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Application of neural networks to radar signal detection in K-distributed clutter

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2 Author(s)
Cheikh, K. ; Constantine Univ., Algeria ; Faozi, S.

The radar signal detection is a very complex task, which is generally based on conventional statistical methods. These methods require a lot of computing and they are optimal only for one type of clutter distribution. Recently, artificial neural networks (ANN) have been used as a means of signal detection. In this paper, we consider the problem of radar signal detection using ANN in a K-distributed environment. Two training algorithms are tested; namely, the back propagation (BP) and genetic algorithms (AG) for a MLP architecture. The simulation results have shown that the MLP architecture outperforms the classical CA-CFAR detector.

Published in:

Control, Communications and Signal Processing, 2004. First International Symposium on

Date of Conference:

2004