Variational Bayesian Inference Time Delay Estimation for Passive Sonars

In passive sonars, distance and depth estimation of underwater targets is often limited by the accuracy time delay estimations. The existing methods uniform discrete grid (signal sampling rate). When a true out grid, deteriorates due to mismatch between real-time grid. This paper proposes new method for estimation, which realizes under framework variational Bayesian inference. proposed grid-less, that is, continuous in domain. Unlike popular grid-less compressive method, this does not require parameter adjustment, can automatically estimate number delays, noise variance, amplitude variance. simulation results showed performance was superior reference state-of-the-art methods.