用平行四边形阵列实现闭环形式2维角估计

提出了适用于平行四边形阵列的２维酉ＥＳＰＲＩＴ方法,它是一种闭环形式的高分辨算法,对信号源方位角和仰角估计实现自动配对。给出了两类酉变换矩阵,将复数域的矩阵运算转换到实数域。除了初始变换和最后维数等于信号个数的矩阵特征分解外,整个过程都采用高效的实值计算。最后对算法做了一阶近似渐进性能分析。仿真结果表明算法是有效的。     

FCA-ESPRIT: a closed-form 2-D angle estimation algorithm for filledcircular arrays with arbitrary sampling lattices

This article addresses the simultaneous estimation of the azimuth and elevation angles of multiple co-channel signals incident upon an array of antennas. A new closed-form algorithm that is applicable with filled circular arrays (FCAs) is presented. The algorithm, which is called FCA-ESPRIT, is applicable with any FCA geometry, e.g., FCAs constructed using rectangular, hexagonal, polar, or random sampling lattices. The only constraint imposed on the FCA geometry is that the spacing between adjacent sensors should be half a wavelength or less on average across the entire aperture. The algorithm provides automatically paired azimuth and elevation angle estimates by solving a set of ESPRIT-like equations wherein the unknowns have the form sin(&thetas; _i)e^jφ(i) (where &thetas;_i and φ _i are the elevation and azimuth angles of the ith source, respectively). The algorithm provides arrival angle estimates via a closed-form procedure-it does not require computationally expensive search or optimization procedures     

Closed-form 2-D angle estimation with rectangular arrays in elementspace or beamspace via unitary ESPRIT

The UCA-ESPRIT is a closed-form algorithm developed for use in conjunction with a uniform circular array (UCA) that provides automatically paired source azimuth and elevation angle estimates. The 2-D unitary ESPRIT is presented as an algorithm providing the same capabilities for a uniform rectangular array (URA). In the final stage of the algorithm, the real and imaginary parts of the ith eigenvalue of a matrix are one-to-one related to the respective direction cosines of the ith source relative to the two major array axes. The 2-D unitary ESPRIT offers a number of advantages over other proposed ESPRIT based closed-form 2-D angle estimation techniques. First, except for the final eigenvalue decomposition of a dimension equal to the number of sources, it is efficiently formulated in terms of real-valued computation throughout. Second, it is amenable to efficient beamspace implementations that are presented. Third, it is applicable to array configurations that do not exhibit identical subarrays, e.g., two orthogonal linear arrays. Finally, the 2-D unitary ESPRIT easily handles sources having one member of the spatial frequency coordinate pair in common. Simulation results are presented verifying the efficacy of the method     

Computationally efficient 2-D DOA estimation for uniform rectangular arrays

A computationally efficient two-dimensional (2-D) direction-of-arrival (DOA) estimation method for uniform rectangular arrays is presented. A preprocessing transformation matrix is first introduced, which transforms both the complex-valued covariance matrix and the complex-valued search vector into real-valued ones. Then the 2-D DOA estimation problem is decoupled into two successive real-valued one-dimensional (1-D) DOA estimation problems with real-valued computations only. All these measures lead to significantly reduced computational complexity for the proposed method.     

Real-time frequency and 2-D angle estimation with sub-Nyquistspatio-temporal sampling

An algorithm is presented for real-time estimation of the frequency and azimuth and elevation angles of each signal incident on an airborne antenna array system over a very wide frequency band (2-18 GHz) commensurate with electronic signal warfare. The algorithm provides unambiguous frequency estimation despite severe temporal undersampling necessitated by cost/complexity of hardware considerations. The 2-18 GHz spectrum is decomposed into 1-GHz bands. The baseband output of each antenna is sent through two 250-MHz sampled channels where one is delayed relative to the other (prior to sampling) by 0.5 ns, which is the Nyquist interval for a 1-GHz bandwidth. Due to the high variance of the Direct ESPRIT frequency estimator, aliased frequencies are estimated via a simple formula and translated to the proper aliasing zone, utilizing eigenvector information generated by PRO-ESPRIT. The algorithm also provides unambigous 2-D angle estimate over the entire 2-18 GHz bandwidth, despite severe spatial undersampling at the higher end of this band necessitated by mutual coupling considerations and resolving power requirements at the lower end of the band. Eigenvector information generated by PRO-ESPRTT is used to facilitate computationally simple estimation of azimuth and elevation angles that are automatically paired with corresponding frequency estimates despite aliasing. Simulations are presented demonstrating the capabilities of the algorithm     

基于伪数据矩阵的二维自动配对角度估计方法

针对多窄带远场信号的无配对问题,提出了一种用L阵进行二维波达方向估计方法.此方法利用时间信息构造具有相同"伪信号"信息的伪数据矩阵来达到自动配对的目的.利用时间信息可以有效消除噪声影响,但是矩阵的构造与同样利用时间信息的辅助变量法是不同的,因此,所提方法具有阵列扩展的能力.仿真试验充分说明了该方法在精度估计、成功配对检测概率、多非相关信号源的估计能力方面都表现出优越的性能.     

Unitary spherical esprit: 2-d angle estimation with spherical arrays for scalar fields

The authors consider the problem of two-dimensional (2-D) direction-of-arrival estimation of multiple plane waves incident on a spherical array. We propose a novel subspace technique that provides automatically paired source azimuth and elevation estimates relying on a spherical phase-mode excitation approach. The algorithm is remarkable for the low computational complexity and enhanced performance in correlated source scenarios by relying on a real beamspace approach, which allows forward?backward averaging. Moreover, the technique yields very accurate estimates by including spherical phase modes of different orders. This is demonstrated by comparing the mean error of the angle estimates obtained by spherical ESPRIT and the corresponding Cramer Rao bounds.     

均匀圆阵二维波达角估计的Cramer-Rao界

均匀圆阵(UCA)是一种应用广泛的具有二位波达角估计能力的平面阵列。为了从理论上分析不同阵列参数下到达波方位角(AOA)、仰角估计精度,推导了均匀圆阵二维波达角估计的性能界,以此为基础分析了阵列孔径、阵元个数、快拍数以及来波仰角高低与到达角估计精度的关系,并通过对UCA-MUSIC算法计算机仿真验证了推导结果的正确性。研究结果为波达角估计类算法提供了可供参考的性能下界,圆阵设计时也不再需要大量的Monte Carlo仿真试验确定阵列参数,可直接从估计精度表达式中获得。     

2-D SPATIAL-SPECTRUM ESTIMATION FORWIDE-BAND SOURCES BASED ON INTERPOLATED CIRCULAR ARRAYS

In array signal processing, 2-D spatial-spectrum estimation is required to determine DOA of multiple signals. The circular array of sensors is found to possess several nice properties for DOA estimation of wide-band sources. C. U. Padmini, et al.(1994) had suggested that the frequency-direction ambiguity in azimuth estimation of wide-baud signals received by a uniform linear array (ULA) can be avoided by using a circular array, even without the use of any delay elements. In 2-D spatial-spectrum estimation for wide-band signals, the authors find that it is impossible to avoid the ambiguity in source frequency-elevation angle pairs using a circular array. In this paper, interpolated circular arrays are used to perform 2-D spatial-spectrum estimation for wide-band sources. In the estimation, a large aperture circular array (Υ>λmin/2) is found to possess superior resolution capability and robustness.     

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。     

三平行线阵改进传播算子算法的波达方向估计

在三平行立体线阵中,传统二维传播算子(Propagator Method,PM)算法进行传播算子估计时,根据划分子阵直接构造的信号协方差矩阵存在较大冗余度.为了降低运算量,可以通过子阵合并的方式,摒弃协方差矩阵的冗余数据,利用重构的协方差矩阵估算传播算子,然后构造新的传播算子,得到与二维波达方向(direction of arrival,DOA)相关的三维超定方程组,再引入非线性最小二乘法处理该方程组求解得二维DOA信息.仿真结果表明,该算法降低了运算量,提高了二维DOA估计的精度.     

On-die diffractive alignment structures for packaging of microlens arrays with 2-D optoelectronic device arrays

A novel technique for aligning a microlens array to an electrically packaged optoelectronic device array is presented: reflective Fresnel zone plates (FZP's) are fabricated on the device die to provide registration spots during alignment. A proof-of-concept experiment in which an MSM array was aligned to a microlens array with an accuracy of better than 9 microns is described.     

Recursive partial realization for 2-D data arrays

In this paper an attempt is made to provide a proper formalization to the partial realization problem for discrete linear causal shift invariant 2-D systems. The approach falls into the class of 2-D Padé approximations; the results, however, are new, since the rational representation matches all the samples of a 2-D partial sequence. The realization algorithm, though characterized by a high complexity, exhibits a recursive structure and allows for a good computational economy.     

Joint angle and delay estimation using shift-invariance techniques

In a multipath communication scenario, it is often relevant to estimate the directions and relative delays of each multipath ray. We derive a closed-form subspace-based method for the simultaneous estimation of these parameters from an estimated channel impulse response, using knowledge of the transmitted pulse shape function. The algorithm uses a two-dimensional (2-D) ESPRIT-like shift-invariance technique to separate and estimate the phase shifts due to delay and direction of incidence with automatic pairing of the two parameter sets. Improved resolution is obtained by enlarging the data matrix with shifted and conjugated copies of itself     

Joint-block-sparsity for efficient 2-D DOA estimation with multiple separable observations

In sparsity-based optimization problems, one of the major issue is computational complexity, especially when the unknown signal is represented in multi-dimensions such as in the problem of 2-D (azimuth and elevation) direction-of-arrival (DOA) estimation. In order to cope with this issue, this paper introduces a new sparsity structure that can be used to model the optimization problem in case of multiple data snapshots and multiple separable observations where the dictionary can be decomposed into two parts: azimuth and elevation dictionaries. The proposed sparsity structure is called joint-block-sparsity which enforces the sparsity in multiple dimensions, namely azimuth, elevation and data snapshots. In order to model the joint-block-sparsity in the optimization problem, triple mixed norms are used. In the simulations, the proposed method is compared with both sparsity-based techniques and subspace-based methods as well as the Cramer–Rao lower bound. It is shown that the proposed method effectively solves the 2-D DOA estimation problem with significantly low complexity and sufficient accuracy.

     

A new algorithm for 2-D DOA estimation

In this paper we present a new algorithm to estimate the 2-D direction of arrival (DOA) of narrowband sources lying in the far field of the array. The array consists of matched co-directional triplets, and can be considered as an extension of the 1-D ESPRIT scenario to 2-D. The proposed approach is simple and direct and does not require a search procedure or initialization. Existing algorithms require a search to match the correct elevation and azimuth angles and are computationally more expensive. This technique automatically pairs the azimuth and elevation angles by marking them. The computational complexity is twice that of 1-D ESPRIT. Simulation results and comparisons with other existing algorithms are presented to demonstrate the performance of the proposed technique.     

New fast algorithm for 2-D Angle-Of-Arrival estimation

Based on propagator method, a fast 2-D Angle-Of-Arrival （AOA） algorithm is proposed in this paper. The proposed algorithm does not need the Eigen-Value Decomposition （EVD） or Singular Value Decomposition （SVD） of the Sample Covariance Matrix （SCM）, thus the fast algorithm has lower computational complexity with insignificant performance degradation when comparing with conventional subspace approaches. Furthermore, the proposed algorithm has no performance degradation. Finally, computer simulations verify the effectiveness of the proposed algorithm.     

Noncausal 2-D spectrum estimation for direction finding

A two-dimensional noncausal autoregressive (NCAR) plus additive noise model-based spectrum estimation method is presented for planar array data typical of signals encountered in array processing applications. Since the likelihood function for NCAR plus noise data is nonlinear in the model parameters and is further complicated by the unknown variance of the additive noise, computationally intensive gradient search algorithms are required for computing the estimates. If a doubly periodic lattice is assumed, the complexity of the approximate maximum likelihood (ML) equation is significantly reduced without destroying the theoretical asymptotic properties of the estimates and degrading the observed accuracy of the estimated spectra. Initial conditions for starting the approximate ML computation are suggested. Experimental results that can be used to evaluate the signal-plus-noise approach and compare its performance to those of signal-only methods are presented for Gaussian and simulated planar array data. Statistics of estimated spectrum parameters are given, and estimated spectra for signals with close spatial frequencies are shown. The approximate ML parameter estimate's asymptotic properties, such as consistency and normality, are established, and lower bounds for the estimate's errors are derived, assuming that the data are Gaussian     

Path diversity reception employing steering vector arrays andsequence estimation techniques for ISI channels

We propose a path diversity reception technique that uses steering vector arrays and Viterbi algorithm-based sequence estimation techniques to cope with severe intersymbol interference (ISI). The proposed scheme suppresses some delayed paths with spatial and temporal processing based on the single constraint sample matrix inversion algorithm to reduce excess ISI for sequence estimation. The path diversity branches are weighted in proportion to the quality of the array output signals and then combined via the branch-metric-combining (BMC) Viterbi algorithm to estimate the most likely transmitted sequence. Maximum likelihood sequence estimation, limited-state sequence estimation, and decision-feedback sequence estimation are examined for their suitability as estimation techniques. Consequently, the proposed scheme is sufficient for managing various kinds of channel models. Thus, the proposed scheme is suitable for high-speed time-division multiple access (TDMA) mobile radio systems, because, in this kind of transmission, fading can be presumed to be nearly quasi-static during the burst, and the delayed paths are spread over several symbols