Study On Two Dimensional Direction Finding And Adaptive Beamforming

This dissertation is devoted to a study of Two-dimensional Direction finding and Adaptive Beamfroming.The work finished in this paper is a part of a large scale army project of research undertaken by the lab the author works with.Direction of arrival(DOA)estimation and beamforming(BF),as kernel topics of array signal processing,have attracted considerable attentions.In this field,numerous achievements of theoretical research were attained in the past decades.Two-dimensional(2-D)direction finding (DF)and beamforming,compared with its one-dimensional(1-D)counterpart,utilize the spatial information of signals more fully,thus result in performance improvements in location accuracy and communication capacity,and have more practical values as well as even wider application fields.However in 2-D array processing,due to its complexity,there are many difficult problems to be solved such as angle ambiguity,aperture losing,DOA estimation of fast moving targets or short signals,DOA estimation in multiuser and multipath environments,robust adaptive BF etc.. This dissertation is focusing on 2-D direction finding and robust beamforming.Some novel or improved methods as solutions to the above mentioned problems are proposed.Angle ambiguity problem in DOA matrix methods and the like is analyzed first,and then some improved algorithms are proposed.A conclusion is drawn that angle ambiguity exists anywhere in 2-D DOA estimation methods based on rotational invariance and can never be avoided as long as the angle parameter is obtained directly by the use of steering vector,thus some auxiliary methods must be taken to solve the problem.Two algorithms of 2-D direction finding based on temporal smoothing are proposed for multiuser and multipath situations aiming at double parallel uniform linear array and uniform circular array respectively.The algorithms can make 2-D DOA estimations of all paths of non-Gaussian signals in Gaussian noise and can group DOAs according to their coherence,thus are suitable for mobile communication.Besides,the maximum number of estimated DOAs is much more than the number of sensors.The computational complexity of the temporal smoothing algorithms is high and the algorithms hold only for the channel model of block fading.A single-snapshot 2-D direction finding method based on double parallel uniform linear arrays,called SS-DOAM method,is brought forward for the first time in the field.DOAs of M-1 signals,no matter whether they are coherent or not,can be estimated using M pairs of elements. Requiring only one snapshot data,the algorithm is very suitable for instant signals and fast moving targets.Based on above SS-DOAM method,a new 2-D DOA estimation method for the situations of multiuser and multipath is proposed.Being different form the above proposed method based on temporal smoothing,this method is not constrained to block fading channel model and the computational complexity is also remarkably reduced.However this method can not be used for the arrays other than double parallel uniform linear array. In the aspect of space-time 2-D direction finding,two new algorithms,i.e.space-time matrix pencil algorithm for uniform circular array(UCA)and space-time 2-D Unitary-ESPRIT algorithm for arbitrary array,are proposed.The common features of them lie in that they utilize fully the spatial and temporal information of signals and they estimate 2-D parameters only by the use of eigenvalues,thus the angle ambiguity can be avoided completely,and the sensor utilization factor becomes higher.But the strategies of them are distinct.One of them uses matrix pencil technique and the other uses Unitary-ESPRIT.In Matrix pencil method 2-D parameters are obtained according to the magnitude and phase of generalized eigenvalues,while in Unitary-ESPRIT method 2-D parameters are obtained according to the imaginary and real parts of eigenvalues.By comparison,the latter one is more flexible in array configuration,however is higher in computational complexity.Finally,a robust adaptive beamforming method is provided in Chapter 7 which is suitable for both 1-D and 2-D beamforming and can implement optimal beamforming only using partial and rough DOA information of coherent paths of desired signal by the criterion of maximum SINR.The algorithm makes blind algorithms capable of identify expected signals and solved the problem of sensitivity to system errors of non-blind beamforming algorithm.Simulation results proved the feasibility and robustness of the proposed algorithm.