Numerically Efficient Implementation of JADE ML Algorithm

Numerical implementation of JADE (Joint Angle and Delay Estimation) ML (Maximum Likelihood) requires multidimensional nonlinear optimization which is computationally intensive and is highly dependent on initial estimates. If the number of the incident signal is L, we have to perform 2L-dimensional search which is computationally intensive for large L. To alleviate the high computational load associated with multi-dimensional search, we replace multi-dimensional search with successive two-dimensional search. Performance of the proposed scheme is evaluated using numerical results.