An Active Acoustic Track-Before-Detect Approach for Finding Underwater Mobile Targets

Abstract

We consider the challenge of tracking and estimating the size of a single submerged target in a high reverberant underwater environment using a single active acoustic transceiver. This problem is common for a multitude of applications, ranging from the security and safety needs of tracking submerged vehicles and scuba divers, to environmental research and management implications such as the monitoring of pelagic fauna. Considering that the target can be either slow (e.g., a scuba diver) or fast moving (e.g., a shark), we avoid continuous signaling, and rely on the emission of wideband pulses whose reflection pattern are evaluated and reshaped in a time-distance matrix. As opposed to common approaches that track targets through template matching or by using tracking filters, we avoid making difficult assumptions about the target's reflection patterns or motion type, and instead perform probabilistic tracking using a constraint Viterbi algorithm, whereby detection is determined based on maximum likelihood criterion. In this process, we use the expectation-maximization approach to manage stationary reflections through distribution analysis, which otherwise may be misidentified as targets. Based on the tracked path, we then evaluate the target's size. To test our approach, we performed extensive simulations as well as eight sea experiments in different environmental settings to track both a scuba diver and a sandbar shark ( Carcharhinus plumbeus ). The simulation results show a tracking performance that is close to the Cramer–Rao lower bound, and the experiment results show a good tradeoff between detection rate and false alarm rate for a low signal-to-clutter ratio of 5 dB, and average tracking error of 1.5 and 6.5 m in the detections of a scuba diver and sandbar shark, respectively. For reproducibility, we share our sea experiment data.