Estimating DOA and polarization with spatially spread loop and dipole pair array

The nonuniform L-shaped spatially spread loop and dipole（SSLD） array whose inter-element spacing is greater than half a wavelength is studied. A joint parameter estimation algorithm of direction of arrival（DOA）, frequency and polarization is presented for plane-wave signals. The direct sampling and the corresponding delayed sampling data are used to construct the data correlation matrix. On the basis of the subspace theory and the least square method, the frequency and the steering vector of the whole array are obtained. According to the relationship of the array manifold vector between electric dipoles and magnetic loops,the polarization parameters are given. The unambiguous phase estimates are acquired by applying virtual baseline array transformation to the spatial steering vectors, and they are used as coarse references to disambiguate the cyclic phase ambiguities in phase differences between two adjacent array elements on the array,then the high accuracy DOA estimates are obtained. Closed-form solutions for each parameter are obtained. This method has advantages of lower calculation complexity and no parameter matching. The experiment results verify the effectiveness and feasibility of the presented algorithm.

DOA and polarization estimation via signal reconstruction with linear polarization-sensitive arrays

This paper addresses the problem of direction-of-arrival （DOA） and polarization estima- tion with polarization sensitive arrays （PSA）, which has been a hot topic in the area of array signal processing during the past two or three decades. The sparse Bayesian learning （SBL） technique is introduced to exploit the sparsity of the incident signals in space to solve this problem and a new method is proposed by reconstructing the signals from the array outputs first and then exploit- ing the reconstructed signals to realize parameter estimation. Only 1-D searching and numerical calculations are contained in the proposed method, which makes the proposed method computa- tionally much efficient. Based on a linear array consisting of identically structured sensors, the proposed method can be used with slight modifications in PSA with different polarization structures. It also performs well in the presence of coherent signals or signals with different degrees of polarization. Simulation results are given to demonstrate the parameter estimation precision of the proposed method.

米波极化敏感阵列的实值MUSIC测高方法

为获得更高的相干信号角度估计精度,并提高算法可实现性,在极化敏感阵列的基础上,文中提出了一种米波极化敏感阵列的实值多重信号分类测高方法。该方法首先采用矩阵重构的方法消除多径相干信号的影响;其次,利用酉变换对接收数据进行实值处理使其变为实数数据,并利用奇异值技术降低接收数据维度及噪声对接收数据的影响;然后,通过对特征值分解获得的噪声子空间矩阵进行空间谱估计获得目标仰角;最后,利用几何关系获得目标高度。由于该方法完全用实值运算来表述,因而可以显著降低计算复杂度。仿真结果表明:该方法测高精度更高,更利于工程实现。

双极化面阵的快速波达方向估计算法

针对目前极化敏感面阵空域-极化域联合谱估计运算量大、耗时长的问题,提出一种降维求根MUSIC(Multiple Signal Classification)优化算法。通过对接收信号进行降维处理,提出新的求解模型将传统四维MUSIC转化为两个一维求根MUSIC求解空域波达方向和引用已求解出的空域信息结合拉格朗日乘子法解决来波信号极化信息估计问题。相比传统的4D-MUSIC和秩亏MUSIC,所提算法在不损失估计精度的前提下提高了运算速度,降低了运算复杂度,无需谱峰搜索过程,消除了因搜索步长而导致的量化误差。对日后大规模阵列计算及MIMO(Multiple Input Multiple Output)雷达引入提供快速求解方法。仿真实验表明,所提算法在低信噪比0 dB下空域误差约为0.85°,速度相比秩亏MUSIC提升了约64.7%,验证了该算法的有效性和高精度性。

Cramér-Rao bound for multiple parameters estimation using a polarization sensitive array

In this paper, new Cramér-Rao lower bounds （CRB） of the estimates of frequencies, two-dimensional arrival angles and polarization parameters of multiple incident signals are derived for a polarization sensitive array. The incident sources have distinct carrier-frequencies, in contrast to the modeling of all sources to be at the same known carrier-frequency, which has been investigated in the existing research literature on the Cramér-Rao bounds （CRB） for polarization sensitive direction finding. The derived CRBs are compact closed-form expressions and applicable to an arbitrary array geometry. Numerical examples and analysis of some special cases provide insights into the fact that the estimation accuracy of all parameters is enhanced with the increasing signal-to-noise ratio （SNR） and number of snapshots. In addition, they are hardly influenced by the sampling frequency and independent of the initial phase of incident sources. These insights offer guidelines to the system engineer on how to improve parameters＇ estimation accuracy.

多跳频信号波达方向与极化状态联合估计算法

为了有效辅助跳频(FH)网台分选和信号识别、跟踪,该文用正交偶极子对构造极化敏感阵列,基于空间极化时频分析,在欠定条件下实现了多跳频信号波达方向(Direction Of Arrival,DOA)与极化状态的高效联合估计。首先建立跳频信号的极化敏感阵列观察模型,然后根据参考阵元时频分析结果建立各跳信号的空间极化时频分布矩阵,再利用该矩阵中蕴含的信号极化-空域特征信息分别运用线性、二次型空间极化时频以及多项式求根共3种方法实现DOA与极化参数联合估计,最后蒙特卡罗仿真结果验证了该算法的有效性。

一种改进的极化敏感阵列解相干算法

在相干信号源情形下,常用的极化敏感阵列信号处理方法(如参数估计、波束形成等)会出现性能下降甚至失效的现象。该文在极化平滑算法的基础上提出一种改进的解相干算法,通过对各子相关矩阵选择适当的加权系数,使平滑之后的相关矩阵具有Toeplitz的形式,进而消除信号之间的相干性。该文推导了最优加权系数的表达式及最大解相干信号个数,并利用加权平滑之后的相关矩阵完成了参数估计和波束形成。计算机仿真结果表明改进的方法具有比常规极化平滑算法更优越的性能,且适用于非均匀噪声和相干噪声的情况。

极化敏感阵列及其应用研究

与普通阵列相比,极化敏感阵列由于利用了极化信息,不仅能完成空域信号的处理,还可完成极化域信号的处理。因此,极化敏感阵列在抗干扰能力、信号检测能力、分辨率、极化多址能力等方面都有很大的优势。针对极化敏感阵列的理论优势作了说明,对其在信号处理和信号检测方面的应用作了详细的阐述。从中可以看出,极化敏感阵列具有更加广阔的应用前景。

基于子空间原理的共形阵列多参数联合估计算法

由于共形载体表面曲率变化的影响,共形阵列流形中的信源方位与极化状态产生"耦合",为多维参数联合估计带来较大难度。针对该问题,利用交叉电偶极子对天线单元在锥面和柱面载体上合理布阵,建立了其快拍数据模型,并提出一种信源方位和极化状态的联合估计算法。算法利用锥面和柱面等单曲率结构的特殊性合理设置坐标系,从而避免了多维角度搜索,有效降低了运算量,并且很容易推广到其他多种单曲率几何结构的共形载体中。Monte Carlo仿真验证了算法的有效性。

基于电磁矢量阵列孔径扩展方法的相干目标DOA估计

该文采用均匀且稀疏分布的电磁矢量矩形阵列,针对相干目标提出了一种有效的2维波达角(DOA)估计算法,该算法通过增加相邻阵元的间隔来扩展阵列的有效孔径,从而提高算法的DOA估计性能。论文首先结合极化平滑算法和传播算子方法得到存在相位周期性模糊的方向余弦估计。为了解决模糊性问题,论文通过协方差矩阵平滑提出一种新的解相干预处理算法,由该算法得到的信号子空间包含矢量阵元的导向矢量,且不存在相位模糊,利用此特点实现去模糊处理,得到目标的DOA估计。仿真结果表明,与基于ESPRIT的孔径扩展算法相比,提出的算法能够实现相干目标的DOA估计,同时无需特征值或奇异值分解,有更低的运算量。

基于时空极化导向矢量的阵列信号多维参数联合估计

通过对极化敏感阵列的时域采样构造了具有旋转不变结构的矩阵对,该矩阵对分解的特征值与对应特征向量分别是旋转矩阵和阵列的时空导向矢量,利用该导向矢量和旋转矩阵直接得到信号的频率、二维波达方向和极化的联合估计,该多维参数计算方法具有虚拟阵元和较高的估计精度。简述了多维ESPRIT方法的基本原理,其配对方法采用了多个矩阵束具有相同的特征向量,两种方法均利用了的相同信息-矩阵束的特征值和特征向量,仿真实验验证和比较了两种方法的性能。

基于极化敏感阵列均匀线阵的二维DOA估计

针对残缺电磁矢量传感器的极化敏感阵列多参数联合估计问题,该文提出一种基于正交偶极子的均匀线阵的2维波达方向(Direction-Of-Arrival,DOA)估计算法。首先,对极化敏感阵列的接收数据矢量的协方差矩阵进行特征分解,然后将信号子空间划分成4个子阵,根据旋转不变子空间(ESPRIT)算法分别求出其中1个子阵与其它3个子阵的相位差,再对不同子阵间的相位差进行配对,最后根据相位差求出信号的DOA估计和极化参数。由正交偶极子组成的均匀线阵使用极化MUSIC算法和传统ESPRIT算法无法进行2维DOA估计,该文提出的算法解决了这个问题,并且相较于极化MUISC算法降低了算法的复杂度。仿真结果验证了该文算法的有效性。

一种基于极化敏感阵列的近场源五维参数估计方法

该文提出了一种基于四阶累积量近场窄带信源参数新的估计方法。该方法利用极化敏感阵列和多重旋转矢量不变技术估计信源五维参数(载波频率、方位角、俯仰角、距离和极化参数),无需谱峰搜索和多维参数匹配,且适用于加性高斯噪声环境。此外,该方法由于采用了非中心对称结构的阵列,可有效减少阵列孔径损失。仿真实验验证了该方法的有效性。

Ka波段双极化直接检波式全功率辐射计研究

提出一种新型的双极化毫米波(MMW)全功率辐射计结构,通过两路直接检波式接收机接收目标辐射信号的2个正交极化分量对目标进行检测识别。在论述其系统结构和工作原理基础上,对系统性能进行了分析。分析表明:此辐射计温度灵敏度高,输出信号信噪比好,作用距离远,并对存在水平、垂直极化视在温度差的虚假目标有较好的识别性能。

一种改进的基于极化敏感阵列的弱信号检测算法

针对空间复杂电磁干扰影响下全球导航卫星系统(GNSS)连续性、完好性和可用性方面面临的巨大挑战,基于极化敏感阵列,提出了一种改进的弱压制干扰信号检测算法。首先对各个极化天线阵子接收的实时数据进行空域、频域和极化域的联合处理,然后对各个频域分量的特征值进行降序排列,进而通过全频段的特征值分布曲线准确分离出强干扰环境下的弱信号分量。结果表明,采用基于多级维纳分解的改进最小描述长度(MDL)准则,可以在不进行特征值分解的前提下有效地进行干扰检测,极大降低了检测算法的实现功耗和复杂度,仿真结果也验证了算法的有效性和准确性。改进算法适用于不同的天线阵型,在存在幅相误差的情况下仍有较高的检测概率,具有较大的工程实践价值。

基于波束空间的极化域-空域联合谱MUSIC算法

极化敏感阵列可以获取到空间电磁信号的极化信息,具有优越的系统性能,可以更充分地利用信号中包含的信息。极化域-空域联合谱MU S IC算法是一种高性能的算法,但是在两信号参数相差不大,尤其是极化角度接近时无法分辨,在低信噪比、干扰信号功率较大时算法性能明显下降,本文将波束空间预处理的方法应用该算法,阵列的抗干扰能力得到了提高,实验证明新算法的有效性。

一种基于MH抽样的极化域—空域联合谱MUSIC估计算法

针对联合谱MUSIC算法中谱峰搜索计算量大的问题,通过运用马尔可夫蒙特卡罗(MCMC)方法,提出一种计算量减小的联合谱MUSIC测向算法。该算法通过将极化联合谱MUSIC函数视为信号来向的概率密度函数,采用MCMC的MH抽样方法,能够在保持常规联合谱MUSIC算法高分辨能力的同时大大减少运算量,仿真结果验证了算法的有效性。

阵元指向未知条件下的信号波达方向估计

提出了一种适用于阵元指向未知情形的极化敏感阵列信号波达方向(DOA)估计方法。该方法利用降秩准则将信号方向、极化和阵元指向信息进行解耦,通过唯角度参数搜索完成信号DOA估计,避免了复杂的多维寻优。讨论了新方法实现无模糊DOA估计的必要条件,并将其与利用错误指向信息的DOA估计方法进行了性能比较。结果表明:对于阵元指向未知或存在一定误差的场合,该算法的估计性能更优。

Joint frequency,2-D DOA,and polarization estimation using parallel factor analysis

This paper proposes a new algorithm for joint frequency, two-dimensional （2-D） directions-of-arrival （DOA）, and polarization estimation using parallel factor （PARAFAC） analysis model and cumulant. The proposed algorithm designs a new array configuration, and extends the PARAFAC analysis model from the common data-domain and subspace-domain to the cumulant one, and forms three-way arrays by using the three cumulant matrices obtained from the properly chosen dipole outputs, and analyzes the uniqueness of low-rank decomposition of the three-way arrays, and then jointly estimates the source parameters via the low-rank decomposition of the constructed PARAFAC model. In comparison with the conventional methods, the proposed method alleviates the aperture loss, and avoids pairing parameter. Finally, the simulation results are presented to validate the performance of the proposed method.

Source localization using a non-cocentered orthogonal loop and dipole (NCOLD) array

A uniform array of scalar-sensors with intersensor spacings over a large aperture size generally offers enhanced resolution and source localization accuracy,but it may also lead to cyclic ambiguity.By exploiting the polarization information of impinging waves,an electromagnetic vector-sensor array outperforms the unpolarized scalar-sensor array in resolving this cyclic ambiguity.However,the electromagnetic vector-sensor array usually consists of cocentered orthogonal loops and dipoles（COLD）,which is easily subjected to mutual coupling across these cocentered dipoles/loops.As a result,the source localization performance of the COLD array may substantially degrade rather than being improved.This paper proposes a new source localization method with a non-cocentered orthogonal loop and dipole（NCOLD）array.The NCOLD array contains only one dipole or loop on each array grid,and the intersensor spacings are larger than a half-wavelength.Therefore,unlike the COLD array,these well separated dipoles/loops minimize the mutual coupling effects and extend the spatial aperture as well.With the NCOLD array,the proposed method can effciently exploit the polarization information to offer high localization precision.