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

机译:用于相差校正相控阵成像系统的闭环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 maximumnlikelihood theory, that corrects phase aberrations in phased arrayncoherent imaging systems using phase estimates which are directlynobtained from measured data (and not from estimated correlationnfunctions). It has the advantage of estimating phase differences withnrespect to the same reference, and not phase differences between signalsnin adjacent array elements, eliminating the need to perform annintegration to get the phase aberration profile. It allows for a realntime implementation, in the sense that corrected data flows out of thencircuit at the same rate that input data is fed into it. Being a closednloop algorithm, it is able to track time variations that may occur innthe phase aberrations and, as in any phase lock loop circuit, it shows antrade-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(而非估计的相关函数)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。它具有以下优点:估计相对于相同参考的相位差,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位像差曲线的需要。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,它能够跟踪相位像差中可能发生的时间变化,并且与任何锁相环电路一样,它显示了采集时间与相位抖动之间的折衷

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