Iterative DOA Estimation Using Subspace Tracking Methods and Adaptive Beamforming

摘要

To understand radio propagation structures and consider signal recovering techniques in mobile communications, it is most effective to estimate the signal parameters (e.g., DOA) of individual incoming waves. Also, in radar systems, it is required to discriminate the desired signal from interference. As one of the high-resolution DOA estimators, MUSIC and ESPRIT have attracted considerable attention in recent years. They need the eigenvectors of the correlation matrix and therefore we have to execute the EVD (eigenvalue decomposition) of correlation matrix. However, the EVD generally brings us a heavy computational load and as a result it is difficult to realize the real-time DOA estimator, which will be useful as a multibeam-forming algorithm for adaptive antennas. This paper focuses on MUSIC and ESPRIT using subspace tracking methods, such as BiSVD, PAST, and PASTd, to carry out iterative DOA estimation. Then, they are compared through computer simulation. Adaptive beamforming based on DCMP and MLM is also mentioned and an example is shown.