High-precision calibration method for collimated porous mask imaging system

A large field of view can be covered by a porous mask imaging system based on collimated light incidence under a limited image plane size, but its calibration is faced with a dilemma in which global geometric errors are difficult to be characterized by a global model for each hole position, while sufficient constraints cannot be provided by a per-hole model. To address this issue, a calibration method was proposed. First, based on calibration data, global geometric parameters, including the mask-to-image-plane spacing, the mounting attitude angles, and the image-plane reference center, were estimated by global least-squares optimization. Subsequently, the calibration data were grouped according to hole positions, and a cubic polynomial error compensation model was established for each hole so that local errors of the hole positions could be compensated. Finally, confidence levels were determined according to the residuals of each hole model, and adaptive weighted fusion was performed on the projection angles of the incident rays solved for each hole. Experimental results show that a measurement accuracy of 6.1″/6.8″ (3σ) is achieved for the projection angle of the incident rays by this method, by which high-precision measurement at the arcsecond level is realized.