Analysis of Fine Structures in Celerity Profiles for Oceanography by Wavelets and Nonlinear Filtering
✍ Scribed by André Quinquis; Christophe Sintes; François Evennou
- Publisher
- Elsevier Science
- Year
- 1996
- Tongue
- English
- Weight
- 462 KB
- Volume
- 6
- Category
- Article
- ISSN
- 1051-2004
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✦ Synopsis
of sonar systems. Oceanography gives us some mac-Quinquis, A., Sintes, C., and Evennou, F., Analysis of Fine roscopic information based on calculations (internal Structures in Celerity Profiles for Oceanography by Wavewaves) [2]. Oceanography is a deterministic aplets and Nonlinear Filtering, Digital Signal Processing 6
proach of the study of fluctuations of celerity. In most (1996), 169-178. cases the fluctuations are unknown, and the system A sonar system's capability can be fully determined by must estimate them and use the estimates to imthe knowledge of the celerity profile. Today, we are able prove the knowledge of the true profile.
to calculate a celerity profile based on different parame-A number of solutions for tracking celerity profile ters. But in real profile, we can find faint defaults which behavior is available; recent studies have tried are very difficult to predict or to be studied. We call them to go beyond these: The goal now is to understand fine structures.
small fluctuations which can appear. We know that Recent studies have examined fine structures of the sound celerity under water using statistics.
the implications are important for long-distance
The basic difficulty is in accessing these fine structures.
propagations of the sound (beyond 100 km). Differ-Fine structures are integrated in a celerity profile with ent studies [2] have proposed to analyze fine strucmacroscopic structures. In order to explore fine structures, tures with statistics. We can say that a profile of we must extract them. The key idea of this article is to celerity c Å c(z) (where z is the parameter of immerconsider a celerity profile c(z) as a time signal s(t). Imsion) is the sum of macroscopic structures (the clasmersion z becomes time. We use causal filters and we must