High Resolution DOA Estimation in MIMO Radar Using Principal Weight Vector for Multiple Targets

In Radar applications, we are in need to identify the signals from the desired directions and to avoid unwanted signals from the enemies, which can be achieved by using the direction of arrival (DOA) estimation. Now-a-days we also meet the situation to use the power resources in an efficient manner by reducing the power allocation for inessential activities. In this paper, we consider these problems for multiple-input-multiple-output (MIMO) radar by introducing the principal weight vector which only allocates the power for the desired spatial sector locations and also enables the different DOA algorithms such as Root multiple signal classification (Root-MUSIC) algorithm, Estimation of Signal Parameter via rotational invariance technique (ESPRIT), Beamscan Estimator and Minimum variance distortionless response (MVDR) estimator (Capon Estimator) with high resolution. The design of principal weight vector in multiple-input-multiple-output (MIMO) radar aims to focus the energy transmission in the desired directions as well as in the other directions. The principal weight vector design is used to maximize the power of the transmitted signals along with the direction of desired spatial sector by minimizing the power in out-of-sector directions. For transmit power distribution, we use the principal weight vector which distributes the power in an efficient manner. This type of power allocation in the desired directions is used to establish the direction of arrival (DOA) estimation at the receiver with high resolution. From these results, comparing the performance level of DOA algorithms using the root mean square error (RMSE) with signal-to-noise ratio (SNR) values.