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Neural network-based radar detection for an ocean environment

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2 Author(s)
Bhattacharya, T.K. ; Commun. Res. Lab., McMaster Univ., Hamilton, Ont., Canada ; Haykin, Simon

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.

Published in:

Aerospace and Electronic Systems, IEEE Transactions on  (Volume:33 ,  Issue: 2 )