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

摘要

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.