均匀圆阵下的宽带信号DOA估计算法

为了解决传统宽带信号DOA估计在全频段作谱峰搜索所得空间谱分辨率较低和计算量非常大的问题,新算法采用FFT变换,仅仅通过采用选取的部分频带数据进行基于子空间的空间谱估计,不仅可以提高宽带信号DOA估计的分辨率,同时减少了运算量。文章介绍了算法实现过程,并对算法计算量进行了定量分析,分辨率和误差性能则通过仿真进行比较分析。另外,算法以均匀圆阵为模型,相对于线阵结构,使所得结论更加具有实用性。     

均匀圆阵多宽带LFM信号的二维DOA估计

针对均匀圆阵（UCA）,根据不同线性调频（LFM）信号在对应阶次上的分数阶傅里叶变换（FRFT）域具有能量聚集性的特点,将不同时频特性LFM信号在FRFT域分离成一系列平稳单频信号,构造出FRFT域上新的空时频分布模型数据,结合MUSIC算法,提出了一种新的均匀圆阵多宽带LFM信号的二维DOA估计。通过仿真实验验证了该方法的有效性。     

基于均匀圆阵的相干信源DOA估计算法研究

针对均匀圆阵相干信源的波达方向估计问题,提出了一种去相干的正交预处理方法——阵列移位算法。阵列移位算法改进了抗相干干扰的波束形成方法,通过圆阵移位和MUSIC算法的结合,使相干信源角估计的性能得到改善。与传统的模式空间平滑算法相比,该方法减少了阵列孔径损失,提高了计算速度。     

基于空频解耦的宽带DOA估计算法

宽带波达方向(DOA)估计是宽带阵列信号处理领域的热点问题,当宽带信号的距离分辨率与宽带孔径可比拟时,孔径渡越效应会成为影响宽带波达方向估计精确度的重要因素。基于宽带阵列信号在空域与频域间呈现线性耦合的特点,利用梯形变换进行解耦处理,并对解耦后数据相干积累进行 DOA估计。实验结果表明,通过对宽带孔径渡越效应的消除,宽带 DOA估计精确度显著提高。该算法具有较低的计算复杂度和较高的 DOA估计精确度,是一种有效的宽带 DOA估计算法。     

基于均匀圆阵的信号源DOA和多谱勒频率估计算法

本文研究均匀圆形阵列的信号处理问题,提出了一种同时估计空间非相关信号源方位角、俯仰角和多谱勒频率的算法,该方法对均匀圆形阵列的输出信号进行模式激励,使其阵列流形具有类似于均匀线性阵列的形式;在此基础上,特征分解构造的波达矩阵,由特征值获得各信号的多谱勒频率,由各特征对应的特征向量处理得到对应信号的到达方向,该方法不需进行谱峰搜索,运算量小,能实现信号的方位角、俯仰角和多普勒频率的自动配对,且具有相当高的分辨率,给出的计算机仿真结果证实了该方法的有效性。     

未知信源数目的MUSIC算法研究

针对MUSIC算法需要预先确定信号源数目的应用前提，分析了信源数目过估计与欠估计情况下的MUSIC算法性能，提出一种改进算法，仿真结果证明在信源数目有误差的情况下该算法的性能良好。     

基于数据阵共扼重构的宽带相干源DOA估计算法

提出了一种基于阵列接收数据阵共扼重构的宽带源DOA估计方法。该算法在保持原ISM算法无需构造复杂聚焦阵的基础上，取前后向平滑的特例——子阵长度与阵元数相等，在每一子带对接收数据阵进行共扼重构，在不损失阵列孔径的前提下实现了相干源的DOA估计，并可提高对非相干源的估计性能。仿真结果验证了新方法的有效性。     

宽带相干信源波达方向估计(DOA)的新算法

辅助方向向量增加(ADVA)聚焦算法是非归一化的,存在聚焦损失。双边相关变换(TCT)聚焦算法是归一化的,不存在聚焦损失,但需要对目标的方位进行预估计。这不仅会使运算复杂,而且得到的聚焦矩阵也只是在预估角度上有最小范数解,在其他方向上则会产生偏离,因此不是稳健的。提出了一种在归一化的条件下,不需要方位预估计的、稳健的聚焦矩阵算法,算法的思想是将整个感兴趣的空间分成组,对每一组在归一化约束的条件下利用奇异值分解法求解最小化问题。通过仿真验证了该算法的有效性。     

基于最优子阵划分ESPRIT的任意线阵高精度DOA估计算法

为了提高任意阵列的波达方向(direction of arrival, DOA)估计性能,从对子阵阵元选取进行优化的角度出发,提出了基于最优子阵划分旋转不变信号参数估计技术(estimation of signal parameters via rotational invariance techniques,ESPR...     

基于四阶累积量扩展孔径的宽带信源测向算法

当阵列过载时,常用高分辨测向算法将会失效.针对此问题,提出了一种新的宽带信源测向算法.该算法利用基于最小冗余直线阵列的四阶累积量来扩展阵列孔径.将得到的四阶累积量去除冗余信息后,构造了一新的Toeplitz矩阵.新矩阵充分利用了原协方差矩阵的信息,避免了冗余信息.通过理论分析和计算机仿真,对扩展后阵列孔径、测向性能、检测概率及可分辨信源数进行了对比研究.结果表明,相比相同阵元数的最小冗余直线阵和均匀直线阵,该算法具有大得多的阵列孔径和更高的分辨率,利用M阵元,最多可以分辨M²-M个信源.     

An analysis of wideband direction-of-arrival estimation for closely-spaced sources in the presence of array model errors

This letter presents an analysis of wideband direction-of-arrival (DOA) estimation for closely-spaced sources using arbitrary antenna array taking into account the effect of array model error, which is important issue in practical implementation. Based on this analysis, a new wideband DOA estimation method without array calibration is then developed to deal with the effects of array errors. The performance improvement of the proposed method in the presence of array errors is shown in simulation results.     

Performance analysis of higher order ESPRIT for localization ofnear-field sources

Most existing array processing techniques for estimating the directions of arrival (DOAs) or signal copy rely heavily on the plane-wave assumption of far-field sources. When the sources are located relatively close to the array, these techniques may no longer perform satisfactorily. In this paper we present an asymptotic performance analysis of an ESPRIT-like method for passive localization of nearfield sources. The algorithm, which is based on fourth-order cumulants, is formulated for observations collected from a single uniformly spaced linear array. We examine the least-squares version of the algorithm and derive the expressions for the asymptotic variance of the estimated DOAs (relative to a reference sensor) and estimated ranges of the sources. We also derive an algorithm independent bound on the asymptotic variance of the estimated parameters. This bound can be used as a measure against the theoretically predicted algorithmic performance. Some insight into the achievable performance of this algorithm is obtained by numerical evaluation of the bound for several test cases of interest, and the results are compared with those obtained by numerical evaluation of the theoretically predicted performance. Monte Carlo simulations are used to verify the theoretical analysis     

一种宽频带共形天线的特性研究

设计了一种具有宽频带特性的柱面共形天线,通过改变柱体曲率半径、长度和介电常数等参数,详细分析了其变化对共形天线性能的影响。结果表明:柱体各个参数的变化会导致天线的谐振频率、阻抗带宽以及辐射特性发生显著的改变。对设计宽频带共形天线时共形载体的选取提供了可靠依据。实际加工制作了天线,测量结果表明:该天线具有宽频带特性,可用频段覆盖2~16 GHz,在工作频段内具有较好的辐射特性,增益稳定。     

DOA estimation of wideband sources using a harmonic source modeland uniform linear array

We consider the problem of estimation of the DOAs of multiple wideband sources incident on a uniform linear array (ULA) in the presence of spatially and temporally white Gaussian noise (WGN). The approach presented builds up on the IQML algorithm suggested by Bresler and Macovski (1986) for the case of narrowband DOA estimation. It is shown that the concept of an ARMA model for the observed data vector for the narrowband case can be generalized to model an appropriately stacked, space-time data vector obtained by combining the space-time samples. The coefficients of the corresponding 2-D predictor polynomial can be used to represent the null subspace of the wideband array steering matrix, and rooting of the polynomial at each frequency, separately, gives the DOA estimates. These separate estimates at multiple frequencies are combined into a single DOA estimate in a least squares sense. This leads to the formulation of an IQML like procedure for the spatial parameter estimation of wideband sources. Like its narrowband counterpart, the proposed approach is applicable to both noncoherent and coherent sources. The performance of the proposed method is studied via extensive computer simulations and by comparison with the Cramer-Rao bounds     

A generalized capon estimator for localization of multiple spread sources

In this correspondence, we develop a generalized Capon spatial spectrum estimator for localization of multiple incoherently distributed (spread) sources in sensor arrays. The proposed generalized Capon technique estimates the source central angles and angular spreads by means of a two-dimensional (2-D) parameter search. Simulation results show that the proposed method has a substantially improved performance compared with several popular spread source localization methods.     

Near-field multiple source localization by passive sensor array

The localization of multiple near-field sources in a spatially white Gaussian noise environment is studied. A modified two-dimensional (2-D) version of the multiple signal classification (MUSIC) algorithm is used to localize the signal sources; range and bearing. A global-optimum maximum likelihood searching approach to localize these sources is discussed. It is shown that in the single source situation, the covariances of both the 2-D MUSIC estimator and the maximum likelihood estimator (MLE) approach the Cramer-Rao lower bound as the number of snapshots increases to infinity. In the multiple source situation, it is observed that for a high signal-to-noise ratio (SNR) and a large number of snapshots, the root mean square errors (RMSEs) of both localization techniques are relatively small. However, for low SNR and/or small number of snapshots, the performance of the MLE is much superior that of the modified 2-D MUSIC     

Performance enhancement of a compact wideband patch antenna array using EBG structures

In this paper, a compact wideband linear microstrip phased array antenna (MPAA) is proposed. To reduce the size of MPAA, a compact wideband aperture coupled microstrip patch antenna (MPA) is utilized as array element. Size reduction of the array element is performed through incorporating an interdigital capacitor (IDC) in the patch and a metamaterial (MTM) unit cell close to slot in the ground plane of the antenna. By cutting two vertical slits from the slot, further compacting of the slot in the ground plane of array element is obtained. By this technique dimensions of the patch and slot are reduced by 12.9% and 12.2%, respectively. Furthermore, dimensions of the MPAA are reduced through decreasing the spacing between array elements causing the antenna performance degradation. To overcome this shortage and improve the radiation characteristics of the proposed MPAA, an electromagnetic bandgap structure (EBG) is utilized. The effect of implementing EBG cells on the reflection coefficient of the elements in the MPAA during beam scanning is studied in details. The maximum measured gain, bandwidth and cross-polarization level of the fabricated MPAA are 13.3 dBi, 24.4% and −40 dB, respectively making it a good candidate for monopulse tracking radar applications. The measurement results confirm the simulation results.     

Off-grid direction-of-arrival estimation for wideband noncircular sources

Researchers have recently shown an increased interest in estimating the direction-of-arrival (DOA) of wideband noncircular sources, but existing studies have been restricted to subspace-based methods. An off-grid sparse recovery-based algorithm is proposed in this paper to improve the accuracy of existing algorithms in low signal-to-noise ratio situations. The covariance and pseudo covariance matrices can be jointly represented subject to block sparsity constraints by taking advantage of the joint sparsity between signal components and bias. Furthermore, the estimation problem is transformed into a single measurement vector problem utilizing the focused operation, resulting in a significant reduction in computational complexity. The proposed algorithm's error threshold and the Cramer–Rao bound for wideband noncircular DOA estimation are deduced in detail. The proposed algorithm's effectiveness and feasibility are demonstrated by simulation results.     

The potential performance gain in using spectral information inpassive detection/localization of wideband sources

We address the problem of detecting the presence of wideband point sources and/or estimating their location using data collected by an array of sensors. This passive localization problem is typical to applications where the radiated signals do not carry information and are of no interest. However, knowledge of their waveshape, or their cross spectral matrix, is essential for applying optimal/sub-optimal detection/localization algorithms. In this paper, we present results of a study in which we compare the optimal procedures for detection/localization and their performance to suboptimal procedures that use no spectral information or only partial spectral information. We show that if the number of sensors in the array is larger than the number of sources to be localized (or detected), then the performance gain of the optimal procedures is potentially significant mainly in conditions of small separation and/or high correlation between sources. The performance gain is also a function of the spectrum: it is potentially higher if the sources are known to be correlated and if their spectra is not smooth. If, however, the number of sources is smaller than the number of sensors, then the role of the spectral information in improving detection/localization performance becomes major: only the use of spectral prior enables reliable localization of more sources than sensors     

DOA ESTIMATION FOR WIDEBAND SOURCES BASED ON UCA

A new Direction Of Arrival （DOA） estimation algorithm for wideband sources based on Uniform Circular Array （UCA） is presented via analyzing widcband performance of the general ESPRIT. The algorithm effectively improves the wideband performance of ESPRIT based on the interpolation principium and UCA-ESPRIT. The simulated results by computer demonstrate its efficiency.