Significant research efforts have focused on techniques for alleviating the nuisance alarm rate (NAR) in the field of φ-OTDR pattern recognition systems. Unfortunately, ephemeral events were mostly neglected in previous research, and algorithms meant for improving classification accuracy were emphasized at the cost of acquiring a very large number of traces. This problem engendered an additional source of NAR in a specific class of events. The proposed solution uses a novel correlation based wrapper on top of differential signals that aims to filter out the effect of unnecessary phases in direct detected φ-OTDR systems. This technique avoids the use of irrelevant data in these differential signals by exploiting a better use of these unnecessary phases and provides a better intensity translation with fewer acquired traces as compared with contemporary techniques of extracting features.
ASJC Scopus subject areas
- Atomic and Molecular Physics, and Optics