New direction of arrival estimation method for wideband coherent signals

To estimate the direction-of-arrival （DOA） of wideband coherent signals, a new method by modifying the orthogonality of the projected suhspaces method is proposed. And it can deal with randomly position perturbed arrays by using the Toeplitz method. This method needn＇t the primary information of DOA for focusing matrix and the sector dividing of interpolated method, which improving the precision of estimation and reducing the computational complexity. Simulations illustrate the effectiveness of this method.

Wideband direction-of-arrival estimation based on cubic spline function

A new direction-of-arrival （DOA） estimation algorithm for wideband sources is introduced, The new method obtains the output of the virtual arrays in the signal bandwidth using cubic spline function interpolation techniques. The narrowband high- resolution algorithm is then used to get the DOA estimation. This technique does not require any preliminary knowledge of DOA angles. Simulation results demonstrate the effectiveness of the method.

Wideband angle of arrival estimation of chirp signals using virtual Wignerville distribution

To estimate the angle of arrivals （AOA） of wideband chirp sources, a new timo-frequency algorithm is proposed. In this method, virtual sensors are constructed based on the fact that the steering vectors of wideband chirp signals are linear and vary with time. And the randon Wignersville distribution （RWVD） of real sensors and virtual sensors are calculated to yield the new time-invariable steering vectors, furthermore, the noise and cross terms are suppressed. In addition, the multiple chirp signals are selected by their time-frequency points. The cost of computation is lower than the common AOA estimation methods of wideband sources due to nonrequirement of frequency focusing, interpolating and matrix decomposition, including subspace decomposition. Under the lower signal noise ratio （SNR） condition, the proposed method exhibits better precision than the method of frequency focusing （FF）. The proposed method can be further applied to nonuniform linear array （NLA） since it is not confined to the array geometry. Simulation results illustrate the efficacy of the proposed method.

DOA estimation method for wideband signals by block sparse reconstruction

For the direction of arrival（DOA） estimation,traditional sparse reconstruction methods for wideband signals usually need many iteration times.For this problem,a new method for two-dimensional wideband signals based on block sparse reconstruction is proposed.First,a prolate spheroidal wave function（PSWF） is used to fit the wideband signals,then the block sparse reconstruction technology is employed for DOA estimation.The proposed method uses orthogonalization to choose the matching atoms,ensuring that the residual components correspond to the minimum absolute value.Meanwhile,the vectors obtained by iteration are back-disposed according to the corresponding atomic matching rules,so the extra atoms are abandoned in the course of iteration,and the residual components of current iteration are reduced.Thus the original sparse signals are reconstructed.The proposed method reduces iteration times comparing with the traditional reconstruction methods,and the estimation precision is better than the classical two-sided correlation transformation（TCT）algorithm when the snapshot is small or the signal-to-noise ratio（SNR） is low.

Polynomial-rooting based fourth-order MUSIC for direction-of-arrival estimation of noncircular signals

A polynomial-rooting based fourth-order cumulant algorithm is presented for direction-of-arrival（DOA） estimation of second-order fully noncircular source signals, using a uniform linear array（ULA）. This algorithm inherits all merits of its spectralsearching counterpart except for the applicability to arbitrary array geometry, while reducing considerably the computation cost.Simulation results show that the proposed algorithm outperforms the previously developed closed-form second-order noncircular ESPRIT method, in terms of processing capacity and DOA estimation accuracy, especially in the presence of spatially colored noise.

DOA estimation of coexisted noncoherent and coherent signals via sparse representation of cleaned array covariance matrix

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.

基于压缩感知的阵元位置无源校准及DOA估计

文章针对阵元位置误差导致水听器阵列性能恶化的问题,提出一种适用于均匀线阵列的阵元位置无源校准方法。该方法综合远场阵列模型和宽带信号空间谱的特性,利用压缩感知技术,将阵元实际位置估计问题转化为稀疏信号的重建,建立了阵元位置误差模型,构建了相应的优化函数,并采用正交匹配追踪(Orthogonal Matching Pursuit,OMP)算法解算阵元实际位置。计算机仿真验证表明,基于压缩感知的方法能有效改善阵元位置误差造成的空间谱估计失效问题,可为目标方位角(Direction of Arrival,DOA)估计提供有效的技术支撑。

宽带相干信号DOA和极化参数联合估计方法

针对宽带相干信号下波达角和极化参数的联合估计问题,提出了一种低复杂度的参数估计方法。首先,通过轴向虚拟平移对圆阵接收信号进行平滑,而后对平滑后的自相关矩阵进行聚焦。之后,联合聚焦后的自协方差矩阵和平滑后的互协方差矩阵构造极化波达方向矩阵。然后,通过该矩阵的特征值和特征向量,经闭合式求解出入射信号的波达角和极化参数。所提算法实现了估计参数的自动配对,无需谱峰搜索,计算量小,且仅需3个阵元即可实现参数估计,能够节约硬件资源。仿真实验从复杂度、有效性和稳健性3个方面验证了所提算法的可行性。

Estimating DOA and polarization with spatially spread loop and dipole pair array

The nonuniform L-shaped spatially spread loop and dipole（SSLD） array whose inter-element spacing is greater than half a wavelength is studied. A joint parameter estimation algorithm of direction of arrival（DOA）, frequency and polarization is presented for plane-wave signals. The direct sampling and the corresponding delayed sampling data are used to construct the data correlation matrix. On the basis of the subspace theory and the least square method, the frequency and the steering vector of the whole array are obtained. According to the relationship of the array manifold vector between electric dipoles and magnetic loops,the polarization parameters are given. The unambiguous phase estimates are acquired by applying virtual baseline array transformation to the spatial steering vectors, and they are used as coarse references to disambiguate the cyclic phase ambiguities in phase differences between two adjacent array elements on the array,then the high accuracy DOA estimates are obtained. Closed-form solutions for each parameter are obtained. This method has advantages of lower calculation complexity and no parameter matching. The experiment results verify the effectiveness and feasibility of the presented algorithm.

A Real-Valued 2D DOA Estimation Algorithm of Noncircular Signal via Euler Transformation and Rotational Invariance Property

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.

基于噪声圆形特性的宽带相干信号DOA估计方法

针对色噪声下基于差分去噪的宽带相干信号波达方向(direction of arrival,DOA)估计方法对相干信源数有限制的问题,提出一种基于噪声圆形特性去噪和Toeplitz矩阵重构的估计算法。首先,对接收到的信号求取协方差矩阵,利用噪声的圆形特性消除噪声。为达到对协方差矩阵进行Toeplitz矩阵重构的要求,通过协方差矩阵相乘来构造新的数据协方差矩阵。然后,通过Toeplitz矩阵重构来解相干。最后,利用旋转子空间算法准则构造聚焦矩阵,使用传播算子算法实现DOA估计。理论分析及仿真实验验证了该算法的有效性,该算法对相干信源数的奇偶没有限制,同时该算法也适用于高斯白噪声下宽带相干信号DOA估计的场景。

Combined UAMP and MF Message Passing Algorithm for Multi-Target Wideband DOA Estimation with Dirichlet Process Prior

When estimating the direction of arrival (DOA) of wideband signals from multiple sources, the performance of sparse Bayesian methods is influenced by the frequency bands occupied by signals in different directions. This is particularly true when multiple signal frequency bands overlap. Message passing algorithms (MPA) with Dirichlet process (DP) prior can be employed in a sparse Bayesian learning (SBL) framework with high precision. However, existing methods suffer from either high complexity or low precision. To address this, we propose a low-complexity DOA estimation algorithm based on a factor graph. This approach introduces two strong constraints via a stretching transformation of the factor graph. The first constraint separates the observation from the DP prior, enabling the application of the unitary approximate message passing (UAMP) algorithm for simplified inference and mitigation of divergence issues. The second constraint compensates for the deviation in estimation angle caused by the grid mismatch problem. Compared to state-of-the-art algorithms, our proposed method offers higher estimation accuracy and lower complexity.

Modified MUSIC estimation for correlated signals with compressive sampling arrays

This paper addresses the issue of the direction of arrival （DOA） estimation under the compressive sampling （CS） framework. A novel approach, modified multiple signal classification （MMUSIC） based on the CS array （CSA-MMUSIC）, is proposed to resolve the DOA estimation of correlated signals and two closely adjacent signals. By using two random CS matrices, a large size array is compressed into a small size array, which effectively reduces the number of the front end circuit. The theoretical analysis demonstrates that the proposed approach has the advantages of low computational complexity and hardware structure compared to other MMUSIC approaches. Simulation results show that CSAMMUSIC can possess similar angular resolution as MMUSIC.

SAGE-based algorithm for DOA estimation and array calibration in the presence of sensor location errors

The direction of arrival(DOA) estimation problem in the presence of sensor location errors is studied and an algorithm based on space alternating generalized expectation-maximization(SAGE) is presented. First, the narrowband case is considered.Based on the small perturbation assumption, this paper proposes an augmentation scheme so as to estimate DOA and perturbation parameters. The E-step and M-step of the SAGE algorithm in this case are derived. Then, the algorithm is extended to the wideband case. The wideband SAGE algorithm is derived in frequency domain by jointing all frequency bins. Simulation results show that the algorithm achieves good convergence and high parameter estimation precision.

COMPUTATIONALLY EFFICIENT ESPRIT METHOD FOR DIRECTION FINDING

In this paper,a low complexity ESPRIT algorithm based on power method and Orthogo- nal-triangular (QR) decomposition is presented for direction finding,which does not require a priori knowledge of source number and the predetermined threshold (separates the signal and noise ei- gen-values).Firstly,according to the estimation of noise subspace obtained by the power method,a novel source number detection method without eigen-decomposition is proposed based on QR de- composition.Furthermore,the eigenvectors of signal subspace can be determined according to Q matrix and then the directions of signals could be computed by the ESPRIT algorithm.To determine the source number and subspace,the computation complexity of the proposed algorithm is approximated as (2log_2 n+2.67)M^3,where n is the power of covariance matrix and M is the number of array ele- ments.Compared with the Single Vector Decomposition (SVD) based algorithm,it has a substantial computational saving with the approximation performance.The simulation results demonstrate its effectiveness and robustness.

Weak signal direction of arrival estimation for colocated multiple-input multiple-output sonar array

In order to suppress the influence of symmetrical noise component on multiple-input multiple-output(MIMO)sonar’s direction of arrival(DOA)estimation under the condition of low signal-to-noise ratio,we propose a DOA estimation algorithm based on covariance matrix reconstruction method.Firstly,the noise field can be decomposed into symmetrical noise field and asymmetrical noise field.We utilize symmetry property of colored noise matrix and the feature that the imaginary part of covariance matrix has no relation with the symmetry noise to remove the real part of covariance matrix.This operation helps to suppress the influence of colored noise on DOA estimation accuracy.Based on the principle of the imaginary matrix part displacement and the dimension reduction transformation method,the real part of covariance matrix is reconstructed,which helps to suppress the bilateral spectrum interference.Thereafter,Toeplitz method is applied for the covariance matrix decorrelation amendment,and a noise subspace is formed by singular value decomposition(SVD).Finally,we can estimate the DOA of target signals.Both theoretical analysis results and numerical simulation results verify the symmetrical noise suppression performance of this algorithm,and the estimation performance of target azimuth is improved obviously.This method has the characteristics of lower operational complexity,higher degrees of freedom and stronger target resolution.

ESTIMATION OF 2-D DOA USING NON-CIRCULAR MUSIC METHOD FOR UNIFORM CIRCULAR AND RECTANGULAR ARRAYS

This paper extends the Non-Circular MUltiple SIgnal Classification(MUSIC)(NC-MUSIC) method for the common array geometries including Uniform Circular Arrays(UCAs) and Uniform Rectangular Arrays(URAs),which enables the algorithm to estimate 2-D Direction Of Arrival(DOA).A comparison between UCAs and URAs of NC-MUSIC is made in this paper.The simulations show that the NC-MUSIC method doubles the maximum estimation number of standard MUSIC.Using non-circular signals,the performance of URAs is improved remarkably while the improvement of UCAs is not so significantly.Moreover,the influence of arrays structures on the NC-MUSIC method is discussed.

Polarization quaternion DOA estimation based on vector MISC array

This paper examines the direction of arrival(DOA)estimation for polarized signals impinging on a sparse vector sensor array which is based on the maximum interelement spacing constraint(MISC).The vector array effectively utilizes the polarization domain information of incident signals,and the quaternion model is adopted for signals polarization characteristic maintenance and computational burden reduction.The features of MISC arrays are crucial to the mutual coupling effects reduction and higher degrees of freedom(DOFs).The quaternion data model based on vector MISC arrays is established,which extends the scalar MISC array into the vector MISC array.Based on the model,a quaternion multiple signal classification(MUSIC)algorithm based on vector MISC arrays is proposed for DOA estimation.The algorithm combines the advantages of the quaternion model and the vector MISC array to enhance the DOA estimation performance.Analytical simulations are performed to certify the capability of the algorithm.

A SUBARRAY-SYNTHESIS BASED 2D DOA ESTIMATION METHOD

In some satellite communications, we need to perform Direction Of Arrival (DOA) angle estima- tion under the restriction that the number of receivers is less than that of the array elements in an array antenna. To solve the conundrum, a method named subarray-synthesis-based Two-Dimensional DOA (2D DOA) angle estimation is proposed. In the method, firstly, the array antenna is divided into a series of subarray antennas based on the total number of receivers; secondly, the subarray antennas’ output covariance matrices are esti- mated; thirdly, an equivalent covariance matrix is synthesized based on the subarray output covariance matri- ces; then 2D DOA estimation is performed. Monte Carlo simulations showed that the estimation method is ef- fective.

TOFS:一种新的宽带源DOA估计算法(英文)

介绍了一种新的宽带源DOA估计方法:TOFS。与TOPS(投影子空间正交性测试)方法类似,该方法通过同时测试频域各频段噪声子空间与阵列搜索流型之间的正交性来进行DOA估计。作为对比,根据非相关MUSIC方法,提出了一种新的适用于宽带的非相关MUSIC方法,称为I-MUSIC方法。与宽带相关方法不同,TOFS方法不需要任何初始值的预估。与宽带非相关方法也不相同,TOFS方法同时测试各频段噪声子空间与阵列搜索流型之间的正交性。仿真了TOFS与I-MUSIC、CSSM、TOPS的性能比较。仿真结果表明,CSSM方法在低信噪比时有较好的性能,TOFS方法在中等信噪比以上时,有较好的性能。同时,TOFS方法避免了TOPS方法中常常出现的伪峰。