On the consideration of motion effects in the computation of impulse response for underwater acoustics inversion

Abstract

The estimation of the impulse response (IR) of a propagation channel may be of great interest for a large number of underwater applications: underwater communications, sonar detection and localization, marine mammal monitoring, etc. It quantifies the distortions of the transmitted signal in the underwater channel and enables geoacoustic inversion. The propagating signal is usually subject to additional and undesirable distortions due to the motion of the transmitter-channel-receiver configuration. This paper shows the effects of the motion while estimating the IR by matched filtering between the transmitted and the received signals. A methodology to compare IR estimation with and without motion is presented. Based on this comparison, a method for motion effect compensation is proposed in order to reduce motion-induced distortions. The proposed methodology is applied to real data sets collected in 2007 by the Service Hydrographique et Océanographique de la Marine in a shallow water environment, proving its interest for motion effect analysis. Motion compensated estimation of IRs is computed from sources transmitting broadband linear frequency modulations moving at up to 12 knots in the shallow water environment of the Malta plateau, South of Sicilia.

Time-varying wideband underwater acoustic channel estimation for OFDM communications

“…where θ i is the declination angle of the ith ray and c is the sound speed in the medium [10]. We note that the ray theory based signal representation in (3) can be shown to be a special case of the time-scale system characterization in (1), with the WSF given by…”

“…To best fit the UWA model with matched time-scale transformations, the dictionary atoms are designed to match the channel propagating nature by selecting them to be time-delayed and Doppler scaled versions of the transmitted signal s(t) as in (3). We can thus choose them using the wideband ambiguity function (WAF) of the transmitted signal [10,12]. Using the MPD, the ith atom in the dictionary will correspond to g i (t) = √ η i s(η i (t−τ i )), η i = 0.…”

“…Using ray theory, the (noiseless) output signal of a sparse wideband UWA channel can be represented by [10] x…”

Doppler domain decomposition of the underwater acoustic channel response

“…In [1] two simulation methods are described for modelling time varying sea surface using ray theory and ray based formulation of the Helmholtz integral equation with a time domain Kirchoff approximation. In [2] a matched filtering technique is used to estimate Impulse Response (IR) and to study the effect of environmental variations caused by source/array movement and sea surface motion on the impulse response. In both [1] and [2] the Doppler shifted replicas of the transmitted signals are matched filtered with the received signal and depending on the peak in the ambiguity plane source/receiver motion and surface variations are approximated.…”

“…In [2] a matched filtering technique is used to estimate Impulse Response (IR) and to study the effect of environmental variations caused by source/array movement and sea surface motion on the impulse response. In both [1] and [2] the Doppler shifted replicas of the transmitted signals are matched filtered with the received signal and depending on the peak in the ambiguity plane source/receiver motion and surface variations are approximated. Due to source and/or receiver motion and the surface variations each path is affected by different dynamics of the environment.…”