DOA Estimation with 2D Subspace Fitting Based on SVD
Hao Zeng, Yinghui Zhang, Shizhong Yang · Jisuanji gongcheng · 2010
This paper improves the traditional Direction Of Arrival(DOA) estimation method with subspace fitting.The Singular Value Decomposition(SVD) of the data matrix is employed to replace the Eigenvalue Decomposition(ED) of the covariance matrix which is estimated by the received data snapshots.The singular values and singular value vectors accomplish the estimation for the number of the impinging signals,and the covariance matrix estimation is avoided to mitigate the computation load and estimation error.The 2D Modified Varying Projection(MVP) algorithm is illustrated according to the principle of the 1D MVP.The estimation of the 2D DOA is adopted on the received signal based on the uniform circle array.