A robust neural network scheme for constant false alarm rate processing for target detection in clutter environment

The authors present a novel neural network-based CFAR detection scheme (referred to as NN-CFAR scheme) that offers a robust performance in the face of loss of reference cells. This scheme employs a multilayer feedforward neural network trained by the error backpropagation approach using the optimal...

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Bibliographische Detailangaben
Hauptverfasser:	Amoozegar, F., Sundareshan, M.K.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Degradation Detectors Face detection Intelligent networks Multi-layer neural network Neural networks Object detection Radar clutter Radar detection Robustness
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Beschreibung
Zusammenfassung:	The authors present a novel neural network-based CFAR detection scheme (referred to as NN-CFAR scheme) that offers a robust performance in the face of loss of reference cells. This scheme employs a multilayer feedforward neural network trained by the error backpropagation approach using the optimal detector as the teacher.
DOI:	10.1109/ACC.1994.752367