One-Bit DOA Estimation via $\ell_{1}$-Norm Shannon Entropy Function Minimization

In recent years, compressive sensing (CS) techniques have been effectively applied in direction-of-arrival (DOA) estimation with infinite precision. However, in practical scenarios, it is still quite challenging to achieve a trade-off between high fidelity and low hardware complexity. Therefore, in this paper, the problem of DOA estimation with one-bit measurements is investigated. A method via normalized
$\ell_{1}$
-norm Shannon entropy function (
$\ell_{1}$
-SEF) minimization is proposed to deal with the complex-valued signals and multiple-measurement vectors (M-MV) in DOA estimation. A generalized fixed-point continuation (GFPC) algorithm is adopted to solve the converted reweighted
$\ell_{1}$
-norm problems. Simulation results are provided to illustrate the effectiveness and superiority of the proposed
$\ell_{1}$
-SEF based DOA estimator over existing approaches.