Parallel arrays with coprime subarrays have shown its potential advantages for two dimensional direction of arrival(DOA)estimation.In this paper,by introducing two flexible coprime factors to enlarge the inter-element...Parallel arrays with coprime subarrays have shown its potential advantages for two dimensional direction of arrival(DOA)estimation.In this paper,by introducing two flexible coprime factors to enlarge the inter-element spacing of parallel uniform subarrays,we propose a generalized parallel coprime array(GPCA)geometry.The proposed geometry enjoys flexible array layouts by the coprime factors and enables to extend the array aperture to achieve great improvement of estimation performance.Meanwhile,we verify that GPCA always can obtain M2 degrees of freedom(DOFs)in co-array domain via 2M sensors after optimization,which outperforms sparse parallel array geometries,such as parallel coprime array(PCA)and parallel augmented coprime array(PACA),and is the same as parallel nested array(PNA)with extended aperture.The superiority of GPCA geometry has been proved by numerical simulations with sparse representation methods.展开更多
Direction of arrival(DOA)estimation for unfolded coprime array(UFCA)is discussed,and a method based on subspace compensation is proposed.Conventional DOA estimation meth-ods partition the UFCA into two subarrays for s...Direction of arrival(DOA)estimation for unfolded coprime array(UFCA)is discussed,and a method based on subspace compensation is proposed.Conventional DOA estimation meth-ods partition the UFCA into two subarrays for separate estimations,which are then combined for unique DOA determination.However,the DOA estimation performance loss is caused as only the partial array aperture is exploited.We use the estimations from one subarray as initial estimations,and then enhance the estimation results via a compensation based on the whole array,which is im-plemented via a simple least squares(LS)operation constructed from the initial estimation and first-order Taylor expansion.Compared to conventional methods,the DOA estimation performance is improved while the computational complexity is in the same level.Multiple simulations are con-ducted to verify the efficiency of the proposed approach.展开更多
文摘Parallel arrays with coprime subarrays have shown its potential advantages for two dimensional direction of arrival(DOA)estimation.In this paper,by introducing two flexible coprime factors to enlarge the inter-element spacing of parallel uniform subarrays,we propose a generalized parallel coprime array(GPCA)geometry.The proposed geometry enjoys flexible array layouts by the coprime factors and enables to extend the array aperture to achieve great improvement of estimation performance.Meanwhile,we verify that GPCA always can obtain M2 degrees of freedom(DOFs)in co-array domain via 2M sensors after optimization,which outperforms sparse parallel array geometries,such as parallel coprime array(PCA)and parallel augmented coprime array(PACA),and is the same as parallel nested array(PNA)with extended aperture.The superiority of GPCA geometry has been proved by numerical simulations with sparse representation methods.
基金the Fund of State Key Laboratory of Com-plex Electromagnetic Environment Effects on Electronics and Information System(CEMEE 2021Z0101B)the Na-tional Natural Science Foundation of China(No.61601167).
文摘Direction of arrival(DOA)estimation for unfolded coprime array(UFCA)is discussed,and a method based on subspace compensation is proposed.Conventional DOA estimation meth-ods partition the UFCA into two subarrays for separate estimations,which are then combined for unique DOA determination.However,the DOA estimation performance loss is caused as only the partial array aperture is exploited.We use the estimations from one subarray as initial estimations,and then enhance the estimation results via a compensation based on the whole array,which is im-plemented via a simple least squares(LS)operation constructed from the initial estimation and first-order Taylor expansion.Compared to conventional methods,the DOA estimation performance is improved while the computational complexity is in the same level.Multiple simulations are con-ducted to verify the efficiency of the proposed approach.
