Abstract:The direction of arrival estimation has been widely employed in Wireless Sensor Networks. This paper proposes a Weighted Subspace Fitting algorithm which can largely reduce the computation amount when doing high-dimensional non-linear optimization by limiting the genetic searching space. This method uses rotation invariant subspace and unbiased estimator of the theoretical minimum error to limit the search space and the complexity of WSF algorithm is reduced by shortening the genetic length of genetic algorithm. The simulation results show that this algorithm has the same performance as the WSF algorithm. Compared with other intelligent optimization algorithms, the proposed algorithm significantly reduces the computational complexity of the algorithm.