波前感測器(wavefront sensor)是適應性光學系統(adaptive optics system，AOS)的主要元件之一，一般波前感測器之後端的信號處理部分，藉由USB、1394、或PCI等傳輸方式將資訊傳入電腦，並於視窗作業系統下執行各種演算法，以重建出波前的相位。這流程若要用於即時AOS，則會因視窗作業系統多重任務執行(multitasking)的設計，而無法準確掌控其控制迴圈至0.1秒以下。因此，本論文即自行發展即時波前感測系統，以因應即時AOS需求。
為了達到即時控制迴圈精準至0.1秒以下，因此設計上將所有的計算處理移至非視窗作業系統之嵌入(embedding)系統中完成，以達到固定時脈信號處理的即時波前感測系統。波前感測器的前端的波前感測部分是使用Shack-Hartmann架構，藉由30 Hz傳輸速度的感光耦合元件(CCD)上的聚焦光點位置，將二維波前信號擷取。在中端的信號傳輸與轉換部分，以實驗室自行研發之影像擷取系統，取代原本透過電腦中的影像擷取卡，直接將信號轉換成數位的訊號，再由電腦中的訊號擷取卡(data acquisition，DAQ)的場域可程式化閘陣列(field-programmable gate array，FPGA)模組去做即時計算。在後端的演算的部分，依序將每個聚焦區域利用重心演算法找出正確的聚焦相對位置，再將每個聚焦位置的偏移量除上透鏡組陣列之焦距，以求出各聚焦點所對應的斜率，並以Zernike模型的微分方式，利用最小平方差(least-square error)來計算出Zernike係數，並計算疊加出¬二維的波前相位。更進一步利用此自製的波前感測器系統與波前修正元件結合並做初步的系統鑑別，希望可以藉由鑑別出的系統模態，進而設計出二維控制器，以達到即時波前控制的目的。

A wavefront sensor is one of major elements in adaptive optics systems (AOS). Generally speaking, acquired wavefront information is transmitted through USB, 1394, or PCI interfaces into a PC, and the phase of the wavefront is then reconstructed by various algorithms in the operating systems (OS) of Windows. Nevertheless, the Windows OS designed for multitasking will lead to a fact that the timing of control loop cannot be handled below 0.1 sec. Therefore, the thesis dedicates in developing a real-time wavefront sensing system that matches the requirement in real-time AOS.
In order to achieve the control loop timing below 0.1 sec., all computations calculations should be executed in embedding systems that reconstruct wavefront information in real time. The front end of the wavefront detection system is based the Shack-Hartmann configuration. Two dimensional (2D) wavefront signals are obtained by positioning the focal spots on a charge coupled device. During the signal transmission and conversion processing, the 2D wavefront signals are directly converted into digital signals by a home-made embedding frame grabber instead of a conventional frame grabber inside PC. The digital signals are then decoded and computed by the field programmable gate array (FPGA) module of a data acquisition (DAQ) card. The positions of the focal spots are obtained by using a weight algorithm. The corresponded slope of each spots is then computed by dividing focal length of lens into position offset of each focal point. Zernike coefficient and 2D wavefront are acquired while Zernike differential and least-square error method is utilized sequentially. Furthermore, the system between the home-made wavefront sensing system and a wavefront corrector has been identified. According to the identified model, a controller can be designed to achieve wavefront compensation.

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