Identification of Intrusion Events Based on Distributed Optical Fiber Sensing in Complex Environment

Abstract

With the development of economy, the construction of modern infrastructures has been gradually improved. Some infrastructures, such as factories and airports, have large construction volume and high security requirements. Once an intrusion occurs, it will pose a great threat to the safety of personnel and property. Therefore, the perimeter security system based on Internet of Things (IoT) devices and technology is important. Distributed optical fiber sensor (DOFS) is an emerging infrastructure for IoT. Owing to multipoint sensing at the same time, it has attracted extensive attention in the field of perimeter security. However, with the ambient interference, intrusion signals and ambient signals form mixed signals, which brings great difficulty to the efficient and correct identification of intrusion signals. In order to establish a perimeter security system in complex environment, this article proposes an intrusion detection scheme based on DOFS, IoT, and pattern separation technology. The scheme realizes the separation of ambient signals and intrusion signals for the first time. Experiments have proved that this method can separate and recover intrusion signals from mixtures with the average SDR and SI-SDR of 12.35 dB and 11.61 dB, which effectively lays a foundation for subsequent feature extraction and identification. Besides, the response time is only about 0.5 s. This work makes a significant step toward achieving high performance of the perimeter security system in complex environment.