FINITE DATA PERFORMANCE OF MUSIC AND MINIMUM NORM METHODS

In the direction of arrival (DOA) estimation problem, we encounter bot h finite data and insufficient knowledge of array characterization. It is therefore important to study how subspace-based methods perform in such conditions. We analyze the finite data performance of the multip le signal classification (MUSIC) and minimum norm (min. norm) methods in the presence of sensor gain and phase errors, and derive expression s for the mean square error (MSE) in the DOA estimates. These expressi ons are first derived assuming an arbitrary array and then simplified for the special case of an uniform linear array with isotropic sensors . When they are further simplified for the case of finite data only an d sensor errors only, they reduce to the recent results given in [9-12 ]. Computer simulations are used to verify the closeness between the p redicted and simulated values of the MSE.