非均匀噪声条件下的互质阵列欠定DOA估计方法

针对基于互质阵列的欠定DOA估计方法在非均匀噪声条件下性能下降的问题,该文提出一种基于协方差矩阵重构和矩阵填充的鲁棒DOA估计方法。首先,将接收数据协方差矩阵分解,得到包含非均匀噪声项的对角阵;然后,选取对角线元素中的最小值,替换其余对角线元素,进而得到重构后的数据协方差矩阵;最后,对重构后的协方差矩阵进行扩展和矩阵填充,结合子空间方法进行DOA估计。理论分析和仿真结果表明,相对于现有方法,该文方法有效地抑制了非均匀噪声的影响,有更好的DOA估计性能。     

空间非平稳噪声下的宽带DOA估计算法

投影子空间正交性测试(TOPS)法是利用子空间的正交性实现宽带信号DOA估计,而在空间非平稳噪声环境下子空间的正交性条件不再满足,尤其是在低信噪比或低快拍条件下子空间估计将出现较大误差,TOPS算法性能将急剧下降。针对该问题,提出了一种空间非平稳噪声下宽带DOA估计算法。该算法首先通过构造特殊对角矩阵将噪声从数据协方差矩阵中剔除,从而克服非平稳噪声对DOA估计的影响;然后利用平方TOPS法实现宽带信号DOA估计,消除了传统TOPS算法中的伪峰。该算法适用于空间非平稳噪声背景及低信噪比环境,提高了对角度相近目标的分辨性能;仿真实验表明了该算法的有效性。     

Direction of Arrival Estimation using EM-ESPRIT with Nonuniform Arrays

This paper deals with the problem of the Direction Of Arrival (DOA) estimation with nonuniform linear arrays. The proposed method is based on the Expectation Maximization method where ESPRIT is used in the maximization step. The key idea is to iteratively interpolate the data to a virtual uniform linear array in order to apply ESPRIT to estimate the DOA. The iterative approach allows one to improve the interpolation using the previously estimated DOA. One of this method’s novelties lies in its capacity of dealing with any nonuniform array geometry. This technique manifests significant performance and computational advantages over previous algorithms such as Spectral MUSIC, EM-IQML and the method based on manifold separation technique. EM-ESPRIT is shown to be more robust to additive noise. Furthermore, EM-ESPRIT fully exploits the advantages of using a nonuniform array over a uniform array: simulations show that for the same aperture and with a smaller number of sensors, the nonuniform array presents almost identical performance as the equivalent uniform array.     

浅海非高斯噪声下基于变分贝叶斯推断的波达角估计

传统基于高斯统计特性的波达角(DOA)估计方法在高斯背景噪声中可以获得较好的估计性能,然而受脉冲噪声影响的浅海环境噪声不再服从高斯分布,若直接利用传统波达角估计方法会引入较大误差。为提升非高斯噪声环境下的波达角估计性能,该文提出一种浅海非高斯噪声下的基于变分贝叶斯推断的波达角估计方法。首先利用信号与脉冲噪声的稀疏性构建多测量向量稀疏信号恢复(SSR)模型;其次,考虑信号的共稀疏特性与脉冲噪声的独立稀疏性,构建层次化贝叶斯估计框架;然后利用变分贝叶斯推断估计信号与噪声的后验概率估计。稀疏信号模型中考虑离网格误差,利用根稀疏贝叶斯估计实现离网格误差修正,解决离网格误差引起的基失配问题;最后通过迭代更新获得较为精确的波达角估计,同时消除脉冲噪声的影响。仿真结果表明：所提方法在非高斯噪声环境下具有较好的波达角估计性能,同时对于脉冲噪声具有较强的抗干扰特性。     

互耦效应对DOA估计的影响

在均匀线性阵列模型下,结合常规波束形成算法、Capon最小方差无失真响应(MVDR)波束形成算法、MUSIC算法、ESPRIT算法和Root-MUSIC算法等几种主要到达角(DOA)估计算法的原理,分析了互耦效应影响这些算法的作用机理,并利用MATLAB进行了数值仿真.理论分析和仿真结果表明,互耦效应带来的误差增大了DOA估计算法的估计误差,降低了估计成功概率,严重影响了算法的性能.     

测向天线阵互耦效应分析

天线阵元间的互耦效应将导致天线阵列的电参数和方向性的改变,从而影响测向系统的性能。针对天线阵列各单元之间的互耦现象,提出了利用矩量法精确分析天线阵列各单元上的电流分布,进一步通过互阻抗网络计算法求出测向天线单元的实际激励电压的幅度和相位,进而得到天线的辐射和接收特性。对实际的均匀直线阵列超分辨测向系统中的互耦效应进行了分析,给出了仿真结果,验证了互耦效应对测向性能的影响。     

一种阵列互耦矩阵与波达方向的级联估计方法

当阵列天线存在互耦效应时,传统多重信号分类(MUltiple SIgnal Classification, MUSIC)算法的测向性能急剧下降。为了有效估计阵列互耦矩阵(MCM)与入射信号的波达方向(Direction Of Arrival, DOA),该文提出一种阵列互耦矩阵与波达方向的级联估计方法。利用互耦矩阵的结构特点,变换阵列流形,实现对互耦矩阵与DOA的解耦合。求解线性约束下的二次优化问题,利用谱峰搜索,得到阵列互耦矩阵和入射信号DOA,完成互耦误差自校正。通过计算机仿真验证了该文方法估计性能的有效性和优越性。     

脉冲噪声下基于广义类相关熵的DOA估计新方法

针对基于分数低阶统计量波达方向估计方法的局限性,受相关熵概念的启发,本文提出广义类相关熵（GCAS）的概念和相应的波达方向估计新方法。计算机仿真结果表明,在Alpha稳定分布噪声环境下,本文提出的基于GCAS的MUSIC波达方向估计方法比基于分数低阶统计量的MUSIC方法在抗噪声特性和多源信号分辨特性等方面具有更好的性能。      

基于宽带均匀同心球阵列的低复杂度二维波达方向估计算法

该文提出一种基于宽带均匀同心球阵列(UCSA)的2维波达方向(2D-DOA)低复杂度估计算法。该方法将宽带UCSA输出信号转换为相位模式,并对其进行频率补偿,实现近似频率不变(FI)特性,从而降低宽带信号处理的计算复杂度。为了进一步降低2D-DOA估计的计算复杂度,该文提出基于FI-UCSA的降维多重信号分类(MUSIC)算法。该方法将相位模式导向向量分解为方位角和仰角相关的两个矩阵,从而把2维搜索问题简化为1维(1D)搜索,实现降维优化并降低计算复杂度。仿真结果表明,该算法计算复杂度相较于2维MUSIC算法得到了极大的降低,并且在估计精度和分辨率上均稍有改善。     

Beam Forming in Smart Antenna with Precise Direction of Arrival Estimation Using Improved MUSIC

Smart antenna is now commonly used in communication systems due to its high advantages. In order to improve the performance of smart antenna operation, efficient design of beam forming pattern is required based on the subjected antenna parameters. In the previous works, beam forming techniques were proposed using hybridization of soft computing techniques, however the precision has not been considered in terms of direction of arrival (DOA). This paper includes DOA while deriving the beam forming pattern of smart antenna. To estimate precise DOA, the MUSIC algorithm is improved by introducing a tuned correlation matrix after solving the objective model for the matrix. Thus estimated DOA pattern is more precise as the unwanted side lobes are suppressed when compared to the conventional DOA pattern. Based on the estimated DOA pattern, the antenna beam forming pattern is derived as per the required direction of angles. The experimental results show the performance of the proposed beam forming technique over the previous techniques.     

增益相位误差下基于部分校准嵌套阵列的DOA估计

现有的波达方向（Direction of Arrival,DOA）估计方法大多依赖于阵列导向矩阵的精确无偏条件,而实际工程中由于时钟偏移、阵元位置偏差的存在导致该条件往往难以满足.为匹配阵列实际接收条件,本文基于部分校准嵌套阵列,提出了一种增益相位误差下的DOA估计新方法.该方法首先利用连乘子函数和简单的代数运算完成初始增益相位误差估计,然后通过协方差矩阵向量化和稀疏表示理论构建具有连续自由度的稀疏表示向量模型,最后考虑有效样本的影响,在初始增益相位误差估计的基础上应用稀疏总体最小均方（Sparse total least squares,STLS）算法完成波达方向估计.本文所提方法不仅对阵列增益相位误差不敏感,而且可依靠嵌套阵列高自由度特性和STLS算法的抗扰动特性获得改进的分辨率和估计精度,计算机仿真结果验证了所提算法的有效性.     

脉冲噪声下基于中值离差相关熵的DOA估计方法

作为阵列信号处理的一个基本问题,波达方向估计在现代通信领域有着广泛的应用。常规估计方法通常基于高斯噪声假设。 而当阵列接收数据包含 Alpha 稳定分布脉冲噪声时算法将完全失效。针对 Alpha 稳定分布噪声下的波达方向估计问题,本文定义了一种改进的相关熵算子——中值离差相关熵,并从理论上证明了它的有界性。 以此为基础结合 MUSIC 算法提出了一种波达方向估计新方法。该方法不需要噪声先验知识,且在脉冲噪声环境中具有鲁棒性。仿真实验表明, 即使在短快拍、强脉冲噪声的恶劣环境下,本文方法依然具有良好的性能。      

均匀线阵互耦矩阵非Toeplitz条件下的DOA估计

理想条件下,均匀线阵的互耦矩阵可用一带状、对称Toeplitz矩阵进行建模。然而实测数据表明,均匀线阵的互耦矩阵具有对称性,但不具有Toeplitz性,此时仍按理想情况建模,会导致DOA估计不准甚至完全失效。基于RBF神经网络,提出了互耦矩阵非Toeplitz条件下的DOA估计方法。算法利用了信号协方差矩阵的对称性和对角线元素不含信号DOA信息的特点,取协方差矩阵的上三角的元素作为网络输入,不仅减少了网络的输入数,同时还提高了与阵列法线夹角60°外的DOA估计精度。实验仿真结果验证了算法的有效性。     

Two Dimensional Direction of Arrival Estimation Algorithm for Coherent Signals Using Three Parallel Uniform Linear Arrays

Journal of Communications Technology and Electronics - The problem of two dimensional direction of arrival estimation of coherent signals using three parallel uniform linear arrays is investigated....     

On the Direction of Arrival (DoA) Estimation for a Switched-Beam Antenna System Using Neural Networks

A generic direction of arrival (DoA) estimation methodology is presented that is based on neural networks (NNs) and designed for a switched-beam system (SBS). The method incorporates the benefits of NNs and SBSs to achieve DoA estimation in a less complex and expensive way compared to the corresponding widely known super resolution algorithms. The proposed technique is step-by-step developed and thoroughly studied and explained, especially in terms of the beam pattern structure and the neuro-computational procedures. Emphasis is given on the direct sequence code division multiple access (DS-CDMA) applications, and particularly the Universal Mobile Telecommunication System (UMTS). Extensive simulations are realized for each step of the method, demonstrating its performance. It is shown that a properly trained NN can accurately find the signal of interest (SoI) angle of arrival at the presence of a varying number of mobile users and a varying SoI to interference ratio. The proposed NN-SBS DoA estimation method can be applied to current cellular communications base stations, promoting the wider use of smart antenna beamforming.      

Mutual Coupling in the Signal-to-Noise Ratio Optimization of Antenna Arrays

In terms of network parameters defined at the input terminals, expressions applicable to any array configuration are derived for the S/N ratio. The formulation is made in such a way that it becomes possible to account for coupling effects that arise from the geometry of the array and the current distributions on the elements of the array. Since the S/N ratio consists of the ratio of two Hermitians forms, known techniques are used for its optimization. Comparisons with simplified theories are given that demonstrate clearly the importance of mutual coupling in many cases. Numerical results for a 4-element circular array are included for two idealized noise temperature distributions. Applications of this theory to EMC fields are also mentioned.     

强干扰环境下水声时延估计技术研究

水声定位系统是现代深海作业必备的高精度水下定位装备,精确的时延估计是实现高精度水声定位的基础,但由于信号远距离传输以及强干扰的影响,水声定位系统时延估计精度较低.针对此问题该文提出一种基于子空间理论的宽带强干扰抑制方法,首先通过贝叶斯信息量准则估计子空间维度,然后推导了不同信号假设下的概率密度函数,求解未知参数的最大似然估计,构造广义似然比并通过最优匹配广义似然比检测法估计与期望信号最匹配的子空间,然后以此构造空间投影算子对接收数据进行线性投影,最终抑制干扰和噪声,提高时延估计精度.仿真结果表明该方法能够有效抑制干扰和噪声的影响,提高定位系统时延估计精度.     

强干扰环境下水声时延估计技术研究

水声定位系统是现代深海作业必备的高精度水下定位装备,精确的时延估计是实现高精度水声定位的基础,但由于信号远距离传输以及强干扰的影响,水声定位系统时延估计精度较低。针对此问题该文提出一种基于子空间理论的宽带强干扰抑制方法,首先通过贝叶斯信息量准则估计子空间维度,然后推导了不同信号假设下的概率密度函数,求解未知参数的最大似然估计,构造广义似然比并通过最优匹配广义似然比检测法估计与期望信号最匹配的子空间,然后以此构造空间投影算子对接收数据进行线性投影,最终抑制干扰和噪声,提高时延估计精度。仿真结果表明该方法能够有效抑制干扰和噪声的影响,提高定位系统时延估计精度。     

Direction of Arrival Estimation of Multiple UWB Signals

This paper deals with the problem of estimation of direction of arrivals (DOA) of a multiple ultra-wideband (UWB) pulse postion modulation signals incident on a smart antenna in the presence of white Gaussian noise. We transform the received signal into frequency domain in order to split the array output into multiple frequency channels. Corresponding frequency channels data of the array is arranged into a model similar to narrowband DOA estimation. Iterative quadratic maximum likelihood algorithm is applied to yield DOA estimates. These separate estimates at different frequencies are combined into a single estimate of DOA for each source in an appropriate manner. The performance of the proposed method is studied via extensive computer simulations. It is seen that the technique can successfully resolve the DOA of the closely-spaced UWB signals.     

估计信号到达角的一种快速算法

通过充分考虑相干信号源以及其回波的各个特性,本文首先提出了适合其特性的信号模型,并以此为基础对信号的某些特性进行深入分析,进而提出了基于FFT的对阵列信号到达角进行估计的快速算法.模拟仿真结果表明,在多个相干信源的前提下.本文提出的对信号到达角进行快速估计的算法是切实可行的,尤其适合在低信噪比和实时场合下使用.