A Digital Twin-Inspired Correction Method for Infrared Detectors

Infrared focal plane arrays (IRFPAs) often suffer from spatiotemporal nonuniformity that persists after conventional two-point nonuniformity correction (NUC), especially under temperature drift and time-varying readout conditions. These residuals are typically structured, including column-group striping caused by shared column-end circuits and row-wise baseline/common-mode drift induced by row-scanning paths. We propose a structured, digital-twin-inspired detector-side refinement of two-point NUC that augments the bias term with interpretable low-dimensional components: a static column bias vector capturing group-correlated residuals and a row-related structured term consisting of a static row baseline and a frame-synchronous common-mode component with row-dependent sensitivity, while keeping the two-point gain/offset backbone unchanged. Rather than representing a full system-level digital twin of the infrared payload, the proposed framework serves as a detector-side virtual representation of dominant readout-induced structured residual states that can be estimated and updated from calibration data. Experiments on blackbody calibration data across multiple temperature points demonstrate that the column-related structured component significantly reduces group-wise column residuals, the row-related structured component suppresses time-varying row striping, and the combined method improves both column- and row-direction metrics consistently across temperatures.