Fast Gridless DOA Estimation Algorithm for MA-ANS Scenarios Using a Modified FastIPM

This letter presents a fast gridless direction-of-arrival (DOA) estimation algorithm that improves the Fast Interior-Point Method (FastIPM). The proposed algorithm effectively achieves a significant reduction in computational load for large-scale arrays while maintaining an accurate estimation. It reduces the complexity of gridless DOA estimation to
$\mathcal {O}(N^{2})$
per iteration (according to the Landau notation). Compared to the original FastIPM, we extend the received signal data model to account for more general scenarios that include missing array elements and arbitrary number of snapshots. By formulating the problem as an optimization with an obstacle function, we iteratively minimize the dual gap to obtain the optimal solution for atomic norm minimization problem. Extensive numerical simulations demonstrate the algorithm's computational superiority over the state-of-the-art gridless DOA estimation methods, providing excellent resolution and accuracy.