Research On The Estimation Algorithms Of Two-dimensional DO A And Polarization Parameters

Direction-of-arrival(DOA)estimation,also referred to as direction finding technique and spatial spectrum estimation,is an important branch in the area of array signal processing,and has been widely used in military and civil fields such as radar,sonar,wireless communication and biomedicine.The passive radar system based on DOA estimation has numerous advantages of high concealment,long operating distance and strong anti-jamming capability,and has gradually become an indispensable role in the electronic countermeasures field.Most of the state of the art passive radar systems use antenna arrays composed of scalar sensors to receive incident signals.However,with the great development of electronic countermeasures technology,the electromagnetic environment is more and more complex so that the scalar sensor arrays cannot meet the needs.The polatization sensitive array composed of electromagnetic vector sensors receives the electromagnetic signals with vector form,which can simultaneously sense the spatial and polarization informantion.Therefore,the study of two-dimensional(2D)DOA and polarization estimation based on polarization sensitive array(PSA)has important practical significance.This dissertation focuses on 2D DOA and polarization estimation algorithms based on polarization sensitive array,and aims to propose some new solutions to the problems in current studies.The main contents of this dissertation are discrebed as followsFirstly,a real-valued MUSIC algorithm is proposed to reduce the computational complexity and enhance the real-time performance,At fisrt,the polarized forward/backward averaging technique is proposed,which converts the eigenvalue decomposition of covariance matrix into real domain.It would reduce the computational complexity of constrcting noise subspace.Then,the estimation of 2D DOA and polarization parameters are decoupled based on rank-defect phenomenon,and the real-valued spatial spectrum function are constructed,which would reduce the computational amount on spectrum peak searching.The polatization parameters are estiated by using the generalized engenvalus decomposition method.The proposed algorithm transforms the parameter estimation from complex domain to real domain,and reduces the demonsion of peak searching,thus redecing the computational complexity greatly.In addition,the polarized forward/backward averaging technique extends the data length of the signal vector,achieving the improvement of estimation accuracy.The simulation results verify the effectiveness of the proposed algorithmSecondly,aiming at the unsatisfactory environment,such as low signal-noise ratio and unequal-power received noise,a new estimation algorithm of 2D DOA and polarization parameters based on sparse representation and reconstruction is proposed.The auto-and cross-covariance matrices of dipole subarray and loop subarray of COLD array are obtained,and the multi-measurement vectors(MMV)are established by vectorization operation.Then,MMV are sparsely represented with 2D spatial grid,and 2D DOA and polarization are estimated by sparse reconstruction method with l1-norm minimization.Since 2D DOA and polarization parameters are completely separated in overcomplete dictionary and coefficient matrix,so that the sparse reconstruction method can make full use of the spatial infomarion in the received signal data,which improve the estimation accurary.Moreover,due to the removal of noise items in the sparse representation model,the effect of niose is suppressed and the estimation accuracy is improved at low singal-noise ratio.Simulation results show that the proposed algorithm has good estimation performance.Finally,a novel 2D DOA and polarization estimation algorithm with parallel co-prime polarization sensitive array is presented to resolve the problems of limited array apeature and degrees of freedom(DOFs)of compact arrays.With the complete measurement of electric field vector,a new cross-covariance marix that not contains polarization parameters is constrcted,and a virtual uniform linear array with higher DOFs is deduced with vectorization operation.Then,the spatial smoothing-based MUSIC and the sparse representation-based method are applied to estimate 2D DOA.At last,the polarization parameters are estimated by least square method.The estimation accuracy is improved due to the enhancement of array aperture and the reducation of mutual coupling effect.Moreover,since the DOF is extended,the underdetermined parameter estimation can be dealt with.The effectiveness of the proposed algorithm is verified by simulation results.