A noise robust sparse time-frequency representation method for measuring underwater gas leakage rate

Passive acoustic monitors analyze sound signals emitted by seafloor gas bubbles to measure leakage rates. In scenarios with low-flux gas leaks, individual bubble sounds are typically non-overlapping. Measurement methods for these bubble streams aim to estimate the frequency peak of each bubble sound, which correlates with the bubble's size. However, the presence of ocean ambient noise poses challenges to accurately estimating these frequency peaks, thereby affecting the measurement of gas leakage rates in shallow sea environments using passive acoustic monitors. To address this issue, we propose a robust measurement method that includes a noise-robust sparse time-frequency representation algorithm and an adaptive thresholding approach for detecting bubble frequencies. We demonstrate the effectiveness of our proposed method using experimental data augmented with ocean ambient noise and ship-transit noise recorded from a bay area.