Download High-Resolution Methods in Underwater Acoustics by Michel Bouvet, Georges Bienvenu PDF

By Michel Bouvet, Georges Bienvenu

Probably the most difficult difficulties in electric engineering is the detection and localization of goal in underwater acoustics. specifically, bearing estimation is generally got through the classical array processing approach, beamforming. High-resolution equipment were brought to beat the most problem of beamforming, negative answer. This quantity consists of tutorials and state of the art examine papers on high-resolution equipment utilized to underwater acoustics. almost all these papers are on the topic of the bearing estimation challenge (detailed presentation of tools in their performances, either theoretical and at-sea, their use with an array of unknown geometry, and so on) yet extensions to the temporal and spectral domain names also are integrated. This monograph on sign processing, underwater acoustics is meant for using electric engineers, complex scholars, researchers, engineers and scientists, technical military humans.

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A . C] = - tr IT. T* C. T . T". C] = - tr [(F' C T ) . (T* CT)] = - II T". C . 19) (11 IIF being the Frobenius norm of a matrix [19]) So that finally, the quadratic form X t . H2 • X is negative for any vector X. tJ the parameters {13i~= t on the constraints domain r{... Consequently, gradient's method (with optimal step) will converge on c~. Let us now present, briefly, the gradient method. Calculation of the gradient vector is straightforward, the i-th component of the gradient vector at iteration k is given by: Gk (i) = - tr[(R - Bk)" l .

Hown in the field of linear systems and is called "realization problem". Its resolution requires the estimation of the covariances of the process {Yi}. 4) = ffp ,irp:o ' isthes ,ifp~0 v anoema ). The estimation of the transition matrix F from these covariances wiLl be presented later. 3) where the observation noise [vi} is spatially correlated now. Unfortunately, this model is useless to extract the interesting parameters because there is no efficient realization methods which are suited to this model with a correlated noise on the observation equation.

Furthermore spurious sources can be seen in the vicinity of the array broadside. :33 Lm,o 34-- , 29-- /- - . 0 / I a ] O " 3Q - £ " ' ,~0, ,- ,~i I ,-,,-, SPATIAL DENSITY Fig. 2 - NON D E T E C T I O N O F W E A K SOURCES As it has been seen previously, a compromise between spurious sources and detection of weak sources must be determined in the presence of colored noise. Another spurious phenomenon is illustrated by fig. 2. A weak source is simulated at a bearing corresponding to a hole of the noise spatial density.

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