An intelligent detection scheme for sonar signal tracking

A novel version of the adaptive sonar signal thresholding scheme using RBF neural networks is proposed in this paper. Intensity thresholding has proven to be an effective technique to eliminate the low energy noise and to reduce the computational load in an underwater target tracking system. The adopted technique yields unbiased estimates under a non-homogenous sea environment, because the false alarm rate is maintained at a constant level while the threshold changes with different sea environments. In addition, the threshold for different range cells can be adaptively estimated, since the noise under estimation is strictly local so that the distance the sonar signals travelled does not affect the received intensities of noise and targets. Finally, the computational requirements are greatly reduces through the introduction of a recursive proposed scheme.