Wideband super-resolution bearing estimation method utilizing sparse representation solver after focusing transformation

To aim at the problem that wideband coherent bearing estimation cannot deal with adjacent weak sources well enough in passive sonar, a super-resolution method utilizing sparse representation solver after wideband focusing transformation was presented. The snapshots at different frequency were transformed into one general representation at the reference frequency. The model was reformulated as a problem of sparse representation for multiple measurement vectors. And then it was solved in a second-order cone programming framework by the interior point algorithm to achieve a super-resolution spatial spectrum. The results of simulations indicated that the proposed method had a better performance in the aspects of weak sources resolution and bearing estimation accuracy than wideband incoherent or coherent signal-subspace methods. The good performance was also verified by the sea trial data of a 32-element towed array sonar, and it also demonstrated that the proposed method was feasible to be applied in passive sonar.