Novel detection schemes are developed using a coherent X-band radar for the detection of small pieces of icebergs. The methods use Wigner-Ville (WV) distribution to perform detection in a joint time-frequency space. Two separate methodologies are presented. The first method extracts classification features from the ambiguity function of the received signal and a neural network is used to perform detection based on these features. The second method uses the method of Principal Components Analysis (PCA) to extract essential information from the time-frequency space for classification. Using real radar data, results are presented and the developed methods are also compared to a conventional Doppler constant false-alarm rate (CFAR) processor.


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    Title :

    Neural network-based radar detection for an ocean environment


    Contributors:


    Publication date :

    1997-04-01


    Size :

    9984545 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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