A dimension decomposition(DIDE)method for multiple incoherent source localization using uniform circular array(UCA)is proposed.Due to the fact that the far-field signal can be considered as the state where the range p...A dimension decomposition(DIDE)method for multiple incoherent source localization using uniform circular array(UCA)is proposed.Due to the fact that the far-field signal can be considered as the state where the range parameter of the nearfield signal is infinite,the algorithm for the near-field source localization is also suitable for estimating the direction of arrival(DOA)of far-field signals.By decomposing the first and second exponent term of the steering vector,the three-dimensional(3-D)parameter is transformed into two-dimensional(2-D)and onedimensional(1-D)parameter estimation.First,by partitioning the received data,we exploit propagator to acquire the noise subspace.Next,the objective function is established and partial derivative is applied to acquire the spatial spectrum of 2-D DOA.At last,the estimated 2-D DOA is utilized to calculate the phase of the decomposed vector,and the least squares(LS)is performed to acquire the range parameters.In comparison to the existing algorithms,the proposed DIDE algorithm requires neither the eigendecomposition of covariance matrix nor the search process of range spatial spectrum,which can achieve satisfactory localization and reduce computational complexity.Simulations are implemented to illustrate the advantages of the proposed DIDE method.Moreover,simulations demonstrate that the proposed DIDE method can also classify the mixed far-field and near-field signals.展开更多
In this paper,we propose a beam space coversion(BSC)-based approach to achieve a single near-field signal local-ization under uniform circular array(UCA).By employing the centro-symmetric geometry of UCA,we apply BSC ...In this paper,we propose a beam space coversion(BSC)-based approach to achieve a single near-field signal local-ization under uniform circular array(UCA).By employing the centro-symmetric geometry of UCA,we apply BSC to extract the two-dimensional(2-D)angles of near-field signal in the Van-dermonde form,which allows for azimuth and elevation angle estimation by utilizing the improved estimation of signal para-meters via rotational invariance techniques(ESPRIT)algorithm.By substituting the calculated 2-D angles into the direction vec-tor of near-field signal,the range parameter can be conse-quently obtained by the 1-D multiple signal classification(MU-SIC)method.Simulations demonstrate that the proposed al-gorithm can achieve a single near-field signal localization,which can provide satisfactory performance and reduce computational complexity.展开更多
主瓣欺骗式干扰给雷达在电子对抗中的应用带来了挑战。为了解决电子对抗中主瓣距离欺骗干扰的到达方向(direction of arrival,DOA)估计问题,基于均匀圆阵的频率分集阵列(uniform circular array-frequency diverse array,UCA-FDA)雷达,...主瓣欺骗式干扰给雷达在电子对抗中的应用带来了挑战。为了解决电子对抗中主瓣距离欺骗干扰的到达方向(direction of arrival,DOA)估计问题,基于均匀圆阵的频率分集阵列(uniform circular array-frequency diverse array,UCA-FDA)雷达,提出了一种利用距离补偿的DOA估计方法。所提方法通过对雷达接收信号进行距离补偿,消除距离维度上的影响,并将角度联合导向矢量和处理后的协方差矩阵代入多重信号分类(multiple signal classification,MUSIC)算法,从而获得目标的方位角和俯仰角。此外,所提方法还增加了分辨来自同一方向的多个目标的功能,具有角度估计精度高、抗干扰性能好、适用低快拍情景的优点。仿真实验也证明了所提方法的有效性。展开更多
针对水下阵列波达方位(direction of arrival,DOA)估计在少快拍情况下对相邻声源分辨能力差的问题,提出了基于迭代原子范数最小化的均匀圆环阵DOA快速估计方法。所提方法利用模态域处理方法对阵列流形进行预处理,将均匀圆环阵转换为虚...针对水下阵列波达方位(direction of arrival,DOA)估计在少快拍情况下对相邻声源分辨能力差的问题,提出了基于迭代原子范数最小化的均匀圆环阵DOA快速估计方法。所提方法利用模态域处理方法对阵列流形进行预处理,将均匀圆环阵转换为虚拟直线阵,然后通过对角重构估计无噪接收信号协方差矩阵,消除模态域处理引入的非均匀噪声的影响。为了充分利用接收信号稀疏性,同时避免字典网格搜索带来的误差,在模态域引入迭代原子范数最小化稀疏恢复方法,提出均匀圆环阵迭代原子范数最小化(uniform circular array-iterative atomic norm minimization,UCA-IANM)方位估计方法。原子范数最小化稀疏恢复问题一般采用内点法求解,该方法随接收信号快拍数增加,计算量急剧上升,不适用于水下计算资源受限的场景。在交替方向乘子法(alternating direction multiplier method,ADMM)的基础上,针对正则化参数难以选择的问题,提出了基于参数优化ADMM的UCA-IANM(UCA-IANM assisted by ADMM with parameter optimization,UCA-IANM-APO)DOA快速估计算法。仿真实验与实测数据分析表明,UCA-IANM-APO DOA快速估计方法的角度分辨能力和估计精度均优于传统DOA估计方法,求解速度较内点法提升了两个数量级。展开更多
A joint estimation algorithm of direction of arrival （DOA）, frequency, and polarization, based on fourth-order cumulants and uniform circular array （UCA） of trimmed vector sensors is presented for narrowband non-G...A joint estimation algorithm of direction of arrival （DOA）, frequency, and polarization, based on fourth-order cumulants and uniform circular array （UCA） of trimmed vector sensors is presented for narrowband non-Gaussian signals. The proposed approach, which is suitable for applications in arbitrary Gaussian noise environments, gives a closed-form representation of the estimated parameters, without spectral peak searching. An efficient method is also provided for elimination of cyclic phase ambiguities. Simulations are presented to show the performance of the algorithm.展开更多
In this paper, a low complexity direction of arrival(DOA) estimation method for massive uniform circular array(UCA) with single snapshot is proposed.Firstly, the coarse DOAs are estimated by finding the peaks from the...In this paper, a low complexity direction of arrival(DOA) estimation method for massive uniform circular array(UCA) with single snapshot is proposed.Firstly, the coarse DOAs are estimated by finding the peaks from the circular convolution between a fixed coefficient vector and the received data vector.Thereafter, in order to refine coarse DOA estimates, we reconstruct the direction matrix based on the coarse DOA estimations and take the first order Taylor expansion with DOA estimation offsets into account.Finally, the refined estimations are obtained by compensating the offsets, which are obtained via least squares(LS) without any complex searches.In addition, the refinement can be iteratively implemented to enhance the estimation results.Compared to the offset search method, the proposed method achieves a better estimation performance while requiring lower complexity.Numerical simulations are presented to demonstrate the effectiveness of the proposed method.展开更多
本文提出了一种用天线阵来进行多个入射平面波的DOA(direction of arrival)估计方法.这种方法可以解决以往像MUSIC、ESPRIT等算法信号数不能超过阵元数的问题.这种方法计算量少、精度高、可适用于任意几何形状天线阵.同时得到信号频率估...本文提出了一种用天线阵来进行多个入射平面波的DOA(direction of arrival)估计方法.这种方法可以解决以往像MUSIC、ESPRIT等算法信号数不能超过阵元数的问题.这种方法计算量少、精度高、可适用于任意几何形状天线阵.同时得到信号频率估计,在平面阵中可得到自动成对的2维角估计.并且借助于相应技术,可对相关信号源的DOA进行估计.本文以均匀圆环天线阵(UCA)来估计多于阵元数的多个入射平面波空间2维角(俯仰角,方位角)为例进行仿真,最后给出计算机模拟结果证实该方法的实用性、有效性.展开更多
基金supported by the National Natural Science Foundation of China(62022091,61921001).
文摘A dimension decomposition(DIDE)method for multiple incoherent source localization using uniform circular array(UCA)is proposed.Due to the fact that the far-field signal can be considered as the state where the range parameter of the nearfield signal is infinite,the algorithm for the near-field source localization is also suitable for estimating the direction of arrival(DOA)of far-field signals.By decomposing the first and second exponent term of the steering vector,the three-dimensional(3-D)parameter is transformed into two-dimensional(2-D)and onedimensional(1-D)parameter estimation.First,by partitioning the received data,we exploit propagator to acquire the noise subspace.Next,the objective function is established and partial derivative is applied to acquire the spatial spectrum of 2-D DOA.At last,the estimated 2-D DOA is utilized to calculate the phase of the decomposed vector,and the least squares(LS)is performed to acquire the range parameters.In comparison to the existing algorithms,the proposed DIDE algorithm requires neither the eigendecomposition of covariance matrix nor the search process of range spatial spectrum,which can achieve satisfactory localization and reduce computational complexity.Simulations are implemented to illustrate the advantages of the proposed DIDE method.Moreover,simulations demonstrate that the proposed DIDE method can also classify the mixed far-field and near-field signals.
基金supported by the National Natural Science Foundation of China(6192100162022091)the Natural Science Foundation of Hunan Province(2017JJ3368).
文摘In this paper,we propose a beam space coversion(BSC)-based approach to achieve a single near-field signal local-ization under uniform circular array(UCA).By employing the centro-symmetric geometry of UCA,we apply BSC to extract the two-dimensional(2-D)angles of near-field signal in the Van-dermonde form,which allows for azimuth and elevation angle estimation by utilizing the improved estimation of signal para-meters via rotational invariance techniques(ESPRIT)algorithm.By substituting the calculated 2-D angles into the direction vec-tor of near-field signal,the range parameter can be conse-quently obtained by the 1-D multiple signal classification(MU-SIC)method.Simulations demonstrate that the proposed al-gorithm can achieve a single near-field signal localization,which can provide satisfactory performance and reduce computational complexity.
文摘主瓣欺骗式干扰给雷达在电子对抗中的应用带来了挑战。为了解决电子对抗中主瓣距离欺骗干扰的到达方向(direction of arrival,DOA)估计问题,基于均匀圆阵的频率分集阵列(uniform circular array-frequency diverse array,UCA-FDA)雷达,提出了一种利用距离补偿的DOA估计方法。所提方法通过对雷达接收信号进行距离补偿,消除距离维度上的影响,并将角度联合导向矢量和处理后的协方差矩阵代入多重信号分类(multiple signal classification,MUSIC)算法,从而获得目标的方位角和俯仰角。此外,所提方法还增加了分辨来自同一方向的多个目标的功能,具有角度估计精度高、抗干扰性能好、适用低快拍情景的优点。仿真实验也证明了所提方法的有效性。
文摘针对水下阵列波达方位(direction of arrival,DOA)估计在少快拍情况下对相邻声源分辨能力差的问题,提出了基于迭代原子范数最小化的均匀圆环阵DOA快速估计方法。所提方法利用模态域处理方法对阵列流形进行预处理,将均匀圆环阵转换为虚拟直线阵,然后通过对角重构估计无噪接收信号协方差矩阵,消除模态域处理引入的非均匀噪声的影响。为了充分利用接收信号稀疏性,同时避免字典网格搜索带来的误差,在模态域引入迭代原子范数最小化稀疏恢复方法,提出均匀圆环阵迭代原子范数最小化(uniform circular array-iterative atomic norm minimization,UCA-IANM)方位估计方法。原子范数最小化稀疏恢复问题一般采用内点法求解,该方法随接收信号快拍数增加,计算量急剧上升,不适用于水下计算资源受限的场景。在交替方向乘子法(alternating direction multiplier method,ADMM)的基础上,针对正则化参数难以选择的问题,提出了基于参数优化ADMM的UCA-IANM(UCA-IANM assisted by ADMM with parameter optimization,UCA-IANM-APO)DOA快速估计算法。仿真实验与实测数据分析表明,UCA-IANM-APO DOA快速估计方法的角度分辨能力和估计精度均优于传统DOA估计方法,求解速度较内点法提升了两个数量级。
基金This project was supported by the Graduate Innovation Laboratory of Jilin University(502039)Jilin Science Committee of China(20030519)+1 种基金the National Natural Science Foundation of China (69872012)the Foundation of Nanjing Institute of Technology.
文摘A joint estimation algorithm of direction of arrival （DOA）, frequency, and polarization, based on fourth-order cumulants and uniform circular array （UCA） of trimmed vector sensors is presented for narrowband non-Gaussian signals. The proposed approach, which is suitable for applications in arbitrary Gaussian noise environments, gives a closed-form representation of the estimated parameters, without spectral peak searching. An efficient method is also provided for elimination of cyclic phase ambiguities. Simulations are presented to show the performance of the algorithm.
基金supported by the National Natural Science Foundation of China (61971217, 61601167)Jiangsu Planned Project for Postdoctoral Research Funds (2020Z013)+2 种基金China Postdoctoral Science Foundation (2020M681585)the fund of State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System (CEMEE 2021Z0101B)the fund of State Key Laboratory of Marine Resource Utilization in South China Sea (Hainan University)(MRUKF2021033)。
文摘In this paper, a low complexity direction of arrival(DOA) estimation method for massive uniform circular array(UCA) with single snapshot is proposed.Firstly, the coarse DOAs are estimated by finding the peaks from the circular convolution between a fixed coefficient vector and the received data vector.Thereafter, in order to refine coarse DOA estimates, we reconstruct the direction matrix based on the coarse DOA estimations and take the first order Taylor expansion with DOA estimation offsets into account.Finally, the refined estimations are obtained by compensating the offsets, which are obtained via least squares(LS) without any complex searches.In addition, the refinement can be iteratively implemented to enhance the estimation results.Compared to the offset search method, the proposed method achieves a better estimation performance while requiring lower complexity.Numerical simulations are presented to demonstrate the effectiveness of the proposed method.
文摘本文提出了一种用天线阵来进行多个入射平面波的DOA(direction of arrival)估计方法.这种方法可以解决以往像MUSIC、ESPRIT等算法信号数不能超过阵元数的问题.这种方法计算量少、精度高、可适用于任意几何形状天线阵.同时得到信号频率估计,在平面阵中可得到自动成对的2维角估计.并且借助于相应技术,可对相关信号源的DOA进行估计.本文以均匀圆环天线阵(UCA)来估计多于阵元数的多个入射平面波空间2维角(俯仰角,方位角)为例进行仿真,最后给出计算机模拟结果证实该方法的实用性、有效性.
