Radiated signal characteristics of marine vessels in the cepstral domain for shallow underwater channel

Abstract

This work examines the distribution of cepstral energy of the radiated signal of a marine vessel and the underwater channel modeled as a block-adaptive linear system. Detailed simulation analysis of the signal at the receiver of a passive sonar has led to the observation that, in the cepstral domain the radiated signal of a marine vessel largely occupies the lower cepstral indices while the underwater channel occupies the higher indices, such that for several range and depth conditions, the two can be separated out. This finding can facilitate the design of filters in the cepstral domain for reducing distortions due to the underwater channel. The work presents analytical justification and simulation studies in this regard.

Marine vessel classification based on passive sonar data: the cepstrum‐based approach

“…A simulation study on synthetic data has shown that the source signal cepstrum and the channel response cepstrum largely segregate towards the lower and higher cepstrum indices, respectively [32]. It is shown that the signal and the channel appear largely in non-overlapping regions of the cepstrum for shallow underwater channels.…”

“…It is also demonstrated that for a range up to 4000 m and depth of 100 m, cepstral liftering is able to significantly reduce the underwater channel distortions on the radiated noise of marine vessels for this purpose. The mathematical derivation for the channel compensation technique in the cepstrum domain is also presented [32].…”

“…The classification performance with cepstral features improves compared to that of spectral features given in Table 2. Cepstral liftering method [32] reduces the channelinduced time-dispersive distortions, which explains the performance enhancement of cepstral features over spectral features.…”

“…In this work, the proposed cepstrum-domain feature compensation method is motivated by homomorphic techniques for decoupling the channel from the radiated signal of a marine vessel [28 -33]. Two techniques have been proposed, namely, the cepstral liftering and the cepstral averaging methods to reduce the distortions because of the underwater channel [32]. Furthermore, the uncorrelatedness of the ambient noise vis-à-vis the source radiated signal, permits the application of spectral averaging techniques to reduce the effect of ambient noise.…”

Classification of Marine Mammals Using Trained Multilayer Perceptron Neural Network With Whale Algorithm Developed With Fuzzy System

“…Therefore, this section proposes the use of cepstral features, including mean cepstral features and cepstral liftering features, to make a valid data set. The channel response cepstrum and the original sound dolphins and whales cepstrum could be separated by higher and lower cepstrum indices, respectively 30 . They are in non-overlapping parts of the liftering cepstrum.…”