Algorithm for two cascades adaptive filtering based underwater target dynamic line enhancer

For greatly improving the ability of the underwater detection system to detect the underwater target, TCAFBDLE (two cascade adaptive filtering based dynamic line enhancer) algorithm is developed. In this algorithm, the higher-order cumulant-based energy power function variable step size adaptive dynamic line enhancer is used as the first cascade, whereas the traditional adaptive line enhancer(ALE) is used as the second one. The proposed algorithm is insensitive to white or colored Gaussian noise and perform well in colored non-Gaussian noise case. The kurtosis signal-to-noise ratio (KSNR) is denned by the kurtosis of the input signal. Simulation tests are dynamically conducted using the underwater moving target-radiated data. Simulation results show that the KSNR is improved about 24.4 dB in the colored Raleigh noise or 18.6 dB in the colored mixed noises composed of the uniformly distributed noise, Raleigh distributed noise and Laplacian distributed noise with respect to the original signal-to-noise ratio(SNR) and that the proposed algorithm can perform a drop of about 35.6 dB for colored Raleigh distributed noise spectrum peak or 31.7 dB for the colored mixed noise spectrum peak, whereas the ALE algorithm can only perform a drop of about 6.3dB for colored Raleigh distributed noise spectrum peak or 4.3 dB for the colored mixed noise spectrum peak.