  In the ocean environment, reverberation is a common and strong interference
which significantly degrades the performance of target bearing estimation.
Meanwhile, sensor failure is inevitable in actual sonar deployment as the
underwater scene is complicated. Therefore, it is a challenge for target
detection in the ocean reverberation with sensor failure. To address this
issue, we propose an improved approach based on the principle of low rank
characteristics of matrix in this paper. Firstly, we utilize Hankel structured
matrix to counteract the problem of sensor failure. Then, the algorithm of
matrix completion (MC) based on l1-norm and l2-norm are exploited to recover
the true signal matrix from the corrupted received matrix. Numerical results
demonstrate that compared with other related methods, the l1-norm provides
better capability in the probability of recovery and shows the best robustness
of bearing estimation with the narrow beam width and low sidelobe. Moreover,
the proposed approach verifies the performances of reverberation suppression
and achieves high resolution of target detection.
