%0 Journal Article
%A LIU Deliang
%A WANG Bo
%T Two-dimensional parameter estimation of near-field sources based on iterative adaptive approach
%D 2019
%R 10.11772/j.issn.1001-9081.2018061417
%J Journal of Computer Applications
%P 523-527
%V 39
%N 2
%X A Near-Field Iterative Adaptive Approach (NF-IAA) was proposed for the joint estimation of Direction Of Arrival (DOA) and range of near-field sources. Firstly, all possible source locations in the neaar field region were represented by dividing two-dimensional grids. Each location was considered to have a potential incident source mapping to an array, indicating the output data model of the array. Then, through the loop iteration, the signal covariance matrix was constructed by using the previous spectral estimation results, and the inverse of the covariance matrix was used as the weighting matrix to estimate the energy of the potential sources corresponding to each location. Finally, the three-dimensional energy spectrum was figured. Since only the energy of real existing source is not 0, the angles and distances corresponding to the peaks are the two-dimensional location parameters of real existing sources. Simulation experimental results show that the DOA resolution probability of the proposed NF-IAA reaches 90% with 10 snapshots, while the DOA resolution probablity of Two-Dimension Multiple Signal Classification (2D-MUSIC) algorithm is only 40%. When the number of snapshots is reduced to 2, 2D-MUSIC algorithm has failed, but NF-IAA can still distinguish 3 incident sources and accurately estimate the two-dimension location parameters. As the number of snapshots and Signal-to-Noise Ratio (SNR) increase, NF-IAA always performs better than 2D-MUSIC. The experimental results show that NF-IAA has the ability to estimate the two-dimensional location parameters of near-field sources with high precision and high resolution when the number of snapshots is low.
%U https://www.joca.cn/EN/10.11772/j.issn.1001-9081.2018061417