A model-based approach to solve a deep water ocean acoustic signal processing problem based on a state-space representation of the normal-mode propagation model is developed. The design of a model-based processor (MBP) for signal enhancement employing an array consisting of a large number of sensors for a deep ocean surveillance operation is discussed. The processor provides enhanced estimates of the measured pressure-field, modes, and residual (innovations) sequence indicating the performance or adequacy of the propagation model relative to the data. It is shown that due to the structure of the normal-mode model the state-space propagator is not only feasible for this large scale problem, but in fact, can be implemented by a set of decoupled parallel second-order processors, implying a real-time capability. In the paper we discuss the design and application of the processor to a realistic set of simulated pressure-field data developed from a set of experiments and sound speed parameters.


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    Title :

    Model-based processing for a large aperture array


    Additional title:

    Auf einem Modell basierende akustische Signalverarbeitung für eine aus einer großen Zahl von Sensoren bestehenden Anordnung


    Contributors:

    Published in:

    Publication date :

    1994


    Size :

    10 Seiten, 22 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




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