  In this letter, we employ and design the expectation--conditional
maximization either (ECME) algorithm, a generalisation of the EM algorithm, for
solving the maximum likelihood direction finding problem of stochastic sources,
which may be correlated, in unknown nonuniform noise. Unlike alternating
maximization, the ECME algorithm updates both the source and noise covariance
matrix estimates by explicit formulas and can guarantee that both estimates are
positive semi-definite and definite, respectively. Thus, the ECME algorithm is
computationally efficient and operationally stable. Simulation results confirm
the effectiveness of the algorithm.
