Arnaud Jarrot

Localization in Underwater Dispersive Channels Using the Time-Frequency-Phase Continuity of Signals

Time-frequency representations constitute the main tool for analysis of nonstationary signals arising in real-life systems. One of the most challenging applications of time-frequency representations deal with the analysis of the underwater acoustic signals. Recently, the interest for dispersive channels increased mainly due to the presence of the wide band nonlinear effect at very low frequencies. That is, if we intend to establish an underwater communication link at low frequencies, the dispersion phenomenon has to be taken into account. In such conditions, the application of the conventional time-frequency tools could be a difficult task, mainly because of the nonlinearity and the closeness of the time-frequency components of the impulse response. Moreover, the channel being unknown, any assumption about the instantaneous frequency laws characterizing the channel could not be approximate. In this paper, we introduce a new time-frequency analysis tool that aims to extract the time-frequency components of the channel impulse response. The main feature of this technique is the joint use of time-amplitude, time-frequency, and time-phase information. Tests provided for realistic scenarios and real data illustrate the potential and the benefits of the proposed approach.

Denoising underwater signals propagating through multi-path channels

In multipath configurations, an estimation of the channel impulse response is useful for who wants to reduce or cancel undesirable multipath effects. However, the underwater noise does not fulfill the classical white-noise assumption for which matched filer-based algorithms performs optimally. In this context, three denoising methods are studied. The first two are classical methods, based on wavelet packet (WPD) decomposition and uniform filter bank (UFB) decomposition. As an alternative, we propose a novel time-frequency denoising approach, founded on the joint use of unitary warping operators and finite impulse response filters. As shown through experimental results, the WPD-based and UFB-based denoising tools are not well-suited in a multipath context. By contrast, our proposed warping-based method gives good results and leads to an improved estimation of the channel impulse response.

Toward The Use Of The Time-Warping Principle With Discrete-Time Sequences

This paper establishes a new coherent framework to extend the class of unitary warping operators to the case of discrete–time sequences. Providing some a priori considerations on signals, we show that the class of discrete–time warping operators finds a natural description in linear shift– invariant spaces. On such spaces, any discrete–time warping operator can be seen as a non – uniform weighted resampling of the original signal. Then, gathering different results from the non– uniform sampling theory, we propose an efficient iterative algorithm to compute the inverse discrete –time warping operator and we give the conditions under which the warped sequence can be inverted. Numerical examples show that the inversion error is of the order of the numerical round– off limitations after few iterations.

A Time-Frequency Characterization Framework for Signals Issued from Underwater Dispersive Environments

Time-frequency representations constitute the main tool for analysis of non-stationary signals arising from environmental systems. Recently, the interest for underwater dispersive channels appears since dispersivity phenomena act at very low frequencies which are well suited for long range underwater communication. In such a case, a main interest is to perform estimation of the impulse response of such channel for processing purposes. In this paper we introduce a time-frequency analysis tool that aims to extract the time-frequency components of the channel impulse response. This technique is based on the adaptive time-frequency filtering whose parameters are defined by a local chirp matching procedure. Tests provided for realistic scenarios illustrate the potential and the benefits of the proposed approach.

An Extension of the Class Of Unitary Time–Warping Projectors To Discrete–Time Sequences

This paper establishes a new coherent framework to extend the class of unitary warping operators (R. Baraniuk, 1995) to the case of discrete-time sequences. Providing some a priori considerations on signals, we show that the class of discrete-time warping operators finds a natural description in linear shift-invariant spaces. On such spaces, any discrete-time warping operator can be seen as a non-uniform weighted resampling of the original signal. Then, gathering different results from the non-uniform sampling theory, we propose an efficient iterative algorithm to compute the inverse discrete-time warping operator and we give the conditions under which the warped sequence can be inverted. Numerical examples show that the inversion error is of the order of the numerical round-off limitations after few iterations

Analysis of Time-Frequency Transient Components Using Phase Chirping Operator

The instantaneous frequency law (IFL) is a very important item when the physical parameters of the corresponding signal have to be evaluated. Radar, sonar, mechanical diagnostic are just three domains where the signals non-stationarity imposes the IFL estimation. There are several cases where the IFL is composed by fast variations. Digital phase modulations or signals emitted by electrical switches are typical examples of IFLs having fast transient parts. To deal with such kind of signals, we propose a new method based on the chirping of the phase transitions. Namely, the phase chirping operator (PCO) transforms a fast IFL variation in a chirp component. This chirp contains all the parameters about the initial variation : time, duration, covered bandwidth, etc. Results for some physical data will highlight the benefits of the PCO compared with wavelet transform and Wigner-Ville distribution

A Watermarking Method for Speech Signals Based on the Time-Warping Signal Processing Concept

This paper deals with the watermarking of audio speech signals which consists in introducing an imperceptible mark in a signal. To this end, we suggest 10 use an amplitude modulated signal that mimics a formantic structure present in the signal. This allows to exploit the time-masking effect occurring when two signals are close in the time-frequency plane. From this embedding scheme, a watermark extraction method based on nonstationary linear filtering and matched filler detection is proposed in order to recover information carried by the watermark. Numerical results conducted on a real speech signal show that the watermark is likely not hearable and informations carried by the watermark are easily retrievable.

Underwater channel characterization using opportunity sources : A time-frequency-phase approach

Analyzing natural signals constitutes the main tool for characterization of physical phenomena. Underwater channel is an example of a natural environment potentially characterized by signals generated by various sources : underwater mammals, human activity noise, etc. In order to efficiently exploit the information from these signals two major problems should be addressed. First, since the signals are unknown or disturbed by unpredictable factors, we are deal with a blind processing context. That is, the lack of a priori hypothesis has to be considered. Generally, the signal has a complex shape characterized by multi‐component non‐linear time‐frequency structures. The proposed solution consists in focusing our processing on non‐parametric time‐frequency analysis considering also fundamental signal items such as time‐frequency energy and local phase analysis. The second problem is related to the complex connection between physical parameters of a phenomenon and parameters of signals characterizing this phe...