Dimension decomposition algorithm for multiple source loca-lization using uniform circular array

A dimension decomposition(DIDE)method for multi-ple incoherent source localization using uniform circular array(UCA)is proposed.Due to the fact that the far-field signal can be considered as the state where the range parameter of the near-field signal is infinite,the algorithm for the near-field source localization is also suitable for estimating the direction of arrival(DOA)of far-field signals.By decomposing the first and second exponent term of the steering vector,the three-dimensional(3-D)parameter is transformed into two-dimensional(2-D)and one-dimensional(1-D)parameter estimation.First,by partitioning the received data,we exploit propagator to acquire the noise sub-space.Next,the objective function is established and partial derivative is applied to acquire the spatial spectrum of 2-D DOA.At last,the estimated 2-D DOA is utilized to calculate the phase of the decomposed vector,and the least squares(LS)is per-formed to acquire the range parameters.In comparison to the existing algorithms,the proposed DIDE algorithm requires nei-ther the eigendecomposition of covariance matrix nor the search process of range spatial spectrum,which can achieve satisfac-tory localization and reduce computational complexity.Simula-tions are implemented to illustrate the advantages of the pro-posed DIDE method.Moreover,simulations demonstrate that the proposed DIDE method can also classify the mixed far-field and near-field signals.