Adaptive Filter for Automatic Identification of Multiple Faults in a Noisy OTDR Profile

We present a novel methodology that is able to distinguish meaningful level shifts from typical signal fluctuations which, in a fiber monitoring context, is associated with the problem of identifying small losses within a noisy optical time-domain reflectometer (OTDR) profile. A two-stage regularization filtering can accurately identify the location of the significant level shifts with an efficient parameter-free algorithm. The developed methodology demands low computational effort and can easily be embedded in a dedicated processing unit. Our case studies compare the new methodology with the current available ones and show that it is the most adequate technique for fast detection of multiple unknown level shifts in a noisy OTDR profile.