Accurate direction‐of‐arrival estimation of multiple sources using a genetic approach

In this paper, we present an accurate direction‐of‐arrival (DOA) estimation method, which is based on the maximum likelihood (ML) principle and implemented using a modified and refined genetic algorithm (GA). With the newly introduced features—intelligent initialization and the emperor‐selective (EMS) mating scheme, carefully selected crossover and mutation operators and fine‐tuned parameters such as the population size, the probability of crossover and mutation etc., the GA‐ML estimator achieves fast global convergence. A GA operator and parameter standard is suggested for this application, which is independent of the source and array configurations except the number of sources. Simulation results demonstrate that in general scenarios, the proposed estimator is the most efficient in computation and its statistical performance is the best among all popular ML‐based DOA estimation methods. Copyright © 2004 John Wiley & Sons, Ltd.     

Computationally Efficient 2‐D DOA Estimation Using Two Parallel Uniform Linear Arrays

new computationally efficient algorithm‐based propagator method for two‐dimensional (2‐D) direction‐of‐arrival (DOA) estimation is proposed, which uses two parallel uniform linear arrays. The algorithm takes advantage of the special structure of the array which enables 2‐D DOA estimation without pair matching. Simulation results show that the proposed algorithm achieves very accurate estimation at a computational cost 4 dB lower than that of standard methods.     

Efficiency Evaluation of the Unconditional Maximum Likelihood Estimator for Near‐Field DOA Estimation

In this paper, we address the problem of closely spaced source localization using sensor array processing. In particular, the performance efficiency (measured in terms of the root mean square error) of the unconditional maximum likelihood (UML) algorithm for estimating the direction of arrival (DOA) of near‐field sources is evaluated. Four parameters are considered in this evaluation: angular separation among sources, signal‐to‐noise ratio (SNR), number of snapshots, and number of sources (multiple sources). Simulations are conducted to illustrate the UML performance to compute the DOA of sources in the near‐field. Finally, results are also presented that compare the performance of the UML DOA estimator with the existing multiple signal classification approach. The results show the capability of the UML estimator for estimating the DOA when the angular separation is taken into account as a critical parameter. These results are consistent in both low SNR and multiple‐source scenarios.     

基于高阶累积量的近场通信波达方向估计算法

通过对近场通信波达方向准确估计,提高目标信源的定位能力.传统方法中对近场源通信信源的波达方向估计采用多普勒估计方法,由于近场通信的空间信源为窄带信号,多普勒估计会导致DOA估计频谱失真.提出一种基于高阶累积量的近场通信波达方向估计算法.采用均匀间隔线列阵构建近场通信的信号模型,进行近场源目标特征构建,提取近场源通信信号的斜度和峰度等特征,采用高阶累积量特征提取方法,分别求得对应近场通信信源的方位角、频率和距离三维参数,使得每个信源的参数自动配对,提高了近场通信DOA波达方向估计的效率和精度,实现近场源通信信号的波达方向估计算法改进.仿真实验结果表明,采用该方法进行近场方法波达方向估计的精度较高,对信源方位的定位准确,性能优越于传统方法,在近场通信中具有较好的应用价值.     

基于MUSIC 算法的圆阵 DOA 估计技术及改进方法

介绍了基于MUSIC算法的圆阵到达方向（DOA）估计技术,即将均匀圆阵接收数据的协方差矩阵进行特征分解,把观测数据划分为信号子空间与噪声子空间,并利用2个空间的正交性构造出＂针状＂空间谱峰,进行信号源DOA估计;针对小信噪比和小快拍数情况下,常规 M USIC算法对入射角度相近的信号源的分辨率严重下降的问题,利用谱函数极大值点对方位角和仰角的二阶导数小于零的特性,通过对方位角和俯仰角求二阶偏导数,提出了新的空间谱函数的方法。     

DOA Estimation for Multiple Sparse Sources with Arbitrarily Arranged Multiple Sensors

This paper proposes a method for estimating the direction of arrival (DOA) of multiple source signals for an underdetermined situation, where the number of sources N exceeds the number of sensors M (M < N). Some DOA estimation methods have already been proposed for underdetermined cases. However, since most of them restrict their microphone array arrangements, their DOA estimation ability is limited to a 2-dimensional plane. To deal with an underdetermined case where sources are distributed arbitrarily, we propose a method that can employ a 2- or 3-dimensional sensor array. Our new method employs the source sparseness assumption to handle an underdetermined case. Our formulation with the sensor coordinate vectors allows us to employ arbitrarily arranged sensors easily. We obtained promising experimental results for 2-dimensionally distributed sensors and sources 3×4, 3×5 (#sensors × #speech sources), and for 3-dimensional case with 4×5 in a room (reverberation time (RT) of 120 ms). We also investigate the DOA estimation performance under several reverberant conditions.     

Acoustic emission source location in dispersive media

In this paper, the acoustic emission source (AE) is located by a non-iterative method using the time-of-arrival (TOA) of several events, received in an array of sensors arbitrary positioning in the 3D space. If at least two event velocities are different, a common property in dispersive propagation, and the array of sensors is not lying in a plane, a close-form estimation of the source–sensors distances, AE time and material constant is derived. Moreover, a direct estimation of the source position is achieved using the multidimensional scaling approach. In simulation experiments, the proposed method detects accurately the location of AE sources, reducing also the ambiguity introduced by noisy arrival times.     

二维相干信号波达方向判断空间平滑算法

波达方向估计是智能天线的重要功能之一,对于相干信号角度模糊问题通常严重影响了方向判断的精准度.文中根据一维空间平滑基本理论和算法,对二维六边形阵列相干信号MUSIC算法波达方向估计问题进行了理论分析和仿真实验,提出了平面六边形阵列到十字形阵列的变换方法,成功地把一维平滑技术应用到平面六边形阵列,仿真表明,这种变换可以有效地消除相干信号的角度模糊问题.     

超宽带信号DOA的估计方法

对信号到达角(DOA)的估计是超宽带定位的关键技术之一.传统的到达角估计方法都基于窄带信号,已不能直接应用在超宽带场合,因此提出了一种基于频域模型的宽带子空间谱估计方法.仿真结果表明,该方法能准确估计超宽带信号的到达角.     

基于压缩感知DOA估计的稀疏阵列设计

根据格拉姆(Gram)矩阵优化测量矩阵的方法,给出了一种基于压缩感知波达方向(DOA)估计的均匀线阵的稀疏阵列设计方法.该方法不需要对阵列的输出数据进行压缩采样,直接利用稀疏阵列的输出数据,然后利用稀疏恢复算法求解DOA估计信息.实验仿真证明,相比于原均匀线阵,所提方法在阵元数目较少且信噪比较低的情况下具有更好的DOA估计性能.     

Performance of a MANET directional MAC protocol with angle‐of‐arrival estimation

The use of directional antennas in mobile ad hoc networks (MANETs) has shown to offer large throughput gains relative to omnidirectional antennas. When used in ad hoc networks, directional medium‐access‐control (DMAC) protocols usually require all nodes, or part of nodes, to be aware of their exact locations. This location information is typically provided using a global positioning system (GPS). Although GPS systems are designed to be as nearly accurate as possible, there are still estimation errors that can cause a relatively large deviation from the actual GPS receiver position. In this paper, we investigate the effect of inaccurate node position estimation on the throughput of these protocols. Our results clearly indicate that the advantages of DMAC protocols diminish if the available position information is not accurate enough. As an alternative, we propose an efficient DMAC protocol that utilizes signal parameter estimation via the rotational invariance technique (ESPRIT) for direction‐of‐arrival (DOA) estimation; alleviating the need for GPS and, hence, avoiding the degrading associated with typical GPS position estimation errors. Moreover, unlike GPS‐based protocols, our protocol is suitable for both outdoor and indoor applications. Under different operating conditions and channel models, our simulation results show the throughput improvement achieved using the proposed protocol relative to the IEEE 802.11. Copyright © 2007 John Wiley & Sons, Ltd.     

基于Y形阵的空时二维波达方向估计

提出了一种适用于Y形阵的空时二维波达方向估计方法,在低信噪比下实现了无模糊的二维波达方向估计。该方法利用了Y形阵的特性,具有较好的稳定性和较小的估计方差。仿真结果证明了本方法的有效性。     

Off‐grid DoA estimation method of wideband signals

In this paper, an off‐grid direction of arrival (DoA) estimation method is proposed for wideband signals. This method is based on the sparse representation (SR) of the array covariance matrix. Similar to the time domain DoA estimation methods, the correlation function of the sources was assumed to be the same and known. A new measurement vector is obtained using the lower‐left triangular elements of the covariance matrix. The DoAs are estimated by quantizing the entire range of continuous angle space into discrete grid points. However, the exact DoAs may be located between two grid points; therefore, this estimation has errors. The accuracy of DoA estimation is improved by the minimization of the difference between the new measurement vector and its estimated values. Simulation results revealed that the proposed method can enhance the DoA estimation accuracy of wideband signals.     

Collision‐interference cancellation for space‐based AIS using beam synthesis technology with optimal sparse linear array

A basic problem in the space‐based automatic identification system (AIS) is the low probability of detecting messages because ships' messages arrive at the receiver in the same time slot. In this study, sparse linear array optimal beam synthesis (SLA–OBS) technology is proposed to improve the capture ability of AIS messages by forming a narrow beam pattern that points in the direction of the desired AIS messages. To capture the desired signal within the narrow beam pattern, the directions of arrival (DOA) and the number of sources from ships are first estimated. Then, the ideal narrow beam pattern and minimal number of array elements are achieved synchronously with the CPLEX optimal tool. The simulations show that the message detection probability with the proposed method is greater than 95%, even when the situations are very serious, whereas the number of sparse linear antennas is small (no more than six). Copyright © 2015 John Wiley & Sons, Ltd.     

Improved TOA‐Based Localization Method with BS Selection Scheme for Wireless Sensor Networks

The purpose of a localization system is to estimate the coordinates of the geographic location of a mobile device. The accuracy of wireless localization is influenced by non‐line‐of‐sight (NLOS) errors in wireless sensor networks. In this paper, we present an improved time of arrival (TOA)–based localization method for wireless sensor networks. TOA‐based localization estimates the geographic location of a mobile device using the distances between a mobile station (MS) and three or more base stations (BSs). However, each of the NLOS errors along a distance measured from an MS (device) to a BS (device) is different because of dissimilar obstacles in the direct signal path between the two devices. To accurately estimate the geographic location of a mobile device in TOA‐based localization, we propose an optimized localization method with a BS selection scheme that selects three measured distances that contain a relatively small number of NLOS errors, in this paper. Performance evaluations are presented, and the experimental results are validated through comparisons of various localization methods with the proposed method.     

A Low‐Complexity Planar Antenna Array for Wireless Communication Applications: Robust Source Localization in Impulsive Noise

This paper proposes robust source localization methods for estimating the azimuth angle, elevation angle, velocity, and range using a low‐complexity planar antenna array in impulsive non‐Gaussian noise environments. The proposed robust source localization methods for wireless communication applications are based on nonlinear M‐estimation provided from Huber and Hampel. Simulation results show the robustness performance of the proposed robust methods in impulsive non‐Gaussian noise.     

Three-dimensional source localization in a waveguide

This paper deals with three-dimensional (3-D) passive localization of a narrowband point source in a 2½-dimensional waveguide using an array of sensors. Two different maximum likelihood (ML) procedures for estimating the source range, depth, and direction-of-arrival (DOA) based on the normal mode representation of the received data are studied. In the first procedure, ML estimation of range and depth is applied on the data collected by a vertical array, and DOA is estimated using the ML algorithm on the data received by a separate, horizontal array. In the second procedure, the ML algorithm is applied on the data received by a two-dimensional (2-D), hybrid array for simultaneously estimating of all three source location parameters. Our study shows that although a horizontal array is sufficient for 3-D localization, to reduce sensitivity of the localization algorithm, a 2-D array should be used. The presented performance analysis of the two algorithms enables one to determine the performance losses in using the stage-wise, suboptimal algorithm relative to the optimal one in any given scenario. Numerical examples with channel parameters, which are typical to shallow water source localization, show performance losses of 0-3 dB. Simulation results of the two ML algorithms and their comparison with the Cramer-Rao bound (CRB) support the theory     

一种基于矩阵三对角化分解的DOA估计算法

针对DOA（Direction of Arrival）估计在低信噪比的情况下估计性能下降的问题, 根据阵列协方差矩阵共轭对称的特点,采用基于Givens变换的三对角化分解方法对协方 差矩阵进行三对角化,同时利用盖氏(Gerschgorin)圆递推方法准确估计信号子空间的秩, 然后再对三对角 矩阵进行对角化,估计出噪声子空间,利用噪声子空间与导向矢量正交实现波达方向估计, 改善了低信噪比背景下估计的误差性能和稳健性。计算机仿真证明了算法的有效性 。     

DOA estimation method of weak sources for an array antenna under strong interference conditions

The concept of a preserving source orthogonality and characteristic beam is defined according to an array data model. It is proven theoretically that the corresponding eigenvectors maintain the preserving orthogonality when the powers and the angle intervals between the signals are large. The theory is then applied to the direction of arrival (DOA) estimation for the array antenna in the presence of strong interference. A novel DOA estimation algorithm based on the elimination of the eigenvectors of interference is proposed. The simulation results and comparison of the jamming jam method (JJM) algorithm show that the proposed algorithm does not require the position of the interference source to be known. Moreover, its interference suppression ability and statistical estimation performance are superior to those of the JJM, and thus, it is more suitable for low SNR and small angle intervals.     

智能天线中一种新的三维波束形成方法

提出了用分布于 x?y?z 三轴上的三个阵元估计扩频信号各条多径的来波方向(DOA)的方法,以及用由 x?y 均匀平面圆阵和 z 轴直线阵组成的阵列天线形成 3 维波束的方法。根据 CDMA 信号模型和多径信道模型,用 最大似然(ML)法分别估计出信号到达 3 个阵元的复信道响应,并利用复信道响应的幅角来估计各条多径信号 的 DOA;然后在已有最小均方误差(MMSE)法和最小二乘(LS)法的基础上生成带限制条件的扩展 MMSE(EMMSE)法形成 3 维波束。模拟表明,给出的 DOA 估计方法具有很高的精度,而 EMMSE 方法形成的波束主 瓣窄,旁瓣被抑制,有很高的输出信干噪比。