Signal-
Noise Ratio) to positioning error are discussed in the content.
However,there are tradeoffsamong the PDOP and SNR. That is the
reason why we introduced these quantities into fuzzy processing
unit. The PDOP and SNR values are used for the fuzzy
processing unit to evaluate the reliable factor, which
represents the reliability of this position fix. Next,
the reliable factor is compared with adesired threshold value.
If it exceeds this value, this position fix is adopted. By
this way, we can select the more accurate position fixes from
the original ones to improve the positioning accuracy.
We employed this fuzzy processing on both the C/A code stand
alone receiver and the DGPS receiver. Our experimental
results will illustrate that fuzzy processing on GPS data can
actually reduce the positioning error to a certain extent. The
improvements on C/A code single receiver are more obvious.
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