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.

The estimation of the impulse response (IR) of a propagation channel is necessary for a large number of acoustic applications: underwater communication, detection and localization, etc. Basically, it informs us about the distortions of a transmitted signal in one channel. This operation is usually subject to additional distortions due to the motion of the transmitter-channel-receiver configuration. This paper points on the effects of the motion while estimating the IR by matching filtering between the transmitted and the received signals and introduces a new motion compensation method. Knowing the transmitted signal, the "apparent" speed of each propagation path can be estimated using wideband ambiguity function [1]. Indeed, some interference appears in the wideband ambiguity plane because of the multipath propagation. A warpingbased lag-Doppler filtering method is proposed allowing us to accurately estimate the IR of the channel.

We investigate two methods for estimating the matched signal transformations caused by time-varying underwater acoustic channels in orthogonal frequency division multiplexing (OFDM) communication systems. The underwater acoustic channel for this 12-20 kHz medium frequency range OFDM system is best modeled using multipath and wideband Doppler scale changes on the transmitted signal. As a result, our first channel estimation method is based on discretizing the wideband spreading function time-scale representation of the channel output using the Mellin transform. The second method is based on extracting the time-scale features of distinct ray paths in the received signal using a modified matching pursuit decomposition algorithm. We validate and discuss both methods using data from the recent Kauai Acomms MURI 2008 (KAM08) underwater acoustic communication experiment.