Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article 2-D DOA Estimation via Matrix Partition and Stacking Technique | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2009 Article ID 896284 8 pages doi 2009 896284 Research Article 2-D DOA Estimation via Matrix Partition and Stacking Technique Nan-Jun Li Jian-Feng Gu and Ping Wei Department of Electronic Engineering University of Electronic Science and Technology of China Chengdu Sichuan 610054 China Correspondence should be addressed to Jian-Feng Gu jianfenggu@ and Ping Wei pwei@ Received 26 February 2009 Revised 14 June 2009 Accepted 31 August 2009 Recommended by M. Greco A novel approach is proposed for the efficient estimation of the two-dimensional 2-D direction-of-arrival DOA of signals impinging on two orthogonal uniform linear arrays ULAs . By partitioning the cross-correlation matrix CCM between two ULAs data into a great deal of submatrices and making use of the submatrices and the symmetric subarrays an extended correlation matrix is constructed and then uses the modified ESPRIT approach to extract out the so-called Kronecker Steering Vectors KSVs of which each is the Kronecker product of the elevation and azimuth angle with a one-to-one relationship. Upon that the proposed method yields the estimate of the 2-D DOA efficiently without requiring the additionally computational burden to remove the pair-matching problem. Furthermore the main idea of the matrix partition and stacking is to much-enhanced subspace estimate. So based on the use of the concept the proposed method s performance is better than the existing similar approaches. Meanwhile unlike the traditional subspace methods it is shown that the proposed can resolve the same uncorrelated sources as the number of subarray sensor through a delicate partition-and-stacking process. Simulation results demonstrate that the proposed method is superior to the existing techniques in both DOA estimation and the detection capability of sources. Copyright 2009 Nan-Jun Li et al. This is an open access article
