Research On DOA Estimation Algorithm Based On The Eigen-subspace

Spatial spectrum estimation is an important area in array signal processing,which is widely used in radar,communication and sonar etc. "Spatial spectrum" indicates the energy distribution of the signals in all directions in space.Therefore,if we get the signal"spatial spectrum", we can get the signal direction of arrival(DOA).The spatial spectrum estimation often called"DOA estimation".This paper mainly research on the DOA estimation algorithm based on the eigen- subspace. First introduce the basic principle of DOA estimation techniques, the array signal statistical model and the eigen-structure subspace concept.On this basis,elaborate two main algorithms based on the eigen-subspace--classical MUSIC algorithm and ESPRIT algorithm. Respectively elaborate the concept and principle of the two algorithms, and analyze its performance through the simulation experiment.For traditional subspace algorithm will be ineffect on coherent signals, discuss spatial smoothing technique and its improvement;and analyze its performance by simulation combining MUSIC algorithm.Finally,it is proposed that a fast subspace algorithm using reduced dimension processing for the DOA estimation algorithm based on the eigen-subspace with computationally expensive and time consuming. This algorithm can fast obtain the signal subspace from a submatrix of the array covariance matrix without eigendecompsition.In detail introduce the algorithm solution process and simulation results show that the method is effective.