Optical Fibers Shape Sensing Accuracy under Different Uncertainty Sources: A Monte Carlo Experiment

Nowadays, optical fibers shape sensing is employed in a wide range of applications. Its working principle is based on the simultaneous measurement of strain in different cores located in the same fiber or sensing cable, allowing distributed measurements of both curvature and bending angle of each point of the sensing cable. It is crucial to study how different sources of noise and uncertainty can affect shape reconstruction. In this study, the curvature and bending angle accuracy are evaluated while exposed to different potential sources of uncertainty, such as measurement noise, core twist and positioning noise, through a Monte Carlo experiment. The results suggest that the curvature and bending angle accuracy are inversely proportional to the square root of the number of cores in presence of measurement noise and core positioning fluctuations. On the other hand, in the presence of twist noise, increasing the number of cores does not improve the shape sensing performance.