Underdetermined direction of arrival estimation with nonuniform linear motion sampling based on a small unmanned aerial vehicle platform

Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suffers from significant performance degradation owing to the limited number of physical elements.To improve the underdetermined DOA estimation performance of a ULA radar mounted on a small UAV platform,we propose a nonuniform linear motion sampling underdetermined DOA estimation method.Using the motion of the UAV platform,the echo signal is sampled at different positions.Then,according to the concept of difference co-array,a virtual ULA with multiple array elements and a large aperture is synthesized to increase the degrees of freedom(DOFs).Through position analysis of the original and motion arrays,we propose a nonuniform linear motion sampling method based on ULA for determining the optimal DOFs.Under the condition of no increase in the aperture of the physical array,the proposed method obtains a high DOF with fewer sampling runs and greatly improves the underdetermined DOA estimation performance of ULA.The results of numerical simulations conducted herein verify the superior performance of the proposed method.

JOINT SPACE-FREQUENCY MULTIUSER SYMBOL DETECTOR FOR MC-CDMA SYSTEM WITH UNIFORM LINEAR ARRAY

The MultiCarrier Code Division Multiple Access (MC-CDMA) scheme is promising for relieving capacity limit problems of Direct Sequence (DS-) CDMA systems due to serious InterChip Interference (ICI) and MultiUser Interference (MUI) in high-data-rate wireless communication systems. In this paper, the Uniform Linear Array (ULA) is applied to the base station of macrocellular MC-CDMA systems in a frequency-selective fading channel environment. A joint space-frequency multiuser symbol sequence detector is developed for all active users within one macrocell without space-frequency channel estimation. Simultaneously, Directions-Of-Arrivals (DOAs) of all active users can also be estimated. By dividing the ULA into two identical overlapping subarrays, a specific auxiliary matrix is constructed, which includes both symbol sequence and DOA information of all active users. Then, based on the subspace method, performing the eigen decomposition on such auxiliary matrix, the closed-form solution of symbol sequences and DOAs for all active users can be obtained. In comparison with schemes based on channel estimation, our algorithm need not explicitly estimate the space-frequency channel for each active user,so it has lower computation complexity. Extensive computer simulations demonstrate the overall performance of this novel scheme.

MODE SPACE SMOOTHING ALGORITHM TO ESTIMATE DOA OF COHERENT SIGNALS IMPINGING ON UNIFORM CIRCULAR ARRAY

A novel method to estimate DOA of coherent signals impinging on a uniform circular array( UCA) is presented in this paper. A virtual uniform linear array (VULA) is first derived by using spatial DFT technique, transforming the UCA from element space to phase mode space to obtain the properties of ordinary ULA, and then the well known spatial smoothing technique is applied to the VULA so that the lost rank of covariance matrix due to signal coherence can be retrieved. This method makes it feasible to use the simple MUSIC algorithm to estimate DOA of coherent signals impinging on a UCA without heavy computation burden. Simulation results strongly verify the effectiveness of the algorithm.

Direction Finding Using Cumulant in Multipath Environment with an Arbitrary Array

In this paper, the problem of estimating the direction of arrival of signals of which some may be perfectly correlated is considered. This method can be applied in the situation that the non-Gaussian independent and coherent signals coexist with unknown Gaussian noise. In this method at first via mappings, the virtual uniform linear array (ULA) and also the shifted versions of this virtual ULA by assuming that all the DOAs are located in one section are constructed. In order to avoid coloring the noise because of these mappings we use a cumulant matrix instead of a covariance ones. In this method since we construct all the subarrays virtually for detection of coherent signals we do not need the array with regular configuration. The advantages of this method are: increasing the array aperture, having the ability to find the DOAs with fewer sensors and also avoiding the coupling between sensors as much as possible in contrast to conventional spatial smoothing.

Improved Capon Estimator for High-Resolution DOA Estimation and Its Statistical Analysis

Despite some efforts and attempts have been made to improve the direction-of-arrival(DOA)estimation performance of the standard Capon beamformer(SCB)in array processing,rigorous statistical performance analyses of these modified Capon estimators are still lacking.This paper studies an improved Capon estimator(ICE)for estimating the DOAs of multiple uncorrelated narrowband signals,where the higherorder inverse(sample)array covariance matrix is used in the Capon-like cost function.By establishing the relationship between this nonparametric estimator and the parametric and classic subspace-based MUSIC(multiple signal classification),it is clarified that as long as the power order of the inverse covariance matrix is increased to reduce the influence of signal subspace components in the ICE,the estimation performance of the ICE becomes equivalent to that of the MUSIC regardless of the signal-to-noise ratio(SNR).Furthermore the statistical performance of the ICE is analyzed,and the large-sample mean-squared-error(MSE)expression of the estimated DOA is derived.Finally the effectiveness and the theoretical analysis of the ICE are substantiated through numerical examples,where the Cramer-Rao lower bound(CRB)is used to evaluate the validity of the derived asymptotic MSE expression.

Joint calibration algorithm for gain-phase and mutual coupling errors in uniform linear array

The effect of gain-phase perturbations and mutual coupling significantly degrades the performance of digital array radar (DAR). This paper investigates array calibration problems in the scenario where the true locations of auxiliary sources deviate from nominal values but the angle intervals are known. A practical algorithm is proposed to jointly calibrate gain-phase errors and mutual coupling errors. Firstly, a simplified model of the distortion matrix is developed based on its special structure in uniform linear array (ULA). Then the model is employed to derive the precise locations of the auxiliary sources by one-dimension search. Finally, the least-squares estimation of the distortion matrix is obtained. The algorithm has the potential of achieving considerable improvement in calibration accuracy due to the reduction of unknown parameters. In addition, the algorithm is feasible for practical applications, since it requires only one auxiliary source with the help of rotation platforms. Simulation results demonstrate the validity, robustness and high performance of the proposed algorithm. Experiments were carried out using an S-band DAR test-bed. The results of measured data show that the proposed algorithm is practical and effective in application. (C) 2016 Production and hosting by Elsevier Ltd. on behalf of Chinese Society of Aeronautics and Astronautics.

Effects of Spatial Characteristics on Smart Antenna System with Uniform Linear Antenna Array

The effect of the spatial characteristics of antenna array on smart antenna systems can not be neglected. In the paper, the relation between spatial correlation and inter-antenna distance, impinging angle, angle spread is first investigated. With the same beam forming algorithm, we simulate the performance of smart antenna system with different Angle Spread （AS） values on the conditions of ideal and real Angle of Arrival （AOA） estimation. The results show that with the ideal AOA estimation, the AOA is enough accurate to guarantee that the system only has little performance degradation even in the case of 20 degreee AS value while the real AOA estimation influenced by channel environment degrades the performance very obviously, up to about 7 dB.

Length minimization of uniform linear antenna array for millimeter wave communications with maximum capacity

For uniform linear antenna array （ULA） based millimeter wave communications, the maximum capacity can be achieved by the optimal antenna separation product （ASP）. However, due to the practical size limitation, it is necessary to decrease the ULA length. In this paper, an optimization problem is formulated to minimize the ULA length for millimeter wave communications with maximum capacity. We decompose the problem into two subproblems： length selection optimization and orientation deployment optimization. The optimal length selection can be obtained when the transmit and receive ULAs have equal length. By using the property of trigonometric function, we derive the optimal orientation deployment and study the influence of orientation deviation on ULA length. Simulation results are presented to validate the analyses.

基于协方差匹配技术的互耦和幅相误差联合校正算法

提出了基于协方差匹配技术的均匀线阵互耦和幅相误差联合校正算法.首先,根据协方差匹配技术中的目标函数和均匀线阵的误差模型,设计了一种交替迭代算法用以实现各种参数的优化计算.接着,为了避免该算法中的每轮循环迭代都需要进行波达方向估计这一复杂环节,利用理想条件均匀线阵协方差阵的Toeplitz性,给出了另一种改进型交替迭代算法用以减少计算复杂度.与基于子空间技术的阵列误差校正方法相比,文中的两种新算法可直接利用信源的统计特性,并且适用于不同的高斯噪声模型(例如噪声功率不一致),仿真实验验证了新算法的有效性和优越性.

垂直线列阵结构对PTRM阵处理空间增益的影响

水声信道多径的复杂性使得被动时间反转镜(PTRM)技术成为一大研究热点。该文推导了多阵元PTRM原理表达式,在此基础上给出了PTRM阵处理获得空间增益的机理,首次从理论上分析了垂直线列阵结构对PTRM阵处理空间增益的影响,并通过计算机仿真验证了理论分析,结果表明,PTRM阵处理空间增益随着阵元数目的增加而得到提高;当阵元间距足够大时(大于半个波长,使噪声不相关),阵元间距对PTRM阵处理的空间增益没有明显影响,此时影响到通信质量的主要是信噪比。

基于空间谱的频谱感知算法及性能分析

现有的基于特征值或谱密度的频谱感知算法,多分别使用近似高斯分布和Tracy-Widom分布来分别分析求解检验统计量在信号是否存在时的分布,未能给出统一的解析表达式。该文提出均匀线阵(ULA)条件下基于空间谱密度比的频谱感知算法,并且基于顺序统计量的最新研究成果,给出检验统计量统一的闭合表达式。该算法基于离散空间谱密度最大最小值的比建立检验统计量。仿真结果表明,对于8阵元的ULA,在采样点数为1000、检测概率为0.9时,所提算法比最大最小特征值(MME)比算法有约1.7 d B的性能优势,同时也有效验证了检验统计量理论分布的准确性。

MIMO雷达非均匀布阵的性能分析

多输入多输出(MIMO)雷达是一种新体制雷达,它在发射端发射正交信号,从而产生虚拟阵元,扩大阵列孔径,在DOA估计、参数识别等方面的性能较相控阵雷达有很大提高。而目前有关MIMO雷达中虚拟阵元的讨论都以均匀线阵(ULA)为基础,并与相控阵雷达的性能进行比较。文中在ULA的基础上,研究了非均匀线阵(NLA),研究结果表明,非均匀线阵产生了更多的有效虚拟阵元,与相控阵雷达和ULA布阵MIMO雷达相比,具有更多的空间自由度、更好的克拉美.罗界和更好的DOA性能。

均匀线阵混合信源DOA估计与互耦误差自校正

针对均匀线阵(uniform linear array,ULA)互耦条件下混合信源的波达方向(direction of arrival,DOA)估计问题,基于联合对角化算法,提出了一种基于3步实现的DOA与互耦系数估计新算法。首先利用互耦矩阵的Toeplitz结构实现混合信源中独立信源的DOA及互耦系数的粗估计;然后结合斜投影及前后向空间平滑,实现混合信源DOA估计;最后以广义空间特征矩阵及混合信源DOA估计值为基础,提出一种非子空间类互耦系数自校正方法。计算机仿真结果表明,与同类算法相比,所提算法无论在DOA及互耦系数估计精度、还是在DOA估计成功率方面,均具有明显的优势,且对于高斯背景噪声具有普适性。

多子阵互耦影响下的鲁棒自校正算法

针对多子阵中各子阵的标称方向可能存在扰动偏差这一问题,给出了一种多子阵互耦影响下的鲁棒自校正算法。与现有很多互耦自校正算法类似,本文算法同样利用了均匀线阵互耦矩阵的带状、对称Toeplitz性以及多子阵互耦矩阵的块状对角特性,从而避免了多参数联合估计中的多维非线性搜索以及迭代运算。不同的是,本文算法能够克服各子阵标称方向的扰动偏差,具有更强的鲁棒性。此外,还推导了多参数联合估计的克拉美罗界。仿真实验验证了本文算法的有效性和优越性。

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。

低复杂度相干分布源中心DOA估计方法

传统的相干分布源波达方向(DOA)估计方法一般都需要谱搜索或对高维样本协方差矩阵进行特征分解,计算复杂度较高。针对上述问题,本文利用均匀线阵提出了一种低复杂度相干分布源中心波达方向估计方法。所提方法利用了平移阵列的旋转不变性质并结合传播算子法来估计分布源的中心波达方向。相比于常规子空间方法,本方法无需任何谱峰搜索和对样本协方差矩阵进行特征分解,计算复杂度更低。方法在小角度扩展条件下的估计性能良好,其性能甚至接近于DSPE算法。而且方法与分布源角分布的具体形式无关,是一种盲的估计。仿真结果证实了方法的有效性。

基于子空间类法的阵列误差有源校正方法

针对均匀线阵提出了一种对同时存在阵元位置误差、幅相误差及阵元互耦的阵列进行校正的方法。该方法通过旋转阵列天线得到多个校正方位的样本数据,达到多个信源独立分时校正的效果,然后通过对空时矩阵进行特征分解,得到实际阵列流型的估计值,并构造代价函数,最后采用迭代算法同时估计出所有阵列误差参数,从而实现误差的校正。计算机模拟仿真及实际阵列天线的校正实验均验证了该算法对误差参数估计的有效性和校正方法的实用性。

一种简单快捷的完全可扩展线阵设计

本文设计了一种具有准均匀线阵形式的完全可扩展线阵,在实现了可简单快捷设计的同时又获得了较大的阵列孔径,其孔径接近完全可扩展线阵中具有最大孔径的约束最小冗余线阵,但却无需设计约束最小冗余线阵中的繁冗搜索,在阵元数很大时本文的设计显得尤为实用。

一种相干分布源中心DOA快速跟踪算法

在智能天线和无线定位等技术中,精确跟踪目标的波达方向(DOA)十分重要。大多数传统的DOA跟踪方法都将目标信号看成是点源。但在密集的移动通讯环境中,信号的多径散射将引起信号能量的扩散,采用分布式信源模型更适合。因此,研究分布源的DOA跟踪技术更有意义和价值。针对相干分布源,本文基于均匀线阵提出了一种中心DOA快速跟踪算法。该算法首先通过正交紧缩近似投影子空间跟踪(OPASTD)算法实时更新信号子空间,然后利用一种低复杂度的方法估计分布源的中心DOA。本文算法避免了对样本协方差矩阵进行重复的特征分解,计算复杂度较低。算法的跟踪性能良好,并能有效跟踪多个分布源。此外,算法不需要分布源角分布形式的先验知识,稳健性好。仿真结果证实了算法的有效性。

基于FFT的子孔径MUSIC波达方向估计

针对现有的很多波达方向估计算法涉及到数据协方差矩阵的估计及其特征分解,甚至是求逆,导致运算复杂度高的问题,提出了基于快速傅里叶变换的子孔径MUSIC波达方向估计算法。首先将等距线阵的接收数据矢量均匀划分为4个子矢量,然后对各个子矢量分别求FFT。将FFT的结果相干积累,并找到最大峰值点。最后,利用子矢量FFT的结果中与最大峰值点对应的数据构造新的降维矢量,借助MUSIC算法进行波达方向估计。该方法避免了直接接收数据的协方差矩阵估计和特征分解,有效地降低了运算量和计算复杂度,在阵元数和快拍数都较多的情况下优越性尤为明显。计算机仿真验证了所提方法的有效性和优越性。