Low-Complexity Reconstruction of Covariance Matrix in Hybrid Uniform Circular Array

Spatial covariance matrix(SCM) is essential in many multi-antenna systems such as massive multiple-input multiple-output(MIMO). For multi-antenna systems operating at millimeter-wave bands, hybrid analog-digital structure has been widely adopted to reduce the cost of radio frequency chains.In this situation, signals received at the antennas are unavailable to the digital receiver, and as a consequence, traditional sample average approach cannot be used for SCM reconstruction in hybrid multi-antenna systems. To address this issue, beam sweeping algorithm(BSA) which can reconstruct the SCM effectively for a hybrid uniform linear array, has been proposed in our previous works. However, direct extension of BSA to a hybrid uniform circular array(UCA)will result in a huge computational burden. To this end, a low-complexity approach is proposed in this paper. By exploiting the symmetry features of SCM for the UCA, the number of unknowns can be reduced significantly and thus the complexity of reconstruction can be saved accordingly. Furthermore, an insightful analysis is also presented in this paper, showing that the reduction of the number of unknowns can also improve the accuracy of the reconstructed SCM. Simulation results are also shown to demonstrate the proposed approach.

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.

Fractal Uniform Circular Arrays Based Multi-Orbital-Angular-Momentum-Mode Multiplexing Vortex Radio MIMO

A radio wave driven by Orbital angular momentum(OAM) is called a vortex radio and has a helical wavefront. The differential helical wavefronts of several vortex radios are closely related to their topological charges or mode numbers. In physics, two or more radio waves with different mode numbers are orthogonal to their azimuth angles. With the development of radio communication technologies, some researchers have been exploring the OAM-based multi-mode multiplexing(multi-OAM-mode multiplexing) technologies in order to enhance the channel spectrum efficiency(SE) of a radio communication system by using the orthogonal properties of vortex radios. After reviewing the reported researches of OAM-based radio communication, we find that some breakthroughs have been made in the combination of OAM and traditional Multi-Input-Multi-Output(MIMO). However, the existing technology is not sufficient to support OAM-based MIMO system to achieve maximum the channel SE. To maximize the spectrum efficiency of OAM-based MIMO system, we present a reused multi-OAM-mode multiplexing vortex radio(RMMVR) MIMO system, which is based on fractal uniform cir-cular arrays(UCAs). The scheme described in this study can effectively combine multiOAM-mode multiplexing with MIMO spatial multiplexing. First, we present the generation of RMMVR MIMO signals. Second, under line-of-sight(LOS) propagation conditions, we derive the channels of the RMMVR MIMO system. Third, we separate the RMMVR MIMO signals using an orthogonal separation method based on full azimuth sampling. Finally, we introduce the method for calculating the channel capacity of the RMMVR MIMO system. Theoretical analysis shows that the scheme proposed in this study is feasible. Moreover, the simulation results show that spatial and mode diversity are obtained by exploiting fractal UCAs. However, to enhance the channel SE of RMMVR MIMO system, an interference cancellation method needs to be introduced for zero-mode vortex radios, and some methods of multi-OAM-mode beams convergence and mode power optimization strategy should be introduced in the future.

基于UCA-FDA雷达距离补偿的DOA估计方法

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。

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.

Adaptive Uniform Circular Array Synthesis Using Cuckoo Search Algorithm

Naturally suited array geometry for 360° coverage is the uniform circular array (UCA). A comparison of two types of uniform circular array configurations is presented in this paper. Due to its symmetrical geometry UCA is always targeted which results in minimal change inside lobe levels and beam width when scanned by a phased array antenna. Particle Swarm Optimization and Cuckoo algorithm are used for the calculation of complex weights of the array elements. Comparisons are drawn in the context of adaptive beam forming capabilities. Obtained results suggest that planar uniform circular array (9:10) using Cuckoo algorithm, has better beam forming properties with also reduced side lobe levels when compared to other geometry.

一般情形下的UCA辐射方向图理论研究

产生涡旋波束的方法有多种,其中最常见的是均匀圆阵列(UCA),具有简单的结构和便捷的模式调控能力。然而,在高阶模态下,增加UCA的单元数会导致成本和空间占比增大,并且可能降低高阶模态的纯度。目前,UCA的设计多种多样,但对于选择合适单元数量的研究还比较缺乏。本文基于DFT,分析UCA的辐射方向图,并在偶数单元数的基础上增加奇数单元数,同时考虑了阵列半径、观测面与圆阵的距离以及观测圆的半径这些因素对纯度的影响。通过仿真研究设定了纯度阈值,从而确定最适合的单元数量。UCA实验结果表明,N=3时带内隔离度可达到35dB,而N=4保持在28-35dB,因此奇数单元有较稳定的隔离度。此外内环N=3,外环N=5的同心圆环阵列(UUCA)的隔离度均大于20dB。综上,在选择UCA单元数量时需要综合考虑纯度要求、成本、空间限制和系统性能等因素。

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.

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。

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.

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.

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 wideband 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.

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.

基于均匀圆阵的改进UCA-ESPRIT算法

波达方向(DOA)估计是阵列信号处理的研究热点和难点之一。基于阵列天线,利用空间谱估计理论进行DOA估计,提出一种改进算法——I-UCA-ESPRIT。首先根据均匀圆阵(UCA)的中心对称性,将输入信号进行重新排列;然后将重新排列的信号进行实值转换,并对相关矩阵进行特征值分解;最后引入SVD算法,以求解来波信号的方位角和俯仰角。仿真结果表明,该算法不仅适用于DOA估计的非相干信号和相干信号,且优于UCA-RB-MUSIC算法和UCA-ESPRIT算法。

复杂干扰场景下的稳健自适应波束形成

针对复杂电磁环境中最小方差无畸变响应及干扰加噪声协方差矩阵重构波束形成器输出信干噪比下降的问题,本文基于均匀圆阵(uniform circular array,UCA)提出了一种适用于该场景的稳健自适应波束形成算法。所提算法利用稀疏重构技术得到的谱函数构造和改进干扰抑制矩阵,使其在干扰方位产生宽零陷,提高了算法的稳定性。考虑到UCA存在副瓣电平高及空间非均匀采样问题,利用二阶约束优化准则抑制UCA副瓣,使得所提算法在抑制干扰的同时具有较低的波束副瓣。当UCA半径选择合适时,所提算法的性能与最优波束形成器接近,仿真验证了所提算法的有效性。

Generation of OAM Waves and Analysis of Mode Purity for 5G Sub-6 GHz Applications

This article presents the generation of Orbital AngularMomentum(OAM)vortex waves with mode 1 using Uniform Circular Array(UCA)antenna.Two different designs,namely,UCA-1(4-element array antenna)and UCA-2(8-element array antenna),were designed and fabricated using FR-4 substrate to generate OAM mode 1 at 3.5 GHz(5G mid-band).The proposed antenna arrays comprised rectangular microstrip patch elements with inset fed technique.The elements were excited by a carefully designed feeding phase shift network to provide similar output energy at output ports with desired phase shift value.The generated OAM waves were confirmed by measuring the null in the bore sight of their 2D radiation patterns,simulated phase distribution and intensity distribution.The measurement results agree well with the simulation results.Moreover,a detailed mode purity analysis of the generated OAM waves was carried out considering different factors.The investigation found that the greater the number of elements,the higher the purity of the generated OAM wave.Compared with other previous works,the proposed antenna design of this paper is very simple to design and fabricate.In addition,the proposed antennas are compact in design even at lower frequency band with very wide bandwidth to meet the requirements of 5G mid-band applications.

A comprehensive error calibration method based on dual uniform circular array

Based on the dual uniform circular array, a novel method is proposed to estimate the direction-of-arrival (DOA) and jointly calibrate gain-phase errors, position errors, and mutual coupling errors. In this paper, only one auxiliary source is required to generate three time-disjoint calibration sources with the help of the rotation platform. Subsequently, according to the principle that the signal subspace is orthogonal to the noise subspace, the cost function is constructed. The alternating iteration method is used to estimate the coefficients of the three kinds of errors. During the process, the proposed algorithm makes full use of the structural characteristics of the array when estimating mutual coupling errors, while the signal phase matrix is used to eliminate the phase influence caused by the delay in signal arrival at the antenna array when estimating gain-phase errors and position errors. Compared with the algorithm using multidimensional nonlinear search, the proposed algorithm has lower computational com-plexity. Moreover, our algorithm does not require additional auxiliary sensors. Simulation results demonstrate that the proposed algorithm is effective and can precisely and comprehensively calibrate the errors in a dual uniform circular array.

基于均匀圆阵的模式空间矩阵重构算法

该文提出了一种新的均匀圆阵解相干方法,这里称为模式空间矩阵重构算法(MODE-TOEP)。该算法对均匀圆形阵列(UCA)的输出信号进行模式激励,使其成为模式空间内的虚拟阵列(VULA);在此基础上重构一个Toeplitz矩阵,成功地估计出相干源的来波方向。MODE-TOEP算法不需要进行平滑计算,从而减少了计算量。计算机仿真实验表明MODE-TOEP算法比传统的模式空间平滑类算法(MODE-FSS,MODE-FBSS)有更好的估计性能。

一种新的DOA估计方法

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.