Compressed Sensing-Based Off-grid 2-D DOA Estimation for Sparse L-shaped
Array and Gain/Phase Uncertainties
Abstract
In this letter, we propose a novel algorithm for sparse L-shaped array
that addresses gain/phase uncertainties and off-grid direction of
arrival estimation using compressed sensing theory. Firstly, the
receiving signal of the sparse array is structured into an Errors in
Variables model. Then, a novel algorithm termed IOMP-TLS is proposed for
off-grid signal reconstruction and gain/phase uncertainties estimation
based on an enhanced greedy algorithm. Finally, the simulations show
that our proposed algorithm is superior to many other methods in
estimation performance.