Fundamental Limits of Coherent Imaging in The Presence of Atmospheric Turbulence
Abstract
We study the fundamental limits of jointly estimating the signal amplitude and the atmospheric phase distortion in complex-valued multi-look coherent imaging, where the measurements are corrupted by multiplicative speckle and additive Gaussian noise, all looks share a known Gaussian sensing matrix, and both parameters belong to structured classes. By analyzing a constrained maximum likelihood estimator, we establish an upper bound on the joint minimax risk that holds uniformly over the admissible parameter classes, while oracle reductions and Fano-type arguments yield worst-case lower bounds over the admissible parameter classes. These results quantify the effects of structural complexity, signal and measurement dimensions, the number of looks, and the noise level, and establish matching minimax rates in several settings, with a remaining gap for phase estimation at low noise when the measurement dimension exceeds the signal dimension. We also construct a two-stage estimator for signal recovery under arbitrary diagonal sign distortions in the real-valued analogue. Under additional conditions, it recovers the signs up to a global sign with high probability and yields a uniform signal risk bound without a distortion-complexity term. Numerical experiments illustrate the dependence of the joint, signal, and phase errors on the model parameters and provide further support for the theoretical analysis.
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BibTeX
@misc{liu2026fundamental,
title = {{Fundamental Limits of Coherent Imaging in The Presence of Atmospheric Turbulence}},
author = {Songbin Liu and Hanyu Yang and Junren Chen and Arian Maleki},
howpublished = {arXiv},
year = {2026},
month = nov,
doi = {10.48550/arxiv.2611.06784},
eprint = {2611.06784},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2611.06784},
}
RIS
TY - UNPB
TI - Fundamental Limits of Coherent Imaging in The Presence of Atmospheric Turbulence
AU - Songbin Liu
AU - Hanyu Yang
AU - Junren Chen
AU - Arian Maleki
PY - 2026
DA - 2026/11/04
PB - arXiv
DO - 10.48550/arxiv.2611.06784
UR - https://arxiv.org/abs/2611.06784
AB - We study the fundamental limits of jointly estimating the signal amplitude and the atmospheric phase distortion in complex-valued multi-look coherent imaging, where the measurements are corrupted by multiplicative speckle and additive Gaussian noise, all looks share a known Gaussian sensing matrix, and both parameters belong to structured classes. By analyzing a constrained maximum likelihood estimator, we establish an upper bound on the joint minimax risk that holds uniformly over the admissible parameter classes, while oracle reductions and Fano-type arguments yield worst-case lower bounds over the admissible parameter classes. These results quantify the effects of structural complexity, signal and measurement dimensions, the number of looks, and the noise level, and establish matching minimax rates in several settings, with a remaining gap for phase estimation at low noise when the measurement dimension exceeds the signal dimension. We also construct a two-stage estimator for signal recovery under arbitrary diagonal sign distortions in the real-valued analogue. Under additional conditions, it recovers the signs up to a global sign with high probability and yields a uniform signal risk bound without a distortion-complexity term. Numerical experiments illustrate the dependence of the joint, signal, and phase errors on the model parameters and provide further support for the theoretical analysis.
ER -