Application of spectral analysis in the remote sensing of marine geological deposits and in the detection of periodicities in the sedimentation processes in continental geological systems (part 1)
Peirlinckx, L.; Van Biesen, L.P.; Van Overloop, E. (1990). Application of spectral analysis in the remote sensing of marine geological deposits and in the detection of periodicities in the sedimentation processes in continental geological systems (part 1), in: UniversiTECH 90: Remote sensing techniques and global change research. Seminar 30-31 March 1990. pp. 1-14
In: (1990). UniversiTECH 90: Remote sensing techniques and global change research. Seminar 30-31 March 1990. Vrije Universiteit Brussel: Brussel. 6 p. abstracts, 19 p. pp., more
|
Authors | | Top |
- Peirlinckx, L.
- Van Biesen, L.P., more
- Van Overloop, E.
|
|
|
Abstract |
E chosounders are used to investigate the presence and thecomposition of marine geological deposits and to enable the automaticgeneration of a sub bottom profiling record, when sailing along rivers,estuaries and in some coastal regions. The method is based on the time domainreflectometrical principal, where underwater acoustic pulses are used. Thefrequency content of the emitted pulses is determining the vertical resolution,Le. in the direction orthogonal to the surface of the sea, and the penetrationinto the sediments. Typically, frequencies ranging from a few Hz to somehundred thousands of Hz are used (seismic, sonic and ultrasonic signals). Ingeneral ceramic transducers are used to generate the emitted pulses and torecord the reflected echoes. In this paper the present noise sources corruptingthe measured echograms will be investigated. Firstly, the measurementprocedures and the set-ups for the noise measurement will be discussed. TheBelgian oceanographic vessel, the Belgica, was used for the measurements ofthe noise generated by propellers, engines, stabilizers, the fish incorporatingthe transducers, the waves and the marine background noise. Secondly, theestimation of the Power Spectral Density (PSD) of the correlated noise sourcesis estimated. Different modern estimators will be compared and the nature ofthe different periodical components in the noise will be treated. An ARMAandAR-model will be furthermore presented to model the most importantnoise components. These models will be used to validate some of the syntheticechograms, generated in the laboratory. The study will demonstrate the highdegree of correspondence between the model and the observed measurements. |
|