Dedispersion Transform Method for Extracting the Normal Modes of a Shallow Water Acoustic Signal in the Pekeris Waveguide

Abstract

The normal modes cannot be extracted even in the Pekeris waveguide when the source-receiver distance is very close. This paper introduces a normal mode extraction method based on a dedispersion transform (DDT) to solve this problem. The method presented here takes advantage of DDT, which is based on the waveguide invariant such that the dispersion associated with all of the normal modes is removed at the same time. After performing DDT on a signal received in the Pekeris waveguide, the waveform of resulting normal modes is very close to the source signal, each with different position and amplitude. Each normal mode can be extracted by determining its position and amplitude parameters by applying particle swarm optimization (PSO). The waveform of the extracted normal mode is simply the waveform of the source signal; the real waveform of the received normal mode can then be recovered by applying dispersion compensation to the source signal. The method presented needs only one receiver and is verified with experimental data.

An Application of Fractional Brownian Motion to Vessel Identification Based on its Sound Spectrum

“…• 1 2 < H < 1, then cov (X n+1 , X n ) > 0, and by the Taylor expansion for f (x) = x 2H , one obtains γ k ≈ H (2H − 1) k 2H−2 , therefore the series ∞ k=1 γ k = ∞, and the fBm process B H is longrange dependent,…”

“…• 0 < H < 1 2 , then cov (X n+1 , X n ) < 0, and consequently the series ∞ k=1 γ k < ∞, and the B H is short-range dependent. Instead of analyzing stochastic processes in the time domain, processes can also be analyzed in the frequency or spectral domain [16].…”

“…Problem of ship identification by its radiated sound is regarded as difficult. This is by the reason of its complexity [1][2]. On the other hand, vessel recognition is very important, particularly from the military point of view.…”