2-D Direction Finding Algorithm Based on Multi-stage Wiener Filter and DSP Implementation
Jian‐Hong Tang
Abstract
Jian‐Hong Tang
Abstract
In order to locate the radiant sources accurately,2-D DOA estimation of arrival signal is required.The MUSIC algorithm can be extended to estimate the 2-D DOA of radiant sources precisely based on space antenna array.The MUSIC algorithm involves the estimation of the covariance matrix and its eigendecomposition,so it has much computational complexity.To decrease the computational complexity of eigendecomposition in MUSIC algorithm,a fast subspace algorithm based on multi-stage wiener filter (MSWF)was proposed.Utilizing the forward recursion of the MSWF,the signal and noise subspace can be obtained without estimating the covariance matrix and its eigendecomposition,so the computational complexity is reduced.This method is used to estimate the 2-D DOA of source based on arbitrary space array in computer simulation and DSP implementation.This method not only greatly decreases computational complexity and saves computational time efficiently,also obtains as good performance as MUSIC algorithm.
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In order to locate the radiant sources accurately,2-D DOA estimation of arrival signal is required.The MUSIC algorithm can be extended to estimate the 2-D DOA of radiant sources precisely based on space antenna array.The MUSIC algorithm involves the estimation of the covariance matrix and its eigendecomposition,so it has much computational complexity.To decrease the computational complexity of eigendecomposition in MUSIC algorithm,a fast subspace algorithm based on multi-stage wiener filter (MSWF)was proposed.Utilizing the forward recursion of the MSWF,the signal and noise subspace can be obtained without estimating the covariance matrix and its eigendecomposition,so the computational complexity is reduced.This method is used to estimate the 2-D DOA of source based on arbitrary space array in computer simulation and DSP implementation.This method not only greatly decreases computational complexity and saves computational time efficiently,also obtains as good performance as MUSIC algorithm.
Key concepts: Eigendecomposition of a matrix, Computational complexity theory, Algorithm, Signal subspace, Wiener filter, Covariance matrix, Recursion (computer science), Direction of arrival