Sequence Comparison in Reconstruction and Targeting in Underwater Sonar Imaging

Abstract

An analysis of different sequences for the reconstruction and targeting of underwater sonar images is presented. The sonar images are assumed to be sparse, and their reconstruction is possible by using the compressive sensing theory. The goal is to localize and reconstruct targets by using an iterative version of the orthogonal matching pursuit (OMP) method. The sequences which are used as the transmitted signal waveforms are formed with: the Alltop sequence, the M sequence, a random Gaussian sequence, a binary random sequence, the Zadoff-Chu sequence, and the Bjorck sequence. The comparison of the reconstruction results is done for various numbers of samples in the sequences and sparsity levels. An analysis of the performance for each of the sequences in various noise levels is done as well. Percentage of successfully detected targets is used as a performance measure.