DOA estimation methods using Weighted Subspace Fitting Technique based on immune evolutionary algorithm

Weighted Subspace Fitting Technique can eliminate coherency between the signal sources, so it is effective to noncoherent signal and coherent signal and the iteration method is often adopted to search DOA. But this method has large amount of computation and the slow search speed. So evolutionary algorithm is introduced to the solution of Weighted Subspace Fitting Technique. Evolutionary algorithm is a computation model to simulate evolution process of creature, and it adopts crossover and mutation to provide optimizing chance or evolution direction, but degradation is inevitable in common evolutionary algorithm. If immune concept is introduced to evolutionary algorithm, degradation phenomenon can be restrained in the optimizing process under the condition of reserving excellent characteristics of original algorithm. So using immune evolutionary algorithm to search DOA in Weighted Subspace Fitting Technique can reduce search time and quicken search speed, and in the end the simulation results validate that this algorithm is effective.