Dual Carriageway Traffic Monitoring Using Superlets Based Signal Processing for Distributed Acoustic Sensing

Recently, using distributed acoustic sensing (DAS) for traffic monitoring has attracted great research attention. In urban environments, the prevalent noise interference and the presence of multi-lane roads limits the signal to noise ratio (SNR) of traffic signals. Moreover, since optical fiber cable is deployed on one side of the road, DAS data are dominantly composed of vehicle signals from the near side of the cable. It is difficult to effectively detect the vehicles moving in the opposite direction. This paper presents a signal processing method based on superlets to largely improve the SNR of traffic signals. Field trial test in the Cross Harbour Tunnel of Hong Kong shows that with the significantly improved SNR, the detection of vehicles travelling along the opposite direction becomes possible, validating the potential of applying DAS for monitoring dual carriageway multi-lane roads.