2-D DOA Estimation Method Based on Dimension Descended Noise Subspace

To improve the speed of the estimation of Direction Of Arrival (DOA), the dimension of the noise subspace is descended by the Singular Value decomposing (SVD) on the intersection of noise subspace and its conjugate one. Then a new method for fast 2-D DOA estimation is proposed based on the double orthogonality of the descended noise subspace to the steering vector and its conjugate one. Theoretical analysis and experiment results show that the newly developed method can be used without any restriction by the array structure and is capable of compressing the range of the dimension of traditional MUltiple SIgnal Classification (MUSIC) spectrum for 2 times, therefore, the calculation capacity of DOA estimate can be reduced to 50% while the estimation precision is the same as that of MUSIC.