Opt Lett. 2025 Aug 15;50(16):5041-5044. doi: 10.1364/OL.566313.
ABSTRACT
Statistical estimation methods for localization microscopy (LM) estimate emitter locations using a parameterized statistical model presumed for the data, enabling derivations of estimators and theoretical accuracy bounds. The most widely used performance bound is the Cramér-Rao lower bound (CRLB), which provides a lower bound on the error covariance of any unbiased estimator of the model parameters (i.e., emitter locations) and characterizes the asymptotic performance of the maximum likelihood estimator (MLE). In practice, however, the presumed model is almost always mismatched to the true model that generates the data due to experimental uncertainties stemming from aberrations, calibration errors, and misalignment. As a result, the CRLB no longer provides an accurate lower bound on achievable localization accuracy, and a different performance bound called the Misspecified Cramér-Rao Bound (MCRB) must be considered. In this Letter, we derive the MCRB in different LM setups, with different Poisson statistics, and analyze the behavior of the derived MCRBs. Our analysis provides a quantitative framework for understanding how experimental imperfections affect the limits of achievable localization accuracy.
PMID:40815735 | DOI:10.1364/OL.566313
