一种基于L阵的二维解相干测向算法

本文对高斯白噪声环境下基于L型阵列二维测向的ESPRIT算法进行了改进.该算法利用阵列结构特点通过平滑原理获得3个互相关矩阵,然后由3个矩阵构造一个特殊大矩阵并对其进行奇异值分解来估计信号子空间,最后利用2D-ESPRIT方法实现二维测向.该算法估计精度高,运算量小,能够对相干信号进行估计.     

时-空二维信号模型下的目标参数估计

提出一种基于时空二维信号模型下相干信号源参数估计的LS-ESPRIT算法,解决了常规ESPRIT算法不能解相干等问题。和解相干的MUSIC算法相比,该方法不需要在整个空间进行谱峰搜索,运算量小。仿真结果表明,该方法适用于所有信号(包括非相干和相干信号)的目标二维参数与多普勒频率估计。在不同信噪比(SNR)情况下,其估计精度较常规方法有了较大的提高,可以满足工程应用的需要。     

基于均匀圆阵相干信源的二维DOA估计

随着通信技术的不断发展,信号传输环境变得日益复杂。针对多径传播形成的高度相关和相干信号测向问题,提出了一种基于均匀圆阵相干信源的二维DOA估计方法。该方法利用均匀圆阵轴向虚拟平移解相干,通过去噪后利用虚拟子阵的自协方差矩阵和互协方差矩阵构造波达方向矩阵,利用该矩阵特征分解估计信号的俯仰角;然后将平滑后的自协方差矩阵与波束空间变换矩阵相乘,使圆阵的导向矢量具备范德蒙结构,最后用求根MUSIC算法估计出信号的方位角,完成了相干信号的二维DOA估计。该方法无需二维谱峰搜索,方位角和俯仰角自动配对,计算量小,分辨率高。仿真实验证明了所提方法的正确性。     

基于四阶累积量的相干信号频率和二维到达角联合估计的新算法

该文提出了一种基于四阶累积量的相干信号频率和二维到达角联合估计的新算法-CTSS算法.CTSS算法利用双平行线阵的时空数据以及平滑技术构造了一个时空平滑矩阵,通过对其进行特征分解,并利用分解得到的特征值和特征矢量估计出空间相干信号的三维参数.在色噪声环境下,该算法能够精确地估计空间相干信号的三维参数,无需多维谱峰搜索,能实现信号三维参数的自动配对,并有效地解决了信源参数兼并问题.计算机仿真结果验证了算法的有效性.     

宽频段相干信号三维参数联合估计的新算法

基于非均匀的L型阵列,本文提出了一种宽频段相干信号频率和二维到达角联合估计的时空二维处理新方法-WTSS(wide-band time-space smoothing)算法.该算法能精确地估计具有相同数字频率的相干信号的三维参数,无需多维谱峰搜索,具有计算量小,参数自动配对的优点.另外,在WTSS算法的基础上,利用L型阵列的特点进行分维处理,成功地实现了具有频率兼并现象的相干信号的三维参数估计.该算法能够并行实现以进一步增强其实时性.计算机仿真结果验证了算法的有效性.     

单快拍数据的分布式二维阵列测角方法研究

该文针对2维阵列波达方向估计问题,提出一种基于单快拍数据的分布式2维DOA估计算法。该算法首先利用每个子阵单元的单快拍数据进行2维Hankle矩阵构造;然后基于2维状态空间平衡法分别获得方位角和俯仰角子阵单元内DOA估计与子阵单元间DOA估计;最后通过解模糊算法获得方位角和俯仰角高精度无模糊DOA估计。该算法较好地解决了子阵单元内DOA估计和子阵单元间DOA估计之间的配对问题以及俯仰角和方位角之间配对问题,充分利用分布式阵列扩展阵列物理孔径特性;同时该算法可直接对相干信号和非相干信号进行处理。计算机仿真结果验证了所提算法的有效性。     

基于降维处理的MUSIC二维DOA估计算法

针对 MUSIC(多重信号分类法)估计方法实现二维 DOA(波达方向)估计的计算量大且遍历搜索耗时的问题,给出了一种基于降维处理的 MUSIC 算法。该算法无需进行二维谱峰值搜索。该算法利用二次优化方法将二维 DOA 估计分解为一维 DOA 估计,先通过一维 MUSIC 估计获得信号与 x 轴夹角,再利用最小二乘算法估计获得信号与 y 轴夹角。最后利用角度关系式得到信号的二维 DOA 估计值。该算法的复杂和搜索范围都大大降低,仿真表明,该算法具有较好的角度估计效果。     

六角形阵列相干信号二维DOA估计

提出了一种基于扩展重构相关矩阵去相干的二维DOA估计算法。针对六角形阵列的结构特点,首先对各个阵元的接收数据求其共轭矩阵来扩展阵列,扩展后的阵列分为3个六角形子阵列,以此为基础,求得各子阵列的自相关矩阵及互相关矩阵来扩展重构相关矩阵,从而实现解相干的目的,最后利用二维MUSIC算法进行DOA估计。该算法在不减少阵列有效孔径的前提下,增加了可估计相干源数目,并且能够得到较好的估计性能。最后,通过计算机仿真证实了该算法的有效性。      

非均匀噪声背景下混合信号DOA估计算法

针对非均匀噪声背景下非相关信源与相干信源并存时波达方向(DOA)估计问题，提出了基于迭代最小二乘和空间差分平滑的混合信号DOA估计算法。首先，该算法利用迭代最小二乘方法得到噪声协方差矩阵估计，然后对数据协方差矩阵进行“去噪”处理，利用子空间旋转不变技术实现非相关信源DOA估计；其次，基于空间差分法消除非相关信号并构造新矩阵进行前后向空间平滑，利用求根MUSIC算法估计相干信源DOA。相比于传统算法，该算法能估计更多的信源数，在低信噪比情况下DOA估计性能更优越。仿真实验结果验证了该算法的有效性。      

单快拍数据的分布式阵列DOA估计

该文针对分布式阵列相干信号单次快拍波达方向估计问题,提出一种基于状态空间平衡法的1维波达角估计算法。该算法首先直接利用单快拍数据以分布式阵列每个子阵单元进行Hankle矩阵构造,然后采用状态空间平衡法,分别获得低精度无模糊的子阵单元内DOA估计和高精度有模糊的子阵单元间DOA估计,最后结合配对和解模糊算法获得高精度无模糊DOA估计。该算法不受信号形式限制,可同时对相干信号和非相干信号进行处理,能充分利用分布式阵列扩展阵列物理孔径特性,获得较高的DOA估计精度。计算机仿真结果验证了所提算法的有效性。     

基于虚拟阵列的二维稀疏阵列相干源DOA估计

波达方向DOA估计是雷达阵列信号处理的一个重要方向,传统的MUSIC算法对均匀阵列条件下独立信号源的估计有很强的适应性,但实际的雷达工作中,稀疏布阵下多相干源测角是一个经常出现的应用场景。文中针对二维稀疏阵列的相干源测角,提出了一种基于虚拟阵列的相干源DOA估计方法。该方法利用虚拟阵列内插的方法,将一个任意二维稀疏阵列内插为一个均匀面阵,再通过二维空间平滑方法对相干源进行测角,能够同时获得信号的方位角和俯仰角信息。稀疏面阵和稀疏圆阵的仿真实验结果表明,该方法可以有效的解决二维稀疏阵列的相干源测角问题。     

ICA-based direction-of-arrival estimation of uncorrelated and coherent signals with uniform linear array

A novel approach for direction-of-arrival (DOA) estimation of uncorrelated and coherent signals with uniform linear array is proposed in this paper. First, the mixing matrix, which contains all azimuth information of signal sources, is estimated by independent component analysis. Afterward, several parameter equations are established upon the new mixing matrix. Finally, all DOAs of coherent and uncorrelated signals are estimated by solving these equations. Compared with traditional methods, the proposed method has higher angle resolution and estimation accuracy. Moreover, the signal number resolved by our approach can exceed the number of array elements. Simulation results have demonstrated the efficiency of the proposed method.     

PULSE CUMULATING METHOD FOR MULTI-TARGETS'''' JOINT AZIMUTH-ELEVATION FREQUENCY-DELAY ESTIMATION

The Directions of Arrivals (DOAs), speeds and distances of targets are all required for array signal processing. Based on the periodic phase shift of coherent pulse sequence waveform, a new estimation of multi-targets' 2-Dimentional (2-D) DOA angle, Doppler frequency shift and relative time-delay is proposed. Based on a virtual sensor array constructed by pulse cumulating, the estimations of azimuth, elevation, Doppier frequency shift and time-delay can be obtained simultaneously, and the least number of pulses could be two. This method is computationally efficient even in heavier noised environment, and all estimations are automatically paired in calculation process with no spectrum searching. Further more, this algorithm can be used to any plane sensor array and deal with many targets at the same time only by few sensors. The targets number that can deal with simultaneously is several times to the sensor number, which is the upper limit for normal algorithms such as ESPRIT and MUSIC. These characteristics would be very useful, especially, for aerial systems. Simulations demonstrate the capabilities of this method efficiently.     

基于均匀圆阵的宽带相干LFM信号定位方法

本文提出一种基于均匀圆阵的宽带相干LFM信号定位方法。首先，算法根据LFM信号在分数阶傅里叶域的能量聚焦性，对接收信号做分数阶傅里叶变换，实现宽带信号的窄带化处理；其次，利用圆阵的虚拟轴向平移形成的相位差构造空间平滑矩阵，完成相干信号的解相干处理；最后，对空间平滑矩阵进行奇异值分解得到相邻阵元接收数据的相位差，结合相位差反演参数估计算法得到二维角度参数估计的闭式解。仿真实验验证了算法对宽带相干LFM信号定位的有效性。     

Near-field coherent source localization by planar array design

This paper is concerned with near-field source localization for scenarios where coherent narrowband sources exist. In this paper, we propose a new method in which we design a general planar array with a covariance matrix whose rank is not decreased by the coherence between sources. Moreover, conditions for the sensor locations in the designed planar array are derived to reach maximum effective array aperture. The proposed method uses second order statistics and features a separable range-bearing search to reduce the computational complexity. This method localizes near-field sources with a number of one-dimensional searches in two steps. In the first step, ranges of sources is estimated using one 1D search and in the second step, the bearing of each signal source is estimated using the corresponding range estimated in the first step. Simulation results show that the performance of the proposed method is comparable with the Cramer–Rao bound.

     

混合信号情况下信源数与DOA联合估计算法

针对非相关信源与相干信源共存情况,提出了一种基于矩阵重构的信源数与波达方向（direction of arrival,DOA）联合估计算法.该算法首先利用特征值的二阶统计量（second order statistic of eigenvalues,SORTE）法和子空间旋转不变技术（estimated signal parameter via rotational invariance techniques,ESPRIT）实现非相关信源数与DOA估计;然后基于空间差分法消除非相关信号并构造新矩阵,利用构造矩阵进行前向空间平滑,实现对相干信源解相干;最后利用SORTE法检测相干信源数,结合求根多重信号分类（multiple signal classification,MUSIC）算法估计相干信源DOA.与传统的差分平滑方法相比,该算法在可估计信源数与低信噪比情况下DOA估计性能等方面优于传统算法.数值仿真实验结果验证了该算法的有效性.     

Spatial spectrum estimation in a coherent signal environment using an array in motion

Spatial spectrum estimation utilizing an array in motion is here investigated for dealing with coherent arrivals in a multiple signal environment. The effect of estimating the spatial correlations while the array is moving is studied in terms of the decorrelation it produces, the change it causes in the eigenvalues of the correlation matrix, and the improvements obtained in the measured spectrum. Cases of both fixed and varying angle of arrival are investigated, The former arises with distant sources and will, with a sufficiently long estimation interval, emulate uncorrelated sources and given correspondingly sharp spectra. The latter arises with nearby sources and will allow them to be distinguished but will be attended by spectral shift and broadening, and loss of resolution. It is shown that meaningful estimates of the arrival angles can nevertheless be made. Specific illustrations are worked out using a seven-element, sparse, nonuniformly spaced linear array utilizing the well-known superresolution spectral estimators-the maximum likelihood (ML) method, the method of linear prediction (LP), and the method of multiple signal classification (MUSIC).     

PULSE CUMULATING METHOD FOR MULTI-TARGETS’ JOINT AZIMUTH-ELEVATION FREQUENCY-DELAY ESTIMATION

The Directions of Arrivals （DOAs）, speeds and distances of targets are all required for array signal processing. Based on the periodic phase shift of coherent pulse sequence waveform, a new estimation of multi-targets＇ 2-Dimentional （2-D） DOA angle, Doppler frequency shift and relative time-delay is proposed. Based on a virtual sensor array constructed by pulse cumulating, the estinaations of azimuth, elevation, Doppler frequency shift and time-delay can be obtained simultaneously, and the least number of pulses could be two. This method is computationally efficient even in heavier noised environment, and all estimations are automatically paired in calculation process with no used to any plane sensor array and deal with many spectrum searching. Further more, this algorithm can be targets at the same time only by few sensors. The targets number that can deal with simultaneously is several times to the sensor number, which is the upper limit for normal algorithms such as ESPRIT and MUSIC. These characteristics would be very useful, especially, for aerial systems. Simulations demonstrate the capabilities of this method efficiently.     

相干信号源的空时三维参数分离估计方法

文中提出了一种宽频段窄带相干信号源的频率和二维波达方向估计的新方法。该方法利用L型阵列并结合一定的时域信息,将相干源的三维参数估计问题转化为3个一维问题,并在每一维使用空间平滑方法和ESPR IT算法求解相应参数,最后通过求解联立方程,获得相干信号的三维参数。因此,避免了谱峰搜索,并且算法本身的并行处理能力,提高了测向系统的实时性。计算机仿真结果表明了该算法的有效性。