In this letter, the orthogonal projection (OP) estimation of the direction of arrival (DOA) and direction of departure (DOD) of multiple targets for bistatic multiple-input multiple-output radars is addressed. First, a two-dimensional direction finding estimator based on OP technique with automatic pairing is developed. Second, this letter also presents a modified reduced-dimension estimator by utilizing the characteristic of Kronecker product, which only performs two one-dimensional angle estimates. Furthermore, the DOA and DOD pairing is given automatically. Finally, simulation results are presented to verify the efficiency of the proposed estimators.

This letter deals with blind carrier frequency offset estimation by exploiting the minimum variance distortionless response (MVDR) criterion for interleaved uplink orthogonal frequency division multiple access (OFDMA). It has been shown that the complexity and estimation accuracy of MVDR strictly depend on the grid size used during the search. For the purpose of efficient estimation, we present an improved polynomial rooting estimator that is robust in low signal-to-noise ratio scenario. Simulation results are provided for illustrating the effectiveness of the proposed estimator.

This letter presents an effective direction of arrival (DOA) estimator that is based on the orthogonal projection (OP) technique. When an OP matrix is attained, the proposed estimator, which dispenses with spatial smoothing (SS) preprocessing, can form the maximizing orthogonality for a single snapshot. Since this technique does not need to perform eigen-decomposition while maintaining better DOA estimates, it also has real-time DOA estimation capability. Numerical results are presented to illustrate the efficiency of this method.

This letter realizes direction of arrival (DOA) estimation by exploiting the noise subspace based estimator. Since single subspace feature extraction fails to achieve satisfactory results under unknown noise fields, we propose a two-step subspace feature extraction technique that is effective even in these fields. When a new noise subspace is attained, the proposed estimator without prewhitening can form the maximizing orthogonality especially for unknown noise fields. Simulation results confirm the effectiveness of the proposed technique.

This letter deals with adaptive array beamforming based on a minimum variance distortionless response (MVDR) technique with robust capabilities for code-division multiple access signals. It has been shown that the MVDR beamformer suffers from the drawback of being very sensitive to pointing error over the eigenspace-based beamformers. For the purpose of efficient estimation and calibration, a highly efficient approach has been proposed that is implemented on polynomial rooting rather than spectral searching. However, this rooting method is suboptimal in the presence of the noise and multiple access interference (MAI). In this letter, we propose an improved polynomial rooting calibration method that is robust in both of the low signal-to-noise ratio and large MAI scenarios. Several computer simulations are provided for illustrating the effectiveness of the proposed method.

In this letter, we present a blind carrier frequency offset (CFO) estimator by exploiting the subspace-based technique for multicarrier-code division multiple access (MC-CDMA) systems. Relative high accuracy and low-complexity to the CFO estimation can be achieved by rooting a polynomial. Simulation results are provided for illustrating the effectiveness of the proposed blind polynomial rooting estimator.