台灣位於菲律賓板塊和歐亞板塊相互碰撞之交界上，多年來遭受無數大小地震侵襲，對人們造成巨大的財產及生命損失。如果事前能夠預測到地震發生就可以提前做好防災措施有助於大幅減少災害損失。儘管在預測地震方面有許多研究，但是因為地震的產生是受到許多不同因素的影響所以直到目前尚未有一個準確預測的方法應用在地震防災上。在地震防災的研究探討上較著重於地震預警(Earthquake Early Warning；EEW)上。
地震預警主要的概念就是在地震發生後，決策中心能夠盡快地根據較早到達各個測站的地震P波訊號分別做處理分析，估算出地震規模、地震震度及地震震央等資訊並發送警報到鄰近震央的區域讓居民能夠在後續破壞性的S波到達之前做好防災措施以因應。在地震預警的效能上主要可以分為二個部分，一個是從地震發生到發出警報的時間，另一個則是警報中估算結果的正確性，本篇中將探討的是關於結果的正確性。
在之前的研究中即時地偵測地震P波到時主要根據個別單一測站所感測搜集的訊號來做處理分析。在本篇論文中我們提出利用訊號交互相關P波到時偵測(Cross-Correlation P-wave Detection；CCPD)以不同測站彼此訊號間的相似性來共同合作偵測P波到時。先選出整個地震網中訊號品質較高的測站當做種子再跟種子鄰近的測站訊號做訊號相關比較得到分數及P波到時，最後再用門檻值篩選訊號品質及分數得到可靠度較高的P波到時。最後我們將方法在即時的地震預警系統上實驗說明門檻值的選擇及將計算篩選出來的P波到時用來估算震央位置來驗證提出的方法，觀察對地震情報估算的改善效果。

Since old days, Taiwan has been always threaten by the large, destructive earthquakes as a result of the geographical position between the Philippine Sea Plate and Eurasian Plate. When the earthquake occurred people always suffered from the great damage and the loss of lives after the earthquake. If people can predict the occurrence of the earthquake, people can save the property and lives from the disaster. The earthquake is always affected by many factors such as the geological configuration. Even many research on predicting earthquake, there is not the correct and precise predicting result on practical application up to now. Recently most the research focus on the earthquake early warning(EEW).
After earthquake the system can estimate the magnitude, intensity and epicenter of the earthquake according to the P-wave then provides alerts to the urban area near the epicenter as soon as possible. It is the main idea of the earthquake early warning. This procedure let people take emergency measures early to prevent the more damage from the forthcoming strong ground shaking by the S-wave. The effect of EEW could be evaluated on two aspects, one is how much time EEW spends from the earthquake occurs until it sends the alert, the other one is the accuracy of the estimated earthquake information in the alert. The proposed method in this paper focuses on the accuracy of the estimated information. Previous research on detecting and timing the P-wave in real-time usually use the single signal collected by a station. In this paper we propose the Cross-Correlation P-wave Detection(CCPD) scheme to utilize the similarity among the signals from different stations to automatically detect and pick the time for P-wave. We first choose the seed station according to the signal quality of the stations then calculate the score and P-wave arrival times based on cross-correlation coefficients with neighbor stations. Subsequently, we set the thresholds to filter the imprecise P-arrival time.
Finally, we make a simulation as EEW works in real time to explain how to set the thresholds to filter the imprecise calculated P-wave arrival times and verify the effect of CCPD method by taking those filtered P-wave arrival times into localizing the epicenter.

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