Monostatic MIMO radar direction finding in impulse noise

Abstract

This work considers direction-finding using a monostatic multiple-input multiple-output (MIMO) radar in the presence of impulsive noise. Employing a novel low-order covariance-based exponential kernel function, the proposed maximum likelihood (ML) formulation exploits an introduced quantum whale optimization algorithm (QWOA) to form the direction estimates. The resulting estimates are shown to be robust to the presence of impulsive noise, offering preferable performance as compared to recent related approaches, even in cases when the number of available snapshots is small.