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Real time implementing wavefront reconstruction for adaptive optics

机译:实时实现自适应光学的波前重建

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The capability of real time wave-front reconstruction is important for an adaptive optics (AO) system. The bandwidth of system and the real-time processing ability of the wave-front processor is mainly affected by the speed of calculation. The system requires enough number of subapertures and high sampling frequency to compensate atmospheric turbulence. The number of reconstruction operation is increased accordingly. Since the performance of AO system improves with the decrease of calculation latency, it is necessary to study how to increase the speed of wavefront reconstruction. There are two methods to improve the real time of the reconstruction. One is to convert the wavefront reconstruction matrix, such as by wavelet or FFT. The other is enhancing the performance of the processing element. Analysis shows that the latency cutting is performed with the cost of reconstruction precision by the former method. In this article, the latter method is adopted. From the characteristic of the wavefront reconstruction algorithm, a systolic array by FPGA is properly designed to implement real-time wavefront reconstruction. The system delay is reduced greatly by the utilization of pipeline and parallel processing. The minimum latency of reconstruction is the reconstruction calculation of one subaperture.
机译:实时波前重建的能力对于自适应光学(AO)系统很重要。系统的带宽和波前处理器的实时处理能力主要受计算速度影响。该系统需要足够数量的子孔节和高采样频率来补偿大气湍流。重建操作的数量相应地增加。由于AO系统的性能随着计算延迟的降低而改善,因此有必要研究如何提高波前重建的速度。有两种方法可以改善重建的实时。一个是转换波前重建矩阵,例如通过小波或FFT。另一个正在增强处理元件的性能。分析表明,通过前一种方法以重建精度的成本进行延迟切割。在本文中,采用后一种方法。从波前重建算法的特性,FPGA的收缩阵列被适当地设计以实现实时波前重建。通过流水线和并行处理的利用率大大减少了系统延迟。重建的最小潜伏期是一个子场的重建计算。

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