A Method for Determining Scale Factor of CFAR Detector Based on BP Neural Networks

DOI

10.2991/iccasm.2012.116How to use a DOI?

Keywords

CFAR, Scale factor, BP neural networks

Abstract

As applying constant false alarm rate (CFAR) detection algorithms, an important task is to determine its scale factor according to given false alarm probability. When analytic expression of scale factor vs false alarm probability is difficult or impossible to be obtained, simulation is adopted traditionally. But the computation of simulation is very large. A method for determining scale factor of CFAR detector based on BP neural networks is proposed in the paper using powerful ability to approximate any non-linear expression. Studies of examples indicate training times of BP neural networks approximating relation between false alarm probability and scale factor can be largely shorten, after nonlinear transformation of natural logarithm is applied to input of BP neural networks. Studies also indicate method for determining scale factor based on BP neural networks can provide high accuracy.

Copyright

© 2012, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ling Dang
AU  - Pingjun Wang
AU  - Zhikai Wang
PY  - 2012/08
DA  - 2012/08
TI  - A Method for Determining Scale Factor of CFAR Detector Based on BP Neural Networks
BT  - Proceedings of the 2012 International Conference on Computer Application and System Modeling (ICCASM 2012)
PB  - Atlantis Press
SP  - 459
EP  - 461
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccasm.2012.116
DO  - 10.2991/iccasm.2012.116
ID  - Dang2012/08
ER  -