A closed loop ML algorithm for phase aberration correction in phased array imaging systems. Part I : Algorithm synthesis and experimental results

This paper describes a new closed loop algorithm, 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.