Dimension decomposition algorithm for multiple source localization using uniform circular array

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.

Fast BSC-based algorithm for near-field signal localization via uniform circular array

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.

Beam Pattern Design and Performance Analyses for Circular Array with Spherical Baffles

The influence of a rigid spherical baffle on the response of a uniform circular microphone array （UCA） is analyzed and two eigen-beam beamforming arrays are designed in the eigen-beam subspaee derived from the soundfield decomposition. Expressions of white noise gain （WNG） and directivity index （DI） are derived for the designed arrays. Performance analyses are carried out for the designed arrays and compared between those of the delay-and-sum beamforming array using UCA with and without a rigid sphere. Computer simulations demonstrate that the designed arrays have frequency-independent directivity with the cost of reduced robustness at low frequency band. The delay-and-sum beamforming array has constant WNG at all frequencies, while its directivity of which is reduced at low frequency band. The rigid sphere can improve the robustness for all the arrays.

Joint estimation of DOA, frequency, and polarization based on cumulants and UCA

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.

DOA ESTIMATION FOR WIDEBAND SOURCES BASED ON UCA

A new Direction Of Arrival （DOA） estimation algorithm for wideband sources based on Uniform Circular Array （UCA） is presented via analyzing widcband performance of the general ESPRIT. The algorithm effectively improves the wideband performance of ESPRIT based on the interpolation principium and UCA-ESPRIT. The simulated results by computer demonstrate its efficiency.

Low complexity DOA estimation for massive UCA with single snapshot

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.

循环平稳特性在UCA超分辨率测向中的应用

阵列天线在军用及民用方面具有广泛的应用前景,从超分辨率测向算法方面对均匀圆阵列天线(UCA)的测向技术进行了研究,介绍了UCA输出数据模型及其波束域处理的基本问题,将循环平稳特性与UCA相结合,提出了两种有效的UCA测向算法———波束域Cyclic MUSIC和Cyclic-Root-MUSIC算法;仿真分析表明,它们具有较好的抑制噪声和抗干扰性能,且具有较低的计算量,由于UCA在360°方位角内具有等性能波束形状、天线增益和互耦平衡,其结构具有圆对称性,因此适于车载或机载系统应用。

CRB for 2-D DOA Estimation in MIMO Radar with UCA

The Cramer-Rao bound(CRB)for two-dimensional(2-D)direction of arrival(DOA)estimation in multiple-input multiple-output(MIMO)radar with uniform circular array(UCA)is studied.Compared with the uniform linear array(ULA),UCA can obtain the similar performance with fewer antennas and can achieve DOA estimation in the range of 360°.This paper investigates the signal model of the MIMO radar with UCA and 2-D DOA estimation with the multiple signal classification(MUSIC)method.The CRB expressions are derived for DOA estimation and the relationship between the CRB and several parameters of the MIMO radar system is discussed.The simulation results show that more antennas and larger radius of the UCA leads to lower CRB and more accurate DOA estimation performance for the monostatic MIMO radar.Also the interference during the 2-D DOA estimation will be well restrained when the number of the transmitting antennas is different from that of the receiving antennas.

基于深度卷积网络的二维波达方向估计方法

为了提高信号波达方向估计技术的实时性和简便性,设计了一种适用于估计均匀圆阵多信号波达方向的深度卷积网络。由阵列观测数据得到的协方差矩阵被当作是包含实部和虚部两个通道的图像,将其当作是卷积神经网络的输入张量,便可以通过训练网络来提取包含在信号协方差矩阵中的波达方向细微特征,从而实现准确快速地同时对多个入射信号的方向进行估计的目的。仿真结果表明,设计的深度卷积网络能够很好地完成二维信号波达方向估计。相比于现有估计方法,卷积网络给出的结果更加精确,且算法相对稳定。因此,提出的深度卷积网络在多目标方位识别与跟踪领域具有潜在的工程应用价值。

均匀圆型声矢量阵的四元数二维波达方向估计

为提高声场空域中目标参数估计的精度,将四元数理论应用于均匀圆型声矢量阵列的二维空间角度估计中,建立了基于四元数模型的信号接收模型,推导了圆型声矢量阵的四元数导向矢量,给出了二维波达角估计的四元数域空间谱算法。考虑算法的软硬件可实现性,理论分析了算法的内存占用空间和计算量。此外,分析了圆阵半径对侧向性能的影响,为实际工作中圆阵的半径选取提供了一定的依据。仿真结果表明,基于四元数模型的MUSIC(Multiple Signal Classification)算法的分辨力较高,抗干扰能力较强,提高了信号参数估计的精度。

基于四阶累积量虚拟阵列扩展的DOA估计

针对Music-like方法能很好地扩展阵列孔径,但计算量较大的问题,提出了一种虚拟阵列扩展的新方法。该方法基于四阶累积量孔径扩展的性质,由实际阵元的坐标与方向矢量直接计算出虚拟阵元的坐标与方向矢量,利用两种阵元坐标之间的关系构造四阶协方差矩阵,运用MUSIC(Mu ltip le S ignal C lassification)算法对非高斯独立信号源进行DOA(D irection of Arrival)估计。该方法在任意阵列的情况下,对非高斯独立信号源进行一维与二维DOA估计,均能准确估计出多于实际阵元数目的方向角与仰角。实验表明,对一N元阵列,该方法最多能够扩展N2-N+1个虚拟阵元,能够估计出N2-N个非高斯独立信源,提高了阵列的空间分辨能力,有效抑制了高斯噪声的干扰,减少了高阶累积量协方差矩阵的计算量。

基于FRFT的均匀圆阵DOA估计

针对广泛应用于第三代移动通信系统中的均匀圆阵,将分数阶Fourier变换的时频特性和分数阶Fourier域波束形成技术相结合,给出一种多分量LFM信号的波达方向估计算法。与其他方法相比,该算法在一定程度上提高了精确度。仿真验证了在多径和多普勒频移存在的复杂信道中算法的有效性。

均匀圆阵的测向模糊研究

在高分辨阵列测向系统中,均匀圆阵(UCA)是一种广泛使用的阵列结构。利用均匀圆阵的阵列流形的微分几何作为分析工具,对实际中常用的几种均匀圆阵的测向模糊进行了大量的计算机仿真试验,定量地给出了这些阵列的测向模糊方向和相应的秩,揭示了均匀圆阵的测向模糊性能与其阵元数和孔径之间的关系,得出了一些有实际意义的结论。这对工程应用时均匀圆阵的选择和构造具有很强的参考价值和指导意义,可以避免系统设计的盲目性和随意性。

基于均匀圆阵的闭环式单基站测向算法研究

为了估算基于均匀圆阵列(UCA)的三维(3D)单基站测向(方位角、仰角和区间),提出了一种改进的适用于三维场景的闭环式算法。该算法是一种计算过程较简单的通用算法,无需使用均匀圆阵列的中心对称性,没有任何传感器数量的限制,只需要一个单独的最小平方程序用于估算基站的位置,并可以估算所有的三维测向参数。实验结果表明,相比多种类似算法,所提算法的性能可与三维MUSIC算法的性能相媲美,且计算复杂度更低,实现速度更快。

阵列频率特性改进研究

传统的均匀线阵(ULA)和均匀圆阵(UCA)的实时性、宽频带特性以及旁瓣级等难以满足系统需求,通过对传统的ULA和UCA的频率特性与其阵形的关系进行了分析,提出了采用有向阵元改进UCA的综合性能。利用半圆阵的阵形结构提高了采用有向阵元的UCA的综合性能。仿真分析表明,该结构获得了更好的宽频带特性,并在具备实时性的同时有较佳的综合性能,满足了快速宽带波束形成系统的需求。

带支撑物圆阵波达方向估计实验研究

为了验证带支撑物圆阵波达方向估计算法的有效性,在介绍算法原理的基础上,利用设计的镶嵌在刚性球上的12元均匀圆阵,分别在消声室和外场进行了声源定向实验研究。定向结果显示消声室内平均估计误差不大于2°,均方根误差不大于2.2°,外场平均估计误差和均方根误差均不大于3°。实验表明基于带支撑物圆阵所推导的波达方向估计算法是有效的,能正确估计出声源的波达方向,且具有较高的精度,为利用带支撑物圆阵进行波达方向估计的工程应用奠定了基础。

基于均匀圆阵的矢量重构解相干算法

为解决基于均匀线阵矢量重构法不能直接用于均匀圆阵这一问题,提出一种模式空间矢量重构算法.提取模式变换后最大广义特征值对应的特征矢量,并对修正的信号特征矢量采用前后矢量重构方式构造数据矩阵实现解相干.在变换前提取最大特征值对应的信号特征矢量,充分去除噪声,且无需变换后广义特征分解计算,算法复杂度显著降低.理论分析和仿真结果验证了该算法的有效性.

空域滤波增益可调节的定向性均匀圆形阵列波达角估计

针对定向性均匀圆形阵列因单元天线的位置、主瓣指向及方向函数等因素造成信号来波落入天线旁瓣或零陷内,从而导致部分单元天线接收的信号信噪比低、信息失效的问题,首先研究了定向性均匀圆形阵列天线的方向性增益及功率波束角,随后进一步分析了连续激励在定向性均匀圆阵远场的幅频响应,最后提出了一种与波数无关的基于半功率波束宽度、增益可调节的空域滤波波达角估计模型。仿真实验结果表明,与其他模型相比该模型在低信噪比下具有估计精度高、参与天线少的优点。与传统的定向性波达角估计模型相比,当信噪比为-20 dB时,该模型的临近空间角度分辨力明显优于前者,并且随着可调节滤波增益至10 dB,其临近角度的峰值隔离度可达65 dB。

采用伪噪声重采样的海事卫星上行信号的检测与定向

在均匀圆形阵列(uniform circular array,UCA)上采用伪噪声重采样(pseudo-noise resampling,PR),利用ROOT-MUSIC算法对海事卫星上行信号进行测向.为了提高低信噪比(signal noise ratio,SNR)下的预测精度,在传统伪噪声重采样的基础上利用统计均值与标准差提出了新的先验条件,并比较了不同的统计数据形成的先验条件对系统性能的影响.仿真结果表明,低信噪比下本方法比常规圆形阵列上的ROOT-MUSIC算法在检测性能上有较大提高.

基于两垂直方向虚拟平移的波达方向判定算法

提出了一种针对均匀圆阵接收信号波达方向(direction of arrival,DOA)判定的算法,该算法相对于其他算法,更能充分利用信号中的有用信息,达到提高算法判定精度的目的.算法将接收信号数学模型在Z轴和X轴方向分别进行虚拟平移,通过模式激励,构造出两个包含接收信号DOA信息的满秩Toeplitz矩阵,达到相干信号解相干的目的.先后根据Z轴、X轴方向旋转因子特性的不同,先得出信号俯仰角的估计值,再得出方位角的估计值,完成二维波达方向的判定.仿真结果验证了该算法对于相干信号DOA判定的正确性,而且对于强相干和低信噪比的入射信号DOA也能有效区分和判定.