Wideband angle of arrival estimation of chirp signals using virtual Wignerville distribution

To estimate the angle of arrivals （AOA） of wideband chirp sources, a new timo-frequency algorithm is proposed. In this method, virtual sensors are constructed based on the fact that the steering vectors of wideband chirp signals are linear and vary with time. And the randon Wignersville distribution （RWVD） of real sensors and virtual sensors are calculated to yield the new time-invariable steering vectors, furthermore, the noise and cross terms are suppressed. In addition, the multiple chirp signals are selected by their time-frequency points. The cost of computation is lower than the common AOA estimation methods of wideband sources due to nonrequirement of frequency focusing, interpolating and matrix decomposition, including subspace decomposition. Under the lower signal noise ratio （SNR） condition, the proposed method exhibits better precision than the method of frequency focusing （FF）. The proposed method can be further applied to nonuniform linear array （NLA） since it is not confined to the array geometry. Simulation results illustrate the efficacy of the proposed method.

Performances Analysis of a System of Localization by Angle of Arrival UWB Radio

The increasingly widespread use of sensor and actuator networks and in general of the Internet of Things (IoT) in several areas of precision, imposes upon localization systems that can often equip them with a robust and more precise localization. It is in this sense that UWB technology has proved to be one of the most powerful communication technologies for these localization systems;thanks, in particular to the bandwidth occupied instantaneously by the signal allowing a very fine temporal resolution. Constructors have set up localization kits based on various technologies. These kits facilitate in a way the work of localization of users. In this paper, we present results on the performance study of the Decawave PDoA Kit. This Kit uses the PDoA (Phase Difference of Arrival) to determine the Angle of Arrival (AoA) parameter with UWB technology. This study is in context of localization by AoA for an application to protect agricultural crops against grain-eating birds. The results of the study show overall AoA measurement errors around 10 degrees in an ideal environment.

Target Localization Based on Angle of Arrivals

Mobile location using angle of arrival （AOA） measurements has received considerable attention. This paper presents an approximation of maximum likelihood estimator （MLE） for localizing a source based on AOA measurements. By introducing an intermediate variable, the nonlinear equations relating AOA estimates can be transformed into a set of equations which are linear in the unknown parameters. It is an approximate realization of the MLE. Simulations show that the proposed algorithm outperforms the previous contribution.

Refractivity estimations from an angle-of-arrival spectrum

This paper addresses the probability of atmospheric refractivity estimation by using field measurements at an array of radio receivers in terms of angle-of-arrival spectrum. Angle-of-arrival spectrum information is simulated by the ray optics model and refractivity is expressed in the presence of an ideal tri-linear profile. The estimation of the refractivity is organized as an optimization problem and a genetic Mgorithm is used to search for the optimal solution from various trial refractivity profiles. Theoretical analysis demonstrates the feasibility of this method to retrieve the refractivity parameters. Simulation results indicate that this approach has a fair anti-noise ability and its accuracy performance is mainly dependent on the antenna aperture size and its positions.

Angle-of-arrival fluctuations in moderate to strong turbulence

Based on the modified spectrum, the analytic expressions for the variance and normalized covariance of angleof-arrival （AOA） fluctuations are presented, which are applicable to the weak and strong regimes. The experimental data of AOA fluctuations validate the new derived expressions in weak and strong regimes. The results show that the receiving aperture D, outer scale and cell scale larger than the scattering disc S contribute significantly to the AOA fluctuations, and contributions from the small-scale turbulence are negligible. For the case of 4S/D 〈〈 1, the receiving aperture dominates low-pass filtering effects and the new displacement variances are in good agreement with the results from the old weak-fluctuation theory. For the case of 4S/D 〉〉 1, the scattering disc dominates the low-pass filtering effects and the new displacement variances depart from the results from the old weak-fluctuation theory.

Beamforming and Angle-of-Arrival Estimation of Square Planar Antenna Array

This paper presents a dual-band planar antenna array for ISM band applications (2.4 GHz and 2.45 GHz). This antenna is proposed for indoor applications and enables adaptive beamforming and angle of arrival (AOA) estimation. An adaptive beamforming algorithm is applied for a planar antenna array, which is able to steer its main beam and nulls in azimuth and elevation planes over a wide frequency band. Planar antenna array operates as a spatial filter in 3D space, processing the received signals with weighting schemes. A planar antenna array is designed for AOA estimation in azimuth and elevation planes by using MUltiple SIgnal Classification (MUSIC) based on subspace algorithm. The Base Station (BS) equipped with this planar antenna is preferred to be at the center position on the room ceiling to cover all sectors of the room. It is designed to use four directional triangular elements arranged to form a square planar antenna array. Planar antenna with four elliptical slotted triangular elements (PAFESTE) is used to obtain optimal directivity in four directions in azimuth plane with specific orientation of 30? in elevation plane. It is characterized by half power beamwidth in elevation plane of about 60? and half power beamwidth in azimuth plane of about 90?.

Accurate Angle-of-Arrival Measurement Using Particle Swarm Optimization

As one of the major methods for location positioning, angle-of-arrival (AOA) estimation is a significant technology in radar, sonar, radio astronomy, and mobile communications. AOA measurements can be exploited to locate mobile units, enhance communication efficiency and network capacity, and support location-aided routing, dynamic network management, and many location-based services. In this paper, we propose an algorithm for AOA estimation in colored noise fields and harsh application scenarios. By modeling the unknown noise covariance as a linear combination of known weighting matrices, a maximum likelihood (ML) criterion is established, and a particle swarm optimization (PSO) paradigm is designed to optimize the cost function. Simulation results demonstrate that the paired estimator PSO-ML significantly outperforms other popular techniques and produces superior AOA estimates.

Blind 2-D Angles of Arrival Estimation for Distributed Signals Using L-Shaped Arrays

Most existing two dimensional（2-D）angles of arrival（AOAs）estimation methods are based on the assumption that the signal sources are point sources.However,in mobile communications,local scattering in the vicinity of the mobile results in angular spreading as seen from a base station antenna array.In this paper,we consider the problem of estimating the 2-D AOAs of spatially distributed sources.First we perform blind estimation of the steering vectors by exploiting joint diagonalization,then the 2-D AOAs are obtained through two fast Fourier transforming of the estimated steering vectors.Simulations are carried out to illustrate the performance of the method.

Estimation of 2-D Angles of Arrival Based on Joint Diagonalization of Two Spatio-Temporal Correlation Matrices

In this paper, we propose a two-dimensional （2-D） angles of arrival （AOAs） estimation method based on a joint diagonalization of two spatio-temporal （ST） correlation matrices. The mathematical manipulations proposed in this paper take the structure of the array that enable estimating 2-D AOAs simultaneously without 2-D searching or pairing. The performance comparison shows that the proposed method is better than ST-DOA matrix method.

基于TOA与AOA算法的室内定位方法

为了解决传统室内定位技术成本较高、稳定性差以及难于部署等问题,提出一种将到达时间(time of arrival,TOA)与到达角(angle of arrival,AOA)相结合的室内定位系统.该系统由定位基站与被控定位单元组成,其特征在于使用对射式布置的超声波传感器获取定位基站与被控定位单元之间的距离特征,利用角度传感器获取被控定位单元相对于定位基站的角度特征,以单基站就实现了精确的室内定位过程.分析了该系统基本结构与原理,建立定位与控制模型,在一定范围内对其定点定位精度与跟随定位精度进行了实验验证.实验结果表明:该系统结构简单,易于安装布置,鲁棒性强,在测试范围内的最大定点定位误差不超过5 cm,跟随定位误差不超过15 cm.

基于CSI商联合AOA的增强型指纹定位方法

针对当前指纹定位技术需要基于多个接入点(AP)被动定位,导致单AP室内场景使用受限的问题,提出一种信道状态信息(CSI)商联合到达角(AOA)的室内指纹定位方法:指出技术关键是利用单链路上的多维信号参数来构建指纹模型;利用多进多出(MIMO)系统空间分集,构建CSI商以获得更稳健的CSI指纹信号,并结合多信号分类(MUSIC)算法原理设计一种多载波AOA指纹表示方法,该方法与原始CSI指纹相比具有区分性;然后为了解决单AP的AOA指纹对称性问题,将CSI商与AOA指纹相结合,得到新的指纹,通过机器学习的方法进行目标位置匹配。实验结果表明,本方法在空教室和实验室环境下的定位准确率分别达到98.96%和97.08%,平均定位误差分别为0.46 m和0.68 m,具有较高的定位性能。

LOCALIZATION ALGORITHM USING DISTANCE AND ANGLE INFORMATION IN WIRELESS SENSOR NETWORKS

A localization algorithm using distance and angle information is proposed in wireless sensor networks. Assuming that node axial orientations are unknown, all angles are measured to calculate the angle differences between two nodes viewed by the third one. Then, localization problems are formulated as convex optimization ones and all geometric relationships among different nodes in the communication range are transformed into linear or quadratic constraints. If all measurements are accurate, the localization problem can be formulated as linear programming （LP）. Otherwise, by incorporating auxiliary variables, it can be regarded as quadratic programming （QP）. Simulations show the effectiveness of the proposed algorithm.

基于复域超多维标度的混合TOA/AOA定位算法

针对全球卫星导航系统信号完全拒止环境下的定位问题,使用超宽带(UWB)技术获取测量信息,基于多维标度变换算法(MDS)提出一种复域下的混合测距信息(TOA)和测角信息(AOA)的超多维标度定位算法(TASMDS),并进一步构建了复域内的核矩阵,提出复域下的超多维标度定位算法(TA-CDSMDS)。对比3种算法的定位结果,以及10°、15°、20°测角误差和不同测距误差下的定位误差,得TA-CDSMDS算法相较于TA-SMDS和MDS,有更小的定位误差,更贴近克拉美罗下界;分析不同节点下3种的计算时间,TA-CDSMDS算法在优化TA-SMDS的基础上减少28%~48%的时间,具有更好的定位性能。

一种加权圆模型的AOA与RSSI融合定位算法

针对多径效应和非视距给定位精度带来负面影响的问题,提出一种适用于3个基站的基于加权圆的融合定位算法:将接收信号强度(RSSI)定位法与到达角(AOA)法相融合;并由于传统的无线信号路径损耗模型在预测距离时易对环境参数有所依赖,提出利用自适应遗传算法(AGA)-反向传播(BP)神经网络来构建传播模型以确定加权圆的权值初始值;最后根据不断迭代的加权范围和角波束来估计待测点位置。实验结果表明,与其他混合定位方法的性能相比,将AGA-BP和加权圆算法相结合能更好地提高定位精度;同时,为测试鲁棒性,加入不同大小的干扰角度,结果可见,提出的算法能有效处理非视距误差。

On Time-of-Arrival Statistic of Gaussian Channel Model

A model of an angle-spread source, termed the “Gaussian Channel Model” is considered. The cumulative distribution function of the Time-of-Arrival of the multipath components is derived for an arbitrary angle spread. The simple approximate expressions for the Time-of-Arrival cumulative distribution function and probability density function are proposed. Numerical results obtained with the help of the derived expressions show the good coincidence with the experimental data and other known results.

无源雷达高速目标回波相参积累和参数估计算法

针对无源雷达高机动匀速目标参数估计中长时间积累引起的距离徙动效应问题,提出了一种基于Keystone变换和圆阵干涉仪测向的高效相参积累和参数估计算法。首先,根据目标运动和外辐射源信号参数,对参考信号和监视信号进行分段处理,段内为快时间,段间为慢时间;然后,利用Keystone变换对各频率的时间轴进行尺度变换,校正高速目标的距离徙动,继而将目标回波信号能量积累至同一时延-多普勒单元;最后,对目标回波所在的时延-多普勒单元进行圆阵干涉仪二维测向,得到目标方位角和俯仰角估计。仿真结果表明,算法可有效实现高机动匀速目标微弱回波信号的相参积累和参数估计,计算复杂度更低,对目标时延、多普勒、方位角和俯仰角参数估计的稳健性和精度更高。

无线传感器网络中基于超宽带的TOA/AOA联合定位研究

提出一种基于超宽带(ultra wideband,UWB)信号到达时间估计(time of arrival,TOA)/到达角度估计(angle of arrival,AOA)联合估计的无线传感器网络(wireless sensor networks,WSNs)定位方案,只需要一个参考节点就可以实现对其他传感器节点的2D相对定位,并且不需要时钟同步,适合于传感器网络节点的低成本设计需求.利用往返时间(round trip time,RTT)进行TOA估计,给出了基于多径检测的TOA估计算法;利用到达时间差估计(time difference of arrival,TDOA)进行AOA估计,因而无需借助复杂的天线波束赋形技术.同时,分析了定位误差模型对定位性能的影响,并通过IEEE802.15.4a信道下的仿真实验进行了验证,结果表明了所提方案的有效性.

基于TDOA/AOA混合的高精度室内可见光定位算法

为了提高室内三维空间的定位精度,提出了一种基于联合到达时间差与到达角度(time difference of arrival/angle of arrival,TDOA/AOA)信息的混合定位算法。由于构建的目标函数具有非凸性,采用传统定位算法在目标函数求解过程中会出现局部最优解的问题。因此,针对该问题,将目标函数转成二次约束二次规划问题,通过引入半定松弛(semi-definite relaxation,SDR)方法将目标函数转换为二阶锥规划(second order cone programming,SOCP)问题,寻找全局最优解。其次,针对SOCP无法对凸包外的目标进行有效定位的问题,在该算法的基础上引入了惩罚项,使松弛后的约束条件进一步逼近原始约束条件,解决了定位过程中的凸包问题。数值仿真结果表明:在10m×10m×3m的三维定位空间内,选取40×40个测试点,平均定位误差为1.39cm,可实现室内三维空间高精度定位。与传统的混合定位算法相比,均能够获得较高的定位精度。

基于AOA的无线传感器网络节点定位算法

在无线传感器网络节点SDP定位算法基础上，提出了一种改进的基于信号到达角（AOA）信息的无线传感器网络节点自身定位算法。本算法在所有节点的坐标轴方向都是未知的假定下，将AOA测量值用于计算信号到达差分角信息，将所有节点之间的角度关系表述为凸规划约束条件，从而将定位问题转化为一个凸集优化问题。在理想情况下，将定位问题转化为一个线性规划问题。实际情况中，考虑到测量误差，通过引入辅助变量，将定位问题转化为一个二次规划问题。仿真结果表明：改进算法与原算法相比，对AOA测量误差在10°以下时，定位精度提高约为5％～20％。

非视距传播环境下对移动用户定位的AOA方法

非视距传播问题是移动定位中的一个关键问题.基于几何结构的单次反射统计信道模型,提出了一种减小非视距传播影响的AOA定位方法.该方法一方面利用所有的参数信息进行定位,使有限的资源得到充分利用,另一方面采用不等式约束减小移动台的可行区域,二者结合以提高非视距传播环境下的定位精度.仿真结果证明了该方法的有效性.