656-664<span style="font-size:10.0pt;font-family:
" times="" new="" roman","serif";mso-fareast-font-family:"times="" roman";mso-bidi-font-family:="" mangal;mso-ansi-language:en-gb;mso-fareast-language:en-us;mso-bidi-language:="" hi"="" lang="EN-GB">In this work an attempt has been made to analyse and discriminate acoustic
backscattered signals from underwater objects of two different materials of PVC
and Brass. A laboratory study of underwater acoustic scattering of spherical
objects of PVC and Brass material is carried out using Empirical Mode
Decomposition (EMD), HilbertTransform (HT) and Support Vector Machine (SVM).
Incident signal used for the measurement is a Linear Frequency Modulated (LFM)
signal of finite duration with the signal bandwidth of 40 kHz to 80 kHz. More
than 80 back scattered acoustic signals from the objects are recorded and processed
for discrimination. An EMD method is designed to decompose the scattered signal
and HT was used to extract the features for discrimination. EMD decomposes the
backscattered signal into intrinsic mode functions ((IMFs) and the significant
features are extracted from the HT. The classification or discrimination is
investigated using support vector machine (SVM) with four types of kernels such
as linear, quadratic, RBF and polynomial.
Performance of the SVM shows that the proposed method using EMD and Hilbert
transform is useful for underwater object discrimination.</span