Sparse array design has significant implications for improving the accuracy of direction of arrival(DOA)estimation of non-circular(NC)signals.We propose an extended nested array with a filled sensor(ENAFS)based on the...Sparse array design has significant implications for improving the accuracy of direction of arrival(DOA)estimation of non-circular(NC)signals.We propose an extended nested array with a filled sensor(ENAFS)based on the hole-filling strategy.Specifically,we first introduce the improved nested array(INA)and prove its properties.Subsequently,we extend the sum-difference coarray(SDCA)by adding an additional sensor to fill the holes.Thus the larger uniform degrees of freedom(uDOFs)and virtual array aperture(VAA)can be abtained,and the ENAFS is designed.Finally,the simulation results are given to verify the superiority of the proposed ENAFS in terms of DOF,mutual coupling and estimation performance.展开更多
The existing direction-of-arrival(DOA)estimation methods only utilize the current received signals,which are susceptible to noise.In this paper,a method for DOA estimation based on a motion platform is proposed to ach...The existing direction-of-arrival(DOA)estimation methods only utilize the current received signals,which are susceptible to noise.In this paper,a method for DOA estimation based on a motion platform is proposed to achieve high-precision DOA estimation by utilizing past and present signals.The concept of synthetic aperture is introduced to construct a linear DOA estima-tion model.A DOA fine-tuning method based on the linear model is proposed to eliminate the lin-ear DOA variation,achieving a non-coherent accumulation of DOA estimations.Moreover,the baseband modulation and the phase modulation caused by the range history are compensated to achieve the coherent accumulation of all the DOA estimations.Simulation results show that the proposed method can significantly improve the DOA estimated accuracy at low signal-to-noise ratios(SNR).展开更多
The performance of traditional high-resolution direction-of-arrival(DOA)estimation methods is sensitive to the inaccurate knowledge on prior information,including the position of ar-ray elements,array gain and phase,a...The performance of traditional high-resolution direction-of-arrival(DOA)estimation methods is sensitive to the inaccurate knowledge on prior information,including the position of ar-ray elements,array gain and phase,and the mutual coupling between the array elements.Learning-based methods are data-driven and are expected to perform better than their model-based counter-parts,since they are insensitive to the array imperfections.This paper presents a learning-based method for DOA estimation of multiple wideband far-field sources.The processing procedure mainly includes two steps.First,a beamspace preprocessing structure which has the property of fre-quency invariant is applied to the array outputs to perform focusing over a wide bandwidth.In the second step,a hierarchical deep neural network is employed to achieve classification.Different from neural networks which are trained through a huge data set containing different angle combinations,our deep neural network can achieve DOA estimation of multiple sources with a small data set,since the classifiers can be trained in different small subregions.Simulation results demonstrate that the proposed method performs well both in generalization and imperfections adaptation.展开更多
针对现有时间维度波达方向(direction of arrival,DOA)估计方案中,时间调控速率受限导致目标信号频谱混叠的问题,提出了一种基于异步调控的DOA估计方法,该方法能够有效提升调控速率,进而提升信号处理的信号带宽。在不改变时间调控超表面...针对现有时间维度波达方向(direction of arrival,DOA)估计方案中,时间调控速率受限导致目标信号频谱混叠的问题,提出了一种基于异步调控的DOA估计方法,该方法能够有效提升调控速率,进而提升信号处理的信号带宽。在不改变时间调控超表面(time-varying metasurface,TVM)硬件约束的情况下,该方法利用单元状态会持续一段时间的性质,交错不同列单元的变化起始时间,在一个状态持续时间内获得了多个不同的响应。异步调控方法能够使TVM在受材料限制的情况下,等效增加虚拟多通道个数,提高DOA估计的精度。仿真结果验证了方法的有效性,相较于现有的同步调控方法,新方法在DOA估计性能上有了较大提升,能够逼近理论上的最优DOA估计结果。展开更多
为了能够准确高效地对离格信号的波达方向(Direction of Arrival, DOA)进行估计,利用卷积神经网络来提取信号协方差矩阵中的深度特征信息,并采用改进型标签策略来确保网络的估计精度和效率。具体来说,通过带小数的标签来注释协方差矩阵...为了能够准确高效地对离格信号的波达方向(Direction of Arrival, DOA)进行估计,利用卷积神经网络来提取信号协方差矩阵中的深度特征信息,并采用改进型标签策略来确保网络的估计精度和效率。具体来说,通过带小数的标签来注释协方差矩阵构成的张量,并配合上改进后的二进制交叉熵损失函数来使得所提出的小数标签能够用于网络训练。针对DOA估计对应的多标签—多分类的问题,使用了包含6层结构的卷积神经网络的输出单元类别以及幅度来分别对离格信号的DOA整数部分与小数部分进行重构。通过与6种现有典型方法的均方根误差(Root Mean Square Error, RMSE)仿真对比,所提方法能够在信噪比为-10 dB的情况下保持着RMSE<0.5°的优秀表现。虽然无法在较少快拍下正常工作,但该方法在快拍数大于8的条件下仍然保持着RMSE<1°的表现性能。同时,在信号数量为5时,所提方法依然具有较高的估计稳定性,且计算速度能够达到毫秒级,用时明显低于其他方法。展开更多
A new direction finding method is presented to deal with coexisted noncoherent and co- herent signals without smoothing operation. First the direction-of-arrival （DOA） estimation task is herein reformulated as a spa...A new direction finding method is presented to deal with coexisted noncoherent and co- herent signals without smoothing operation. First the direction-of-arrival （DOA） estimation task is herein reformulated as a sparse reconstruction problem of the cleaned array covariance matrix, which is processed to eliminate the affection of the noise. Then by using the block of matrices, the information of DOAs which we pursuit are implied in the sparse coefficient matrix. Finally, the sparse reconstruction problem is solved by the improved M-FOCUSS method, which is applied to the situation of block of matrices. This method outperforms its data domain counterpart in terms of noise suppression, and has a better performance in DOA estimation than the customary spatial smoothing technique. Simulation results verify the efficacy of the proposed method.展开更多
In this paper, a novel DOA estimation methodology based upon the technology of adaptive nulling antenna is proposed. Initially, the nulling antenna obtains the weight vector by LMS algorithm and power inversion criter...In this paper, a novel DOA estimation methodology based upon the technology of adaptive nulling antenna is proposed. Initially, the nulling antenna obtains the weight vector by LMS algorithm and power inversion criterion.Afterwards, reciprocal of the antenna pattern is defined as the spatial spectrum and the extracted peak values are corresponded to the estimated DOA. Through observation of the spectrum and data analysis of variable steps and SNRs, the simulation results demonstrate that the proposed method can estimate DOA above board. Furthermore, the estimation error of the proposed technique is directly proportional to step size and is inversely proportional to SNR. Unlike the existing MUSIC algorithm, the proposed algorithm has less computational complexity as it eliminates the need of estimating the number of signals and the eigenvalue decomposition of covariance matrix. Also it outperforms MUSIC algorithm, the recently proposed MUSIC-Like algorithm and classical methods by achieving better resolution with narrow width of peaks.展开更多
In this paper,a two-dimensional(2 D)direction-of-arrival(DOA)estimation algorithm with increased degrees of freedom for two parallel linear arrays is presented.Being different from the conventional two-parallel linear...In this paper,a two-dimensional(2 D)direction-of-arrival(DOA)estimation algorithm with increased degrees of freedom for two parallel linear arrays is presented.Being different from the conventional two-parallel linear array,the proposed two-parallel linear array consists of two uniform linear arrays with non-equal inter-element spacing.Propagator method(PM)is used to obtain a special matrix which can be utilized to increase the virtual elements of one of uniform linear arrays.Then,the PM algorithm is used again to obtain automatically paired elevation and azimuth angles.The simulation results and complexity analysis show that the proposed method can increase the number of distinguishable signals and improve the estimation precision without increasing the computational complexity.展开更多
Unmanned Aerial Vehicle(UAV)equipped with uniform linear array has been applied to multiple emitters localization.Meanwhile,nested linear array enables to enhance localization resolution and achieve under-determined D...Unmanned Aerial Vehicle(UAV)equipped with uniform linear array has been applied to multiple emitters localization.Meanwhile,nested linear array enables to enhance localization resolution and achieve under-determined Direction of Arrival(DOA)estimation.In this paper,we propose a new system structure for emitters localization that combines the UAV with nested linear array,which is capable of significantly increasing the positioning accuracy of interested targets.Specifically,a localization scheme is designed to obtain the paired two-dimensional DOA(2D-DOA,i.e.azimuth and elevation angles)estimates of emitters by nested linear array with UAV.Furthermore,we propose an improved DOA estimation algorithm for emitters localization that utilizes Discrete Fourier Transform(DFT)method to obtain coarse DOA estimates,subsequently,achieve the fine DOA estimates by sparse representation.The proposed algorithm has lower computational complexity because the coarse DOA estimates enable to shrink the range of over-complete dictionary of sparse representation.In addition,compared to traditional uniform linear array,improved 2D-DOA estimation performance of emitters can be obtained with a nested linear array.Extensive simulation results testify the effectiveness of the proposed method.展开更多
The direction-of-arrival(DoA) estimation is one of the hot research areas in signal processing. To overcome the DoA estimation challenge without the prior information about signal sources number and multipath number i...The direction-of-arrival(DoA) estimation is one of the hot research areas in signal processing. To overcome the DoA estimation challenge without the prior information about signal sources number and multipath number in millimeter wave system,the multi-task deep residual shrinkage network(MTDRSN) and transfer learning-based convolutional neural network(TCNN), namely MDTCNet, are proposed. The sampling covariance matrix based on the received signal is used as the input to the proposed network. A DRSN-based multi-task classifications model is first introduced to estimate signal sources number and multipath number simultaneously. Then, the DoAs with multi-signal and multipath are estimated by the regression model. The proposed CNN is applied for DoAs estimation with the predicted number of signal sources and paths. Furthermore, the modelbased transfer learning is also introduced into the regression model. The TCNN inherits the partial network parameters of the already formed optimization model obtained by the CNN. A series of experimental results show that the MDTCNet-based DoAs estimation method can accurately predict the signal sources number and multipath number under a range of signal-to-noise ratios. Remarkably, the proposed method achieves the lower root mean square error compared with some existing deep learning-based and traditional methods.展开更多
动态超表面天线(dynamic metasurface antenna,DMA)已成为空基平台波达方向(direction of ar rival,DOA)估计的优选技术,但其性能易受平台抖动的影响。针对空基平台在DOA估计中面临的角度随机抖动问题,提出了一种基于DMA异构码本循环卡...动态超表面天线(dynamic metasurface antenna,DMA)已成为空基平台波达方向(direction of ar rival,DOA)估计的优选技术,但其性能易受平台抖动的影响。针对空基平台在DOA估计中面临的角度随机抖动问题,提出了一种基于DMA异构码本循环卡尔曼滤波的抗抖动DOA估计算法。首先,针对角度随机抖动导致的接收端数据非线性问题,提出了一种非线性误差分离方案,将接收数据中的抖动误差转化为易于分离的线性分量,便于后续的抖动分量滤除。其次,为了使接收数据与卡尔曼滤波算法相匹配,提出了一种异构码本循环方案,通过在长时间尺度上构建相同的DMA码字,以支持卡尔曼滤波算法利用累积的时间信息来识别和滤除抖动误差。最后,卡尔曼滤波处理后的数据通过原子范数方法恢复出稀疏信号,并采用基于Han kel矩阵分解的多信号分类(multiple signal classification,MUSIC)方法进行空间谱估计。仿真结果证实,在相同信噪比(signal-to-noise ratio,SNR)条件下,所提方案相较于传统的多次估计平均方案,估计精度提升了48%,估计结果更接近无抖动的理想状态。展开更多
A linear array of diversely polarized antennas with one pair of identical sensors is used to obtain closed-form unambiguous estimation of 2-D direction of arrival （DOA） and polarization. Spatial phase information to...A linear array of diversely polarized antennas with one pair of identical sensors is used to obtain closed-form unambiguous estimation of 2-D direction of arrival （DOA） and polarization. Spatial phase information together with weighted 3-D polarization-angular coherence structure （PACS） are first recovered with fourth-order cumulants manipulation via a new 2-D ESPRIT variant. Spatial filtering is performed to obtain the scaled PACS, from which the closed-form 2-D DOA and polarization estimates can be derived with only quadrant ambiguity involved. The undesired quadrant ambiguity can be further resolved by using the acquired estimate of spatial phase factor.展开更多
The problem of two-dimensional(2 D)direction of arrival(DOA)estimation for double parallel uniform linear arrays is investigated in this paper.A real-valued DOA estimation algorithm of noncircular(NC)signal is propose...The problem of two-dimensional(2 D)direction of arrival(DOA)estimation for double parallel uniform linear arrays is investigated in this paper.A real-valued DOA estimation algorithm of noncircular(NC)signal is proposed,which combines the Euler transformation and rotational invariance(RI)property between subarrays.In this work,the effective array aperture is doubled by exploiting the noncircularity of signals.The complex arithmetic is converted to real arithmetic via Euler transformation.The main contribution of this work is not only extending the NC-Euler-ESPRIT algorithm from uniform linear array to double parallel uniform linear arrays,but also constructing a new 2 Drotational invariance property between subarrays,which is more complex than that in NCEuler-ESPRIT algorithm.The proposed 2 DNC-Euler-RI algorithm has much lower computational complexity than2 DNC-ESPRIT algorithm.The proposed algorithm has better angle estimation performance than 2 DESPRIT algorithm and 2 D NC-PM algorithm for double parallel uniform linear arrays,and is very close to that of 2 D NC-ESPRIT algorithm.The elevation angles and azimuth angles can be obtained with automatically pairing.The proposed algorithm can estimate up to 2(M-1)sources,which is two times that of 2 D ESPRIT algorithm.Cramer-Rao bound(CRB)of noncircular signal is derived for the proposed algorithm.Computational complexity comparison is also analyzed.Finally,simulation results are presented to illustrate the effectiveness and usefulness of the proposed algorithm.展开更多
The problem of two-dimensional direction of arrival(2D-DOA)estimation for uniform planar arrays(UPAs)is investigated by employing the reduced-dimensional(RD)polynomial root finding technique and 2D multiple signal cla...The problem of two-dimensional direction of arrival(2D-DOA)estimation for uniform planar arrays(UPAs)is investigated by employing the reduced-dimensional(RD)polynomial root finding technique and 2D multiple signal classification(2D-MUSIC)algorithm.Specifically,based on the relationship between the noise subspace and steering vectors,we first construct 2D root polynomial for 2D-DOA estimates and then prove that the 2D polynomial function has infinitely many solutions.In particular,we propose a computationally efficient algorithm,termed RD-ROOT-MUSIC algorithm,to obtain the true solutions corresponding to targets by RD technique,where the 2D root-finding problem is substituted by two one-dimensional(1D)root-finding operations.Finally,accurate 2DDOA estimates can be obtained by a sample pairing approach.In addition,numerical simulation results are given to corroborate the advantages of the proposed algorithm.展开更多
Usually,the problem of direction-of-arrival(DOA)estimation is performed based on the assumption of uniform noise.In many applications,however,the noise across the array may be nonuniform.In this situation,the performa...Usually,the problem of direction-of-arrival(DOA)estimation is performed based on the assumption of uniform noise.In many applications,however,the noise across the array may be nonuniform.In this situation,the performance of DOA estimators may be deteriorated greatly if the non-uniformity of noise is ignored.To tackle this problem,we consider the problem of DOA es-timation in the presence of nonuniform noise by leveraging a singular value thresholding(SVT)based matrix completion method.Different from that the traditional SVT method apply fixed threshold,to improve the performance,the proposed method can obtain a more suitable threshold based on careful estimation of the signal-to-noise ratio(SNR)levels.Specifically,we firstly employ an SVT-based matrix completion method to estimate the noise-free covariance matrix.On this basis,the signal and noise subspaces are obtained from the eigendecomposition of the noise-free cov-ariance matrix.Finally,traditional subspace-based DOA estimation approaches can be directly ap-plied to determine the DOAs.Numerical simulations are performed to demonstrate the effective-ness of the proposed method.展开更多
To increase the limited spatial processing gain of physical aperture of UUV(unmanned underwater vehicle) linear array and satisfy the demand of long distance target detection,a flank array based on the synthetic apert...To increase the limited spatial processing gain of physical aperture of UUV(unmanned underwater vehicle) linear array and satisfy the demand of long distance target detection,a flank array based on the synthetic aperture technique is introduced into UUV,and a modified beam domain passive synthetic aperture processing algorithm(BDPSA) suitable for the flank array is proposed concurrently,which sums the beamforming of linear array coherently for successive measurement after phase compensation to make the beam output peak corresponding to the expected target bearing,expand the array aperture effectively and improve the resolution.The simulation of detection probability and distinguishing probability for double targets within 1,1/2,1/3 and 1/4 beam-width shows that the method of BDPSA has lower SNR threshold for target distinguishing,improves the detection probability and distinguishing probability under low SNR,and realizes the long-distance and high resolution bearing estimation because of the obvious improvement of the spatial array gain.展开更多
This paper proposes low-cost yet high-accuracy direction of arrival(DOA)estimation for the automotive frequency-modulated continuous-wave(FMcW)radar.The existing subspace-based DOA estimation algorithms suffer fromeit...This paper proposes low-cost yet high-accuracy direction of arrival(DOA)estimation for the automotive frequency-modulated continuous-wave(FMcW)radar.The existing subspace-based DOA estimation algorithms suffer fromeither high computational costs or low accuracy.We aim to solve such contradictory relation between complexity and accuracy by using randomizedmatrix approximation.Specifically,we apply an easily-interpretablerandomized low-rank approximation to the covariance matrix(CM)and R∈C^(M×M)throughthresketch maties in the fom of R≈OBQ^(H).Here the approximately compute its subspaces.That is,we first approximate matrix Q∈C^(M×z)contains the orthonormal basis for the range of the sketchmatrik C∈C^(M×z)cwe whichis etrated fom R using randomized unifom counsampling and B∈C^(z×z)is a weight-matrix reducing the approximation error.Relying on such approximation,we are able to accelerate the subspacecomputation by the orders of the magnitude without compromising estimation accuracy.Furthermore,we drive a theoretical error bound for the suggested scheme to ensure the accuracy of the approximation.As validated by the simulation results,the DOA estimation accuracy of the proposed algorithm,eficient multiple signal classification(E-MUSIC)s high,closely tracks standardMUSIC,and outperforms the well-known algorithms with tremendouslyreduced time complexity.Thus,the devised method can realize high-resolutionreal-time target detection in the emerging multiple input and multiple output(MIMO)automotive radar systems.展开更多
Synthetic aperture using moving array is widely used for extending array aperture and improving direction of arrival(DOA)estimation performance.This paper proposes a DOA estimation algorithm with non-uniform motion sy...Synthetic aperture using moving array is widely used for extending array aperture and improving direction of arrival(DOA)estimation performance.This paper proposes a DOA estimation algorithm with non-uniform motion synthetic linear array.The proposed method successively estimates the phase correction factors of the signals received by a moving linear array and then compensates the manifold to construct a much larger synthetic array.With the synthetic array,the DOA estimation performance is efficiently improved.Besides,due to the successive phase correction factors estimation,the proposed method can be applied regardless of the configuration and motion of the linear array and can release the request of temporal signal coherence.The simulations validate the effectiveness of the proposed method.展开更多
基金supported by China National Science Foundations(Nos.62371225,62371227)。
文摘Sparse array design has significant implications for improving the accuracy of direction of arrival(DOA)estimation of non-circular(NC)signals.We propose an extended nested array with a filled sensor(ENAFS)based on the hole-filling strategy.Specifically,we first introduce the improved nested array(INA)and prove its properties.Subsequently,we extend the sum-difference coarray(SDCA)by adding an additional sensor to fill the holes.Thus the larger uniform degrees of freedom(uDOFs)and virtual array aperture(VAA)can be abtained,and the ENAFS is designed.Finally,the simulation results are given to verify the superiority of the proposed ENAFS in terms of DOF,mutual coupling and estimation performance.
基金supported in part by the National Science Fund for Excel-lent Young Scholars(No.62222113)in part by the joint Funds of the National Natural Science Foundation of China(No.U22B2015)+1 种基金in part by the stabilization support of National Radar Signal Processing Laboratory(No.KGJ202203)in part by the Fundamental Research Funds for the Central Universities(No.ZDRC2004).
文摘The existing direction-of-arrival(DOA)estimation methods only utilize the current received signals,which are susceptible to noise.In this paper,a method for DOA estimation based on a motion platform is proposed to achieve high-precision DOA estimation by utilizing past and present signals.The concept of synthetic aperture is introduced to construct a linear DOA estima-tion model.A DOA fine-tuning method based on the linear model is proposed to eliminate the lin-ear DOA variation,achieving a non-coherent accumulation of DOA estimations.Moreover,the baseband modulation and the phase modulation caused by the range history are compensated to achieve the coherent accumulation of all the DOA estimations.Simulation results show that the proposed method can significantly improve the DOA estimated accuracy at low signal-to-noise ratios(SNR).
基金the National Natural Sci-ence Foundation of China(No.62101340).
文摘The performance of traditional high-resolution direction-of-arrival(DOA)estimation methods is sensitive to the inaccurate knowledge on prior information,including the position of ar-ray elements,array gain and phase,and the mutual coupling between the array elements.Learning-based methods are data-driven and are expected to perform better than their model-based counter-parts,since they are insensitive to the array imperfections.This paper presents a learning-based method for DOA estimation of multiple wideband far-field sources.The processing procedure mainly includes two steps.First,a beamspace preprocessing structure which has the property of fre-quency invariant is applied to the array outputs to perform focusing over a wide bandwidth.In the second step,a hierarchical deep neural network is employed to achieve classification.Different from neural networks which are trained through a huge data set containing different angle combinations,our deep neural network can achieve DOA estimation of multiple sources with a small data set,since the classifiers can be trained in different small subregions.Simulation results demonstrate that the proposed method performs well both in generalization and imperfections adaptation.
文摘针对现有时间维度波达方向(direction of arrival,DOA)估计方案中,时间调控速率受限导致目标信号频谱混叠的问题,提出了一种基于异步调控的DOA估计方法,该方法能够有效提升调控速率,进而提升信号处理的信号带宽。在不改变时间调控超表面(time-varying metasurface,TVM)硬件约束的情况下,该方法利用单元状态会持续一段时间的性质,交错不同列单元的变化起始时间,在一个状态持续时间内获得了多个不同的响应。异步调控方法能够使TVM在受材料限制的情况下,等效增加虚拟多通道个数,提高DOA估计的精度。仿真结果验证了方法的有效性,相较于现有的同步调控方法,新方法在DOA估计性能上有了较大提升,能够逼近理论上的最优DOA估计结果。
文摘为了能够准确高效地对离格信号的波达方向(Direction of Arrival, DOA)进行估计,利用卷积神经网络来提取信号协方差矩阵中的深度特征信息,并采用改进型标签策略来确保网络的估计精度和效率。具体来说,通过带小数的标签来注释协方差矩阵构成的张量,并配合上改进后的二进制交叉熵损失函数来使得所提出的小数标签能够用于网络训练。针对DOA估计对应的多标签—多分类的问题,使用了包含6层结构的卷积神经网络的输出单元类别以及幅度来分别对离格信号的DOA整数部分与小数部分进行重构。通过与6种现有典型方法的均方根误差(Root Mean Square Error, RMSE)仿真对比,所提方法能够在信噪比为-10 dB的情况下保持着RMSE<0.5°的优秀表现。虽然无法在较少快拍下正常工作,但该方法在快拍数大于8的条件下仍然保持着RMSE<1°的表现性能。同时,在信号数量为5时,所提方法依然具有较高的估计稳定性,且计算速度能够达到毫秒级,用时明显低于其他方法。
基金Supported by the National Natural Science Foundation of China (61072098 61072099+1 种基金 60736006)PCSIRT-IRT1005
文摘A new direction finding method is presented to deal with coexisted noncoherent and co- herent signals without smoothing operation. First the direction-of-arrival （DOA） estimation task is herein reformulated as a sparse reconstruction problem of the cleaned array covariance matrix, which is processed to eliminate the affection of the noise. Then by using the block of matrices, the information of DOAs which we pursuit are implied in the sparse coefficient matrix. Finally, the sparse reconstruction problem is solved by the improved M-FOCUSS method, which is applied to the situation of block of matrices. This method outperforms its data domain counterpart in terms of noise suppression, and has a better performance in DOA estimation than the customary spatial smoothing technique. Simulation results verify the efficacy of the proposed method.
基金support of the Science and Technology Commission of Chongqing through the Nature Science Fund (2013jj B40005)supported by the Fundamental Research Funds for the Central University (106112016CDJZR165508) of China
文摘In this paper, a novel DOA estimation methodology based upon the technology of adaptive nulling antenna is proposed. Initially, the nulling antenna obtains the weight vector by LMS algorithm and power inversion criterion.Afterwards, reciprocal of the antenna pattern is defined as the spatial spectrum and the extracted peak values are corresponded to the estimated DOA. Through observation of the spectrum and data analysis of variable steps and SNRs, the simulation results demonstrate that the proposed method can estimate DOA above board. Furthermore, the estimation error of the proposed technique is directly proportional to step size and is inversely proportional to SNR. Unlike the existing MUSIC algorithm, the proposed algorithm has less computational complexity as it eliminates the need of estimating the number of signals and the eigenvalue decomposition of covariance matrix. Also it outperforms MUSIC algorithm, the recently proposed MUSIC-Like algorithm and classical methods by achieving better resolution with narrow width of peaks.
基金supported by the National Natural Science Foundation of China(51877015,U1831117)the Cooperation Agreement Foundation by the Department of Science and Technology of Guizhou Province of China(LH[2017]7320,LH[2017]7321,[2015]7249)+2 种基金the Innovation Group Major Research Program Funded by Guizhou Provincial Education Department(KY[2016]051)the Foundation of Top-notch Talents by Education Department of Guizhou Province of China(KY[2018]075)PhD Research Startup Foundation of Tongren University(trxy DH1710)。
文摘In this paper,a two-dimensional(2 D)direction-of-arrival(DOA)estimation algorithm with increased degrees of freedom for two parallel linear arrays is presented.Being different from the conventional two-parallel linear array,the proposed two-parallel linear array consists of two uniform linear arrays with non-equal inter-element spacing.Propagator method(PM)is used to obtain a special matrix which can be utilized to increase the virtual elements of one of uniform linear arrays.Then,the PM algorithm is used again to obtain automatically paired elevation and azimuth angles.The simulation results and complexity analysis show that the proposed method can increase the number of distinguishable signals and improve the estimation precision without increasing the computational complexity.
基金Postgraduate Research&Practice Innovation Program of Jiangsu Province(SJCX18_0103,KYCX18_0293)China NSF Grants(61371169,61601167,61601504)+2 种基金Jiangsu NSF(BK20161489)the open research fund of State Key Laboratory of Millimeter Waves,Southeast University(No.K201826)the Fundamental Research Funds for the Central Universities(NO.NE2017103).
文摘Unmanned Aerial Vehicle(UAV)equipped with uniform linear array has been applied to multiple emitters localization.Meanwhile,nested linear array enables to enhance localization resolution and achieve under-determined Direction of Arrival(DOA)estimation.In this paper,we propose a new system structure for emitters localization that combines the UAV with nested linear array,which is capable of significantly increasing the positioning accuracy of interested targets.Specifically,a localization scheme is designed to obtain the paired two-dimensional DOA(2D-DOA,i.e.azimuth and elevation angles)estimates of emitters by nested linear array with UAV.Furthermore,we propose an improved DOA estimation algorithm for emitters localization that utilizes Discrete Fourier Transform(DFT)method to obtain coarse DOA estimates,subsequently,achieve the fine DOA estimates by sparse representation.The proposed algorithm has lower computational complexity because the coarse DOA estimates enable to shrink the range of over-complete dictionary of sparse representation.In addition,compared to traditional uniform linear array,improved 2D-DOA estimation performance of emitters can be obtained with a nested linear array.Extensive simulation results testify the effectiveness of the proposed method.
基金funded by Beijing University of Posts and Telecommunications-China Mobile Research Institute Joint Innovation Center。
文摘The direction-of-arrival(DoA) estimation is one of the hot research areas in signal processing. To overcome the DoA estimation challenge without the prior information about signal sources number and multipath number in millimeter wave system,the multi-task deep residual shrinkage network(MTDRSN) and transfer learning-based convolutional neural network(TCNN), namely MDTCNet, are proposed. The sampling covariance matrix based on the received signal is used as the input to the proposed network. A DRSN-based multi-task classifications model is first introduced to estimate signal sources number and multipath number simultaneously. Then, the DoAs with multi-signal and multipath are estimated by the regression model. The proposed CNN is applied for DoAs estimation with the predicted number of signal sources and paths. Furthermore, the modelbased transfer learning is also introduced into the regression model. The TCNN inherits the partial network parameters of the already formed optimization model obtained by the CNN. A series of experimental results show that the MDTCNet-based DoAs estimation method can accurately predict the signal sources number and multipath number under a range of signal-to-noise ratios. Remarkably, the proposed method achieves the lower root mean square error compared with some existing deep learning-based and traditional methods.
文摘动态超表面天线(dynamic metasurface antenna,DMA)已成为空基平台波达方向(direction of ar rival,DOA)估计的优选技术,但其性能易受平台抖动的影响。针对空基平台在DOA估计中面临的角度随机抖动问题,提出了一种基于DMA异构码本循环卡尔曼滤波的抗抖动DOA估计算法。首先,针对角度随机抖动导致的接收端数据非线性问题,提出了一种非线性误差分离方案,将接收数据中的抖动误差转化为易于分离的线性分量,便于后续的抖动分量滤除。其次,为了使接收数据与卡尔曼滤波算法相匹配,提出了一种异构码本循环方案,通过在长时间尺度上构建相同的DMA码字,以支持卡尔曼滤波算法利用累积的时间信息来识别和滤除抖动误差。最后,卡尔曼滤波处理后的数据通过原子范数方法恢复出稀疏信号,并采用基于Han kel矩阵分解的多信号分类(multiple signal classification,MUSIC)方法进行空间谱估计。仿真结果证实,在相同信噪比(signal-to-noise ratio,SNR)条件下,所提方案相较于传统的多次估计平均方案,估计精度提升了48%,估计结果更接近无抖动的理想状态。
文摘A linear array of diversely polarized antennas with one pair of identical sensors is used to obtain closed-form unambiguous estimation of 2-D direction of arrival （DOA） and polarization. Spatial phase information together with weighted 3-D polarization-angular coherence structure （PACS） are first recovered with fourth-order cumulants manipulation via a new 2-D ESPRIT variant. Spatial filtering is performed to obtain the scaled PACS, from which the closed-form 2-D DOA and polarization estimates can be derived with only quadrant ambiguity involved. The undesired quadrant ambiguity can be further resolved by using the acquired estimate of spatial phase factor.
基金supported by the National Science Foundation of China (No.61371169)the Aeronautical Science Foundation of China(No.20120152001)
文摘The problem of two-dimensional(2 D)direction of arrival(DOA)estimation for double parallel uniform linear arrays is investigated in this paper.A real-valued DOA estimation algorithm of noncircular(NC)signal is proposed,which combines the Euler transformation and rotational invariance(RI)property between subarrays.In this work,the effective array aperture is doubled by exploiting the noncircularity of signals.The complex arithmetic is converted to real arithmetic via Euler transformation.The main contribution of this work is not only extending the NC-Euler-ESPRIT algorithm from uniform linear array to double parallel uniform linear arrays,but also constructing a new 2 Drotational invariance property between subarrays,which is more complex than that in NCEuler-ESPRIT algorithm.The proposed 2 DNC-Euler-RI algorithm has much lower computational complexity than2 DNC-ESPRIT algorithm.The proposed algorithm has better angle estimation performance than 2 DESPRIT algorithm and 2 D NC-PM algorithm for double parallel uniform linear arrays,and is very close to that of 2 D NC-ESPRIT algorithm.The elevation angles and azimuth angles can be obtained with automatically pairing.The proposed algorithm can estimate up to 2(M-1)sources,which is two times that of 2 D ESPRIT algorithm.Cramer-Rao bound(CRB)of noncircular signal is derived for the proposed algorithm.Computational complexity comparison is also analyzed.Finally,simulation results are presented to illustrate the effectiveness and usefulness of the proposed algorithm.
基金supported by the National Natural Science Foundation of China(Nos.61631020,61971218,61601167,61371169)。
文摘The problem of two-dimensional direction of arrival(2D-DOA)estimation for uniform planar arrays(UPAs)is investigated by employing the reduced-dimensional(RD)polynomial root finding technique and 2D multiple signal classification(2D-MUSIC)algorithm.Specifically,based on the relationship between the noise subspace and steering vectors,we first construct 2D root polynomial for 2D-DOA estimates and then prove that the 2D polynomial function has infinitely many solutions.In particular,we propose a computationally efficient algorithm,termed RD-ROOT-MUSIC algorithm,to obtain the true solutions corresponding to targets by RD technique,where the 2D root-finding problem is substituted by two one-dimensional(1D)root-finding operations.Finally,accurate 2DDOA estimates can be obtained by a sample pairing approach.In addition,numerical simulation results are given to corroborate the advantages of the proposed algorithm.
基金the National Natural Science Foundation of China(No.61771316).
文摘Usually,the problem of direction-of-arrival(DOA)estimation is performed based on the assumption of uniform noise.In many applications,however,the noise across the array may be nonuniform.In this situation,the performance of DOA estimators may be deteriorated greatly if the non-uniformity of noise is ignored.To tackle this problem,we consider the problem of DOA es-timation in the presence of nonuniform noise by leveraging a singular value thresholding(SVT)based matrix completion method.Different from that the traditional SVT method apply fixed threshold,to improve the performance,the proposed method can obtain a more suitable threshold based on careful estimation of the signal-to-noise ratio(SNR)levels.Specifically,we firstly employ an SVT-based matrix completion method to estimate the noise-free covariance matrix.On this basis,the signal and noise subspaces are obtained from the eigendecomposition of the noise-free cov-ariance matrix.Finally,traditional subspace-based DOA estimation approaches can be directly ap-plied to determine the DOAs.Numerical simulations are performed to demonstrate the effective-ness of the proposed method.
文摘To increase the limited spatial processing gain of physical aperture of UUV(unmanned underwater vehicle) linear array and satisfy the demand of long distance target detection,a flank array based on the synthetic aperture technique is introduced into UUV,and a modified beam domain passive synthetic aperture processing algorithm(BDPSA) suitable for the flank array is proposed concurrently,which sums the beamforming of linear array coherently for successive measurement after phase compensation to make the beam output peak corresponding to the expected target bearing,expand the array aperture effectively and improve the resolution.The simulation of detection probability and distinguishing probability for double targets within 1,1/2,1/3 and 1/4 beam-width shows that the method of BDPSA has lower SNR threshold for target distinguishing,improves the detection probability and distinguishing probability under low SNR,and realizes the long-distance and high resolution bearing estimation because of the obvious improvement of the spatial array gain.
文摘This paper proposes low-cost yet high-accuracy direction of arrival(DOA)estimation for the automotive frequency-modulated continuous-wave(FMcW)radar.The existing subspace-based DOA estimation algorithms suffer fromeither high computational costs or low accuracy.We aim to solve such contradictory relation between complexity and accuracy by using randomizedmatrix approximation.Specifically,we apply an easily-interpretablerandomized low-rank approximation to the covariance matrix(CM)and R∈C^(M×M)throughthresketch maties in the fom of R≈OBQ^(H).Here the approximately compute its subspaces.That is,we first approximate matrix Q∈C^(M×z)contains the orthonormal basis for the range of the sketchmatrik C∈C^(M×z)cwe whichis etrated fom R using randomized unifom counsampling and B∈C^(z×z)is a weight-matrix reducing the approximation error.Relying on such approximation,we are able to accelerate the subspacecomputation by the orders of the magnitude without compromising estimation accuracy.Furthermore,we drive a theoretical error bound for the suggested scheme to ensure the accuracy of the approximation.As validated by the simulation results,the DOA estimation accuracy of the proposed algorithm,eficient multiple signal classification(E-MUSIC)s high,closely tracks standardMUSIC,and outperforms the well-known algorithms with tremendouslyreduced time complexity.Thus,the devised method can realize high-resolutionreal-time target detection in the emerging multiple input and multiple output(MIMO)automotive radar systems.
基金supported by the Natural Science Foundations of China(Nos.61371169,61601167)the Open Research Fund of National Mobile Communications Research Laboratory of Southeast University(No.2015D030)+2 种基金the Jiangsu Natural Science Foundations(No.BK20161489)the Open Research Fund of State Key Laboratory of Millimeter Waves of Southeast University(No.K201826)the Fundamental Research Funds for the Central Universities(No.NE2017103)
文摘Synthetic aperture using moving array is widely used for extending array aperture and improving direction of arrival(DOA)estimation performance.This paper proposes a DOA estimation algorithm with non-uniform motion synthetic linear array.The proposed method successively estimates the phase correction factors of the signals received by a moving linear array and then compensates the manifold to construct a much larger synthetic array.With the synthetic array,the DOA estimation performance is efficiently improved.Besides,due to the successive phase correction factors estimation,the proposed method can be applied regardless of the configuration and motion of the linear array and can release the request of temporal signal coherence.The simulations validate the effectiveness of the proposed method.
