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首页> 外文期刊>IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control >A closed loop ML algorithm for phase aberration correction in phased array imaging systems. I. Algorithm synthesis and experimental results [Ultrasound medical imaging]
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A closed loop ML algorithm for phase aberration correction in phased array imaging systems. I. Algorithm synthesis and experimental results [Ultrasound medical imaging]

机译：一种用于相控阵成像系统中相差校正的闭环ML算法。一，算法合成与实验结果[超声医学成像]

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摘要

A new closed loop algorithm is described, based on the maximum likelihood theory, that corrects phase aberrations in phased array coherent imaging systems using phase estimates which are directly obtained from measured data (and not from estimated correlation functions). It has the advantage of estimating phase differences with respect to the same reference, and not phase differences between signals in adjacent array elements, eliminating the need to perform an integration to get the phase aberration profile. It allows for a real time implementation, in the sense that corrected data flows out of the circuit at the same rate that input data is fed into it. Being a closed loop algorithm, it is able to track time variations that may occur in the phase aberrations and, as in any phase lock loop circuit, it shows a trade-off between acquisition time and phase jitter.
机译：基于最大似然理论，描述了一种新的闭环算法，该算法使用直接从测量数据（而不是从估计的相关函数获得）的相位估计来校正相控阵相干成像系统中的相位像差。它的优点是估计相对于同一参考的相位差，而不是相邻阵列元件中信号之间的相位差，从而消除了执行积分以获得相差像差的需求。从校正的数据以与输入数据馈入电路相同的速率流出电路的意义上说，它允许实时实施。作为一种闭环算法，它可以跟踪可能出现在相位像差中的时间变化，并且像在任何锁相环电路中一样，它显示了采集时间和相位抖动之间的折衷方案。

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