Study On Super-Resolution DOA Estimation And Adaptive Beamforming

Array Signal Processing techniques are widely applied to the fields of Radar, Communication, Navigation, Seismology, Sonar etc, which mainly consist of two parts, the adaptive beamforming and signal DOA (Direction-of-arrival) estimation techniques. Both issues are studied and some new methods are proposed in this thesis.Many of the super-resolution DOA (Direction-of-arrival) estimation algorithms presume the number of signal sources. Since the sample snapshot is limited, however, the available algorithms on source number estimation may fail at lower SNR (signal-to-noise). In this paper, a novel algorithm for high resolution DOA estimation is analyzed, which not only skips sources number estimation and EVD, but also behaves satisfactorily with a few snapshot, it may be viewed as a combination of merit of conventional Capon and Music method. The algorithm's feasibility and robustness were analyzed and verified by the simulation and actual experiment data.As for the adaptive beamforming, two concrete problems which may be met in practice are studied. First, aiming at the reduction of system cost and complexity, by utilizing the characteristic of GSC (General Sidelobe Canceller), a novel dimension-reductional method has been analyzed. This method has low computational complexity due to the designed block matrix and is not sensitive to the system error by using robust processing. Second, for the existence of mismatched signal steering vector and moving interference, an improved adaptive beamforming, based on derivative constraints of input data and estimation of actual signal steering vector, have been analyzed. The algorithm's feasibility and robustness were analyzed and verified by the simulation and actual experiment data.