Objetivo
The project objective is to advance the shallow-water coherent communication networking techniques, to achieve high reliability and fast
self-start/self-recovery capability.
The project will concern the investigation of innovative solutions for the basic building block of the communication network, that is the Multi-Element Multi-User (MEMU) array receiver operating in the absence of training sequences.
The activities foreseen are the following.
- Analysis and modelling of the shallow water propagation channel. - Analysis and upgrade of the decision-directed array processing algorithms in a receiving network node, combining jointly synchronization and fractionally-spaced decision feedback equalization.
- Introduction of channel identification to update the parameters of a MEMU equalizer, to improve performance.
- Analysis of fast blind array techniques for self-start and selfrecovery. - Combination of blind and decision-directed techniques in dual-mode processors.
- Performance evaluation obtained first on synthetic data generated by a channel and node simulator, then on data gathered at sea.
The expected achievements of the project are:
- to characterise the acoustic propagation in shallow water; - to synthesize innovative array processing algorithms not adopting training sequences;
- to quantify the capability of fast self-start and self-recovery; - to implement a channel and node simulator, for performance evaluation on synthetic data;
- to acquire sea trials data for off-line testing and performance evaluation of the processing and the modelling.
The contents of the proposal are: outlining a communication network; analysing the channel response, and generation of time signals at the receiver input; network node processing, entailing decision-directed equalization, blind and dual-mode processing; performance evaluation by software simulation and sea trials data.
Ámbito científico
Convocatoria de propuestas
Data not availableRégimen de financiación
CSC - Cost-sharing contractsCoordinador
00184 Roma
Italia