多子阵互耦条件下的一维波达方向估计及互耦自校正

该文研究多子阵(multiple subarrays)阵元互耦条件下的波达方向(DOA)估计,假设阵列由多个位置已知的均匀线阵(ULA)组成,但线阵阵元间存在互耦效应。利用均匀线阵互耦矩阵的带状、对称Toeplitz性及多子阵互耦矩阵的块状对角特性,提出了一种解耦合波达方向估计及互耦自校正算法。该算法在未知阵元互耦参数的情况下,可准确估计出信源的波达方向。另外,算法在精确估计波达方向的同时,还可准确估计出阵元间的互耦系数,实现多子阵的互耦自校正。算法的波达方向估计只需一维谱峰搜索,避免了通常多参数联合估计的多维非线性搜索及迭代运算,可明显减小算法运算量。文中讨论了算法参数可辨识性的必要条件,并分析计算了多参数联合估计的克拉美-罗界(CRB)。理论分析及蒙特卡罗仿真结果表明,该算法具有计算量小、DOA估计分辨力高、互耦校正效果好等优点。     

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。     

基于L型阵列的方位估计及互耦自校正算法研究

 针对L型阵,提出了一种互耦自校正算法（SAL: self-calibration algorithm for L-shaped array）。该算法利用L型阵列特殊的互耦特性,实现了对信源信息（DOA）和阵列互耦系数的解耦合,从而无需任何校正源就可以实现两类参数的估计。与基于循环迭代最小化技术的传统自校正算法相比,该算法先通过搜索谱峰估计信源信息（DOA）,再估计互耦系数,从而避免了多维搜索带来的庞大运算量和迭代中的全局收敛性问题。仿真结果表明本文提出的自校正算法具有精度高、计算量小的特点。     

2-D DOA Estimation in the Presence of Mutual Coupling

We present a 2-D direction of arrival (DOA) estimation algorithm in the presence of unknown mutual coupling for the uniform rectangular array (URA) based on the multiple signal classification (MUSIC) algorithm. By setting the sensors on the boundary of the URA as auxiliary sensors, it can accurately estimate the DOAs without any calibration sources or iterative operations. We prove that the effect of mutual coupling can be eliminated by the inherent mechanism of the proposed method. Twice search technique is used to reduce the computation of the 2-D spectrum search. Moreover, we provide a method to estimate the mutual coupling coefficients after getting the DOA estimates. Simulation results confirm the effectiveness of the proposed algorithm.     

阵列互耦条件下相干信源DOA估计算法研究

针对阵列互耦条件下相干信源到达方向（DOA）估计的问题,利用均匀线阵互耦矩阵的带状循环特性及对称Toeplitz性,提出了一种基于改进的空间平滑算法的信源DOA估计算法。该算法无需阵元的互耦参数信息,只需一维谱峰搜索,避免了通常多参数联合估计的多维非线性搜索及迭代运算;由于采用改进的空间平滑算法,所以该算法具有很好的统计估计性能。计算机仿真结果验证了该算法的正确性和有效性。     

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。     

多径环境下阵列波达方向估计及互耦校正

在阵列信号处理的研究中,多径环境会降低接收机的定位精度,传统的多重信号分类算法的性能会大大降低,空间平滑算法能有效地进行解相干。当阵列天线存在互耦效应时,传统的空间平滑算法的测向性能会大大下降。针对多径环境下的均匀线阵,利用互耦矩阵的复对称带状的结构特点,结合空间平滑算法,提出了一种可以进行互耦校正的波达方向估计算法。该算法通过求解线性约束下的二次规划问题,利用谱峰搜索得到入射信号的DOA。数值仿真结果验证了该算法的有效性。     

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。     

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.     

均匀平面阵下的二维DOA估计与互耦自校正

针对存在互耦效应时均匀平面阵的测向鲁棒性问题,提出了一种基于秩损准则的互耦自校正算法。根据对互耦效应的先验知识,提出的算法只需将受互耦扰动的阵列响应在变换域中重新排列,便可在后续处理中屏蔽掉互耦效应的不利影响,同时也避免了现有工作中存在的阵列孔径损失问题。借助秩损估计原理,在变换域中设计了一种巧妙的计算步骤,使得方位估计的降维操作得以实现;并且,后续还可通过特征分解法得到更精确的互耦系数估计,以进行阵列误差自校正。与现有的研究工作相比,所提算法无论是在估计精度,还是在计算效率上均有着显著的性能优势。     

空间谱估计中误差自校正方法研究

阵列误差一直是空间谱估计理论实际应用的一个主要瓶颈。该文提出了一种新的阵列误差自校正方法,结合有源校正与在线自校正理论和方法,通过利用一个空间位置方位不需要精确可知的辅助信号源,利用优化算法完成信号源角度以及阵列复增益误差的联合估计,然后将估计的阵列误差参数应用到其后的空间谱估计中。这种自校正算法具有准确度高的优点,并且属于离线算法,一方面避免了传统的有源校正方法对辅助源位置方位精度的严格要求,同时避免了在线自校正算法的大计算量,可以应用到实际空间谱估计中。      

高斯噪声背景下多用户波达方向估计与互耦自校正

在高斯噪声背景下,针对互耦条件下的均匀线阵(Uniform Linear Array, ULA),该文提出了一种联合多用户波达方向(Direction Of Arrival, DOA)估计与互耦误差自校正算法。该算法首先利用特征矩阵联合相似对角化(Joint Approximative Diagonalization of Eigen matrix, JADE)方法估计出各用户广义空间特征矢量,然后定义了一个将各用户广义空间特征矢量转换为只与部分阵元相关的转换矩阵,进而在斜投影及前后向空间平滑的基础上,实现了多用户相干信源DOA估计,最后以多用户相干信源DOA及广义空间特征矢量估计值为基础,给出一种互耦自校正方法。仿真结果表明:该算法具有较高的DOA估计精度及DOA估计成功率,而且对高斯白噪声/色噪声背景,阵列互耦误差已知/未知情形,均具有普适性。     

基于MUSIC迭代法的互耦误差校正

针对阵元之间存在互耦误差,阵列流型会出现一定程度的偏差和扰动的问题,提出了基于MUSIC(MUlti-ple SIgnal Classification)迭代法的互耦误差自校正算法及在互耦误差条件下的DOA(Direction of Arrival)估计算法。利用MUSIC迭代法对波达方向和互耦误差同时进行估计。该算法能够在互耦误差存在的情况下,有效地估计出波达方向和互耦矩阵,仿真实验证明了该算法的有效性。     

Accurate DOA estimation using array antenna with arbitrary geometry

The so called universal steering vector (USV) whose locus is equivalent to the array element pattern is applied to the direction of arrival (DOA) estimation by multiple signal classification (MUSIC) algorithm. It is shown that if the USV which includes the effect of the mutual coupling between the array elements is used, the compensation for the received voltage to remove the effect of the mutual coupling is not required any more. The USV for array antennas with arbitrary geometry is derived and evaluated efficiently by using the method of moments (MoM) so that the DOA estimation can be performed accurately by using the array antenna with arbitrary geometry. Numerical examples of the DOA estimation by a dipole array antenna, and an antenna array composed of a monopole antenna and a planar inverted-F antenna (PIFA) mounted on a mobile handset are presented to demonstrate the effectiveness of the proposed method.     

三正交分离式极化敏感阵列的波达方向估计

该文研究了分离式极化敏感阵列(SS-PSA)的多目标波达方向(DOA)估计问题。首先建立三正交分离式极化敏感均匀稀疏阵列的信号模型;接着利用阵列的旋转不变性采用ESPRIT算法计算出多值模糊DOA估计;利用该模糊DOA估计值对分离式极化天线进行空间相移的补偿,然后利用共点式极化天线之间的多维角度结构求出对应的虚拟DOA估计;最后通过提取多值模糊估计值和对应虚拟估计值之差的最小范数得到多目标的DOA估计。该文所提阵列采用分离式极化天线代替传统共点式极化天线,降低了阵列的互耦影响;采用稀疏阵列结构有效地扩展了阵列的物理孔径,大大提高了DOA估计精度。计算机仿真结果证明了该算法对分离式极化天线DOA估计的有效性和高精度性。     

缝隙阵列天线DOA估计的互耦影响与修正

互耦的存在严重影响了DOA估计的精度，文中研究了存在互耦情况下的DOA估计问题，重点讨论了阵列单元互耦效应的有效计算和对MUSIC算法的修正问题；以缝隙阵列天线为例，通过对无限阵散射参量的修正得到有限阵的散射矩阵和阻抗矩阵，进而通过阻抗矩阵估计互耦的影响，并对MUSIC算法进行修正，最后给出了仿真结果。     

2-D DOA estimation in case of unknown mutual coupling for multipath signals

In this paper, two dimensional (2-D) direction-of-arrival (DOA) estimation problem in case of unknown mutual coupling and multipath signals is investigated for antenna arrays. A new technique is proposed which uses a special array structure consisting of parallel uniform linear array (PULA). PULA structure is complemented with auxiliary antennas in order to have a structured mutual coupling matrix (MCM). MCM has a symmetric banded Toeplitz structure which allows the application of the ESPRIT algorithm for 2-D paired DOA estimation. The advantage of the PULA structure is exploited by dividing it into overlapping linear sub-arrays (triplets) and spatial smoothing is employed to mitigate multipath signals. Closed form expressions are presented for search-free, paired and unambiguous 2-D DOA estimation. Two algorithms PULA-1 and PULA-2 are proposed to effectively solve the problem. Several simulations are done and the accuracy of the proposed solution is shown.     

On the Resiliency of MUSIC Direction Finding Against Antenna Sensor Coupling

Many classical direction of arrival (DOA) estimation algorithms suffer from sensitivity to sensor coupling. By applying a group of auxiliary sensors in a uniform linear array (ULA), we prove the resiliency of the MUSIC direction finding algorithm against array sensor coupling. We show that the performance of MUSIC algorithm under antenna array with unknown coupling can be very close to the case with known coupling. We can also estimate the mutual coupling coefficients before refining the DOA estimates by utilizing an extended sensor array. Moreover, our analysis on the effect of mutual coupling in direction finding illustrates the existence of some blind angles which should be avoided when the array is designed. Our simulation results corroborate our analysis.     

稀疏极化敏感阵列的波达方向和极化参数联合估计

该文采用稀疏分布极化敏感阵列(SD-PSA),研究了多目标波达方向(DOA)和极化参数的估计问题。首先建立稀疏极化敏感阵列信号模型;然后利用阵列的空间旋转不变性运用ESPRIT算法得出信号的高精度周期性模糊多值DOA估计;同时利用子阵列导向矢量之间的关系得出信号的极化信息和DOA的无模糊粗估计;最后利用DOA粗估计值解模糊,得到信号的高精度无模糊DOA估计。该文所提阵列的阵元间距大于半个波长距离,扩展了阵列2维物理孔径,一定程度上降低了阵元间的互耦影响,相应的信号DOA估计精度大大提高。仿真实验结果验证了该算法对信号DOA和极化参数估计的有效性。     

共形阵列天线信源方位与极化状态的联合估计算法

 针对共形天线阵列流形的特点,提出了共形阵列天线信源方位与极化状态的联合估计算法.算法的方位估计不需要信源极化状态的任何信息,估计精度高、分辨力强,在完成信源方位估计的同时,还可以精确的估计出信源的极化状态,不需要参数配对,实现了共形阵列天线信源方位与极化状态的联合估计.算法仅需要二维参数搜索,计算量比已有的联合估计算法小,且适用于任意共形载体,具有广泛的应用范围.对算法参数估计的理论性能进行了分析推导,给出了参数估计的CRB(Cramer-Rao Bound),并通过Monte-Carlo仿真实验验证了理论分析的正确性与算法的有效性.