In this paper, we present an improvement of an existing method to estimate the channel parameters of an underwater acoustic channel in a wideband scenario. For underwater acoustic communications, the channel is characterized by paths having both time delay and Doppler scale. In this paper we focus on using a linear frequency modulated (LFM) preamble to estimate the channel parameters. We propose an improvement to the state-of-the-art method, which utilizes the fractional Fourier transform (FrFT), and show that matched filtering and the FrFT method can both be viewed as integral transforms having the same kernel. We argue that, contrary to the prevailing belief in the literature, matched filtering is superior compared to the FrFT method for channel parameter estimation. We support our findings using numerical experiments.@en

The sound field in a room can be represented by a weighted sum of room modes. To estimate the room modes, current literature uses on-the-grid, sparse reconstruction methods. However, these on-the-grid methods are known to suffer from basis mismatch. In this work, we investigate the use of a gridless framework for estimating room modes using atomic norm minimization, a gridless method. The advantage of this approach would be that it does not suffer from this basis mismatch problem. We derive a bound for the sound field reconstruction problem in a one-dimensional room with rigid walls and relate this to the frequency separation that is required by the atomic norm. We conclude that for perfect reconstruction based on the investigated gridless approach, additional prior knowledge about the signal model is required. We show how recovery is possible in a one-dimensional setting by exploiting both the structure of the sound field and the acquisition method.@en