Direction-of-arrival and polarization estimation with uniform circular arrays in the presence of mutual coupling

A modified Root-MUSIC algorithm is proposed to estimate the directions-of-arrival (DOAs) and the polarization of plane waves, which impinge at a fixed elevation angle, using a diversely polarized uniform circular array (UCA). Special attention is devoted to the presence of mutual coupling effects in antenna arrays. By describing the electromagnetic characteristics on the basis of a phase-mode expansion for the open-circuit voltages and the mutual coupling matrix, the modified Root-multiple signal classification (MUSIC) algorithm takes mutual coupling effects into account by a limited number of phase modes. Finally, the efficiency of the new algorithm is verified based on synthetic antenna data.     

阵元间互耦条件下一维波达方向估计方法

该文在与波达方向(DOA)有关的阵元间互耦条件下,提出了一种新的自校准DOA估计方法,并给出了参数可辨识性的一个必要条件。该方法利用一维DOA搜索,无需估计互耦参数,避免了多维参数搜索和迭代过程。仿真实验结果表明,阵元间互耦参数和DOA估计存在模糊性。在其间存在互耦的阵元个数已知的条件下,可以得到正确的DOA估计结果。     

超宽带系统中基于稀疏恢复的TOA和DOA联合估计方法

针对稀疏表示框架下进行超宽带系统中到达时间(Time of Arrival, TOA)和波达方向(Direction of Arrival, DOA)联合估计的问题,提出了一种基于稀疏恢复的TOA和DOA联合估计方法。采用l范数作为稀疏约束条件,并利用联合正交匹配追踪算法获取TOA估计值,解决了TOA配对问题,最后根据两副天线的时延差与DOA之间的关系获得信号的DOA估计。所提算法考虑了离网格信号参数估计问题,并通过联合稀疏恢复进行补偿。仿真结果表明,所提算法的参数估计性能优于传统的压缩感知算法、传播算子算法、矩阵束算法以及借助旋转不变性的信号参数估计技术(Estimating Signal Parameters via Rotational Invariance Techniques, ESPRIT)算法,同时计算复杂度更低。     

基于稀疏贝叶斯学习的高效DOA估计方法

针对采用l1范数优化的稀疏表示DOA估计算法正则化参数选取困难、计算复杂度高的问题,该文提出一种基于稀疏贝叶斯学习的高效算法。该算法首先利用均匀线阵的结构特性,将DOA估计联合稀疏模型的构建与求解转换到实数域进行。其次,通过优化稀疏贝叶斯学习的基消除机制,使该算法具有更快的收敛速度。仿真结果表明,与l1范数优化类算法相比,该文方法具有更高的空间分辨率和估计精度且计算复杂度低。     

DOA error estimation in 3D cylindrical dipole array geometries including the mutual coupling effect

The direction of arrival (DOA) error in dipole 3D arrays is estimated through Monte-Carlo simulations using the standard MUSIC algorithm. Novel 3D geometries are implemented which demonstrate better precision given the same lateral area. The mutual coupling effect is included by changing the search vector in the MUSIC DOA algorithm for the novel 3D geometries. A simple straight forward method is used which does not need complex electromagnetic computations. Simulations show that the proposed method can successfully account for the mutual coupling effects in two dimensional direction finding (both azimuth and elevation angle) with novel 3D array geometries. Reduced DOA estimation error is observed in the novel geometries which can be used as a method of mitigation for the mutual coupling effect.     

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.     

Histopathological image classification through discriminative feature learning and mutual information-based multi-channel joint sparse representation

Histopathological image classification is a very challenging task because of the biological heterogeneities and rich geometrical structures. In this paper, we propose a novel histopathological image classification framework, which includes the discriminative feature learning and the mutual information-based multi-channel joint sparse representation. We first propose a stack-based discriminative prediction sparse decomposition (SDPSD) model by incorporating the class labels information to predict deep discriminant features automatically. Subsequently, a mutual information-based multi-channel joint sparse model (MIMCJSM) is presented to jointly encode the common component and particular components of the discriminative features. Especially, the main advantage of the MIMCJSM is the construction of a joint dictionary using a mutual information criterion, which contains a common sub-dictionary and three particular sub-dictionaries. Based on the joint dictionary, the MIMCJSM captures the relationship of multi-channel features, which can improve discriminative ability of joint sparse representation coefficients. Finally, the joint sparse representation coefficients of different levels can be aggregated using the spatial pyramid matching (SPM) model, and the linear support vector machine (SVM) is used as the classifier. Experimental results on ADL and BreaKHis datasets demonstrate that our proposed framework consistently performs better than popular existing classification frameworks. Additionally, it can show promising strong-robustness performance for histopathological image classification.     

基于加权l1最小化的低复杂度波达方向估计算法

基于阵列协方差矩阵的稀疏表征和阵列响应矩阵的Khatri-Rao积,提出了一种低运算复杂度的波达方向估计算法.所提算法在减少未知数个数的同时,通过线性变换降低约束方程的维数,可有效减少优化问题的计算复杂度.为充分利用阵列协方差矩阵中蕴涵的信息,使用Capon谱的倒数作为权值构建出了加权l1最小化问题,这使得所提算法在降低运算量的同时能够获得较好的估计性能.仿真实验验证了所提算法的有效性.     

An efficient DOA estimation method in multipath environment

An efficient direction of arrival (DOA) estimation method is proposed with uniform linear array (ULA) in multipath environment. By applying a transformation, we can convert a constructed complex matrix to a real one, and then utilize the real matrix combined with our proposed criterion to estimate the DOAs of uncorrelated signals. Afterwards, the contributions of uncorrelated signals are eliminated, and then several new matrices without the information of uncorrelated signals are constructed to resolve the remaining coherent signals. The proposed estimation method overcomes the shortcomings of the existing methods and has satisfactory performance. Simulation results confirm the theoretical analysis and show the effectiveness of the proposed method.     

互耦条件下均匀线阵DOA盲估计

阵元间存在互耦时,经典的波达角(DOA)估计算法性能急剧下降甚至失效。针对互耦条件下均匀线阵DOA估计问题,该文提出一种基于盲源分离的DOA盲估计算法。首先,利用源信号的统计特性,由盲源分离方法估计广义阵列流形矩阵;然后,利用均匀线阵互耦矩阵带状、Toeplitz矩阵的特点,将DOA估计问题转化为多个可分离非线性最小二乘问题,由多个1维频域搜索得到DOA的估计。该算法无需高维搜索或多维迭代,对互耦自由度要求更低,互耦自由度未知时仍旧适用,稳健度高。数值仿真验证了该文算法的有效性。     

Directions of arrival estimation with planar antenna arrays in the presence of mutual coupling

Directions of arrival (DoAs) estimation of multiple sources using an antenna array is a challenging topic in wireless communication. The DoAs estimation accuracy depends not only on the selected technique and algorithm, but also on the geometrical configuration of the antenna array used during the estimation. In this article the robustness of common planar antenna arrays against unaccounted mutual coupling is examined and their DoAs estimation capabilities are compared and analysed through computer simulations using the well-known MUltiple SIgnal Classification (MUSIC) algorithm. Our analysis is based on an electromagnetic concept to calculate an approximation of the impedance matrices that define the mutual coupling matrix (MCM). Furthermore, a CRB analysis is presented and used as an asymptotic performance benchmark of the studied antenna arrays. The impact of the studied antenna arrays geometry on the MCM structure is also investigated. Simulation results show that the UCCA has more robustness against unaccounted mutual coupling and performs better results than both UCA and URA geometries. The performed simulations confirm also that, although the UCCA achieves better performance under complicated scenarios, the URA shows better asymptotic (CRB) behaviour which promises more accuracy on DoAs estimation.     

多径条件下均匀线阵DOA估计及互耦误差自校正

针对多径信道环境下存在互耦误差的均匀线阵,提出了一种联合波达方向估计及互耦 误差自校正算法。在不改变阵列互耦误差的条件下,首先利用虚拟阵列平移预处理方法,将 相干信源协方差矩阵恢复到满秩。进而利用互耦误差的对称Toeplitz特性,基于子空间原理 构造一代阶函数,采用秩损的方法得到互耦误差条件下的DOA估计及阵列互耦误差。数值仿 真结果表明,该算法具有良好的DOA估计性能与互耦误差自校正性能。     

L-shaped array-based elevation and azimuth direction finding in the presence of mutual coupling

For two-dimensional (2-D) directions-of-arrival (DOA) estimation problem, both the mutual coupling and the failure in pairing can cause severe performance degradation. In this paper, a new elevation and azimuth direction finding algorithm is developed to overcome the above-mentioned two difficulties in the L-shaped array configuration. The key points of this paper are: (i) constructing several correlation matrices to blindly compensate the effect of unknown mutual coupling using the outputs of properly chosen sensors and (ii) deriving a rank-reduction propagator method to estimate elevation and azimuth angles so as to avoid pairing parameters. Simulation results are presented to validate the performance of the proposed method.     

基于压缩感知DOA估计的稀疏阵列设计

根据格拉姆(Gram)矩阵优化测量矩阵的方法,给出了一种基于压缩感知波达方向(DOA)估计的均匀线阵的稀疏阵列设计方法.该方法不需要对阵列的输出数据进行压缩采样,直接利用稀疏阵列的输出数据,然后利用稀疏恢复算法求解DOA估计信息.实验仿真证明,相比于原均匀线阵,所提方法在阵元数目较少且信噪比较低的情况下具有更好的DOA估计性能.     

Compensation for the mutual coupling effect for the ESPRIT algorithm in single snapshot array processing

An effective method is introduced to compensate the effects of mutual coupling for the Estimation of Signal Parameter via Rotational Invariance Techniques (ESPRIT) direction finding algorithm in application of signal snapshot array processing.Changing the covariance matrix into a Teoplitz matrix can achieve high resolution in the Direction Of Arrive (DOA) estimation.How the mutual coupling affects the array antennas has been discussed and a new definition of mutual im- pedance has been used to characterize the mutual coupling effects between the array elements.Based on the new mutual impedance matrix,a practical method is presented to eliminate the effects of mutual coupling for ESPRIT in the single snapshot data processing.The simulation results show that, this new method not only properly reduces the effects of mutual coupling,but also maintains its steady performance even for weak signals.     

基于稀疏重构的跳频信号时频分析方法

针对现有时频分析方法存在噪声抑制能力弱、时频聚集性不强的缺点,提出了一种基于稀疏重构的跳频信号时频分析方法来获取清晰的、高聚集度的时频图。首先根据惩罚函数的思想建立了跳频信号无约束的稀疏重构模型;然后理论分析了罚函数因子的取值标准;最后用近似l0范数算法求解得出跳频信号的时频图。仿真结果表明该算法能够有效地获取跳频信号的时频图。     

基于高阶累积量虚拟阵列扩展的DOA估计

该文提出了一种基于高阶累积量虚拟阵列扩展的DOA估计新方法。该方法基于高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,利用两种阵元的坐标之间的关系构造四阶或六阶协方差矩阵,运用MUSIC方法对非高斯独立信号源进行DOA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,均能准确地估计出多于实际阵元数目的方向角与仰角。实验表明,该方法简单、有效地扩展了阵列孔径,提高了阵列的空间分辨能力,有效地抑制了高斯噪声的干扰,降低了高阶累积量协方差矩阵的计算量。     

互耦条件下米波雷达角度估计的自校正算法

针对互耦条件下米波雷达目标低角估计问题,提出了一种波达方向估计的自校正算法。分析了米波雷达在互耦条件下目标回波存在多径时的信号形式;利用均匀线阵互耦矩阵的特点对接收数据协方差矩阵的信号参数形式进行变换;在未知互耦校正信息的情况下,基于子空间原理得到目标波达方向的角度搜索函数,还推导出表面反射系数和阵列互耦矩阵的计算表达式。与同类校正算法相比,该算法在存在多径相干信号和未知互耦矩阵的情况下,不损失阵列孔径,不需要辅助阵元和校准源,且不需要迭代运算。仿真结果验证了该算法的有效性。     

A novel compact his-EBG structure and its application in reduction of printed antenna mutual coupling

Anovel compact E shape High Impedance Surface (HIS) Electromagnetic Band-Gap (EBG) comprising Amended Minkowski Fractal Boundary (AMFB), Added Metal Strips (AMS), and metal plated via printed on a Rogers TMM 10i (ɛ _r =9.8, t=2.0 mm) substrate is presented. The first order AMFB and ABS are introduced for equivalent capacitance enhancement and miniaturization with effective space-filling characteristics. The dimension of lattice size is only 0.058λ ₀. The proposed structure exhibits a most compact characteristic about 35% size reduction as compared with conventional mushroom-like HIS-EBG, and better surface-wave decoupling of around 9 dB at the operating frequency band. Details of design parameters which affect the whole performance of certain band-gap are intensively investigated. A constructed prototype is potential candidate for antenna system performance enhancement.