基于空间相关性滤波和迭代最小余差剔除NLoS的ToA定位算法

To mitigate the Non-Line-of-Sight (NLoS) error which seriously affects the localization accuracy and robustness in complex indoor environment, a novel Iterative Minimum Residual (IMR) based on the consistency hypothesis of the residual and the error is proposed in this paper. It chooses the best subset of measurements to calculate the coordinates of the unknown node by comparing the residuals obtained with different subsets of beacons. To reduce the time complexity of the IMR algorithm, Spatial Correlation Filter (SCF) is also proposed, which can remove the most serious NLoS distance with low calculation cost. Combined with the proposed SCF and IMR algorithm, nodes can be localized with high accuracy and low time complexity. Experimental results with real dataset demonstrate that the proposed algorithm can identify the NLoS range effectively with about 50% time cost of employing SCF only.     

小波分析法解决无线定位跟踪问题

无线定位中,信号的非视距传播（NLoS）很大程度上决定了移动台的定位精度,而小波分析理论在信号处理中有较为明显的优点,提出了一种在蜂窝网络中非视距环境下对移动台（MS）的定位及跟踪算法。利用小波变换对信号的分解和重构,实现了对TDOA测量值误差的修正,再利用经典Chan算法对移动台位置进行估计,配合相应的距离门限值对移动台的位置进行跟踪定位。仿真结果表明,该算法能够有效地实现对移动台位置的静态定位和动态跟踪,并明显优于同等环境下经典算法的仿真结果,有效提高了定位精度。     

基于TOA的置信因子移动定位算法

移动台的精确定位面临的一个主要问题就是信号的非视距(NLOs)传输。小文在TOA测量距离的基础上,利用基站和测量值之间的几何关系、信号的损耗模型和信号强度信息,提出了置信因子定位算法(BFA)。研究了BFA算法在不同类型NLOS误差下的表现,结果表明该算法能够有效地降低NLOS误差的影响,定位精度比其它算法有显著提高,而且在不同分布的NLOS误差下表现稳定。     

Indoor channel measurements and characterization at 60 GHz for wireless local area network applications

This work presents propagation measurement results at 60 GHz in order to determine the characteristics of indoor radio channels between fixed terminals. Path loss measurements are reported for line-of-sight (LoS) and non-line-of-sight (NLoS) cases, fading statistics in a physically stationary environment are extracted and a detailed investigation of the people movement effect on the temporal fading envelope is performed. Models that presented to predict path loss provide excellent fitting with errors of 1.13 and 3.84 dB for LoS and NLoS topographies, respectively. The dynamic range of fading in a quiescent environment is 8.8 dB and increased to 35 dB when a person moves between the fixed terminals with the channel becoming extremely nonstationary. Temporal variations induced by the moving people depend on the speed, the number of individuals the body sizes and the environment. Slow fading is observed as well as a quasi-wide-sense stationary (QWSS) behavior of the fading, but up to 50 ms of time.     

Mobile Localization Under Non-Line-of-Sight Conditions Using Scattering Information

A novel mobile localization algorithm under non-line-of-sight (NLoS) conditions involving at most two base stations (BS) is presented. By using such a small number of BSs, the proposed technique avoids problems related to weak mobile hearability and excessive network messaging overload. Based on a scattering model, the NLoS hybrid approximate maximum likelihood (NLoS HAML) approach presented herein estimates the distances between the mobile station (MS) and the scatterers through the measured hybrid time-of-arrival/angle-of-arrival (ToA/AoA) statistics. Then, it matches the calculated distances to a known scatterers’ distribution in a maximum likelihood (ML) sense. Numerical results prove that the proposed algorithm outperforms previous methods by providing an accuracy enhancement that reaches 60%. It is also shown that the performance enhancement provided by the proposed algorithm is maximized when the adequate scatterers distribution is adopted.     

6G超大规模天线信道波束域传播特性分析

为了探明6G超大规模天线信道在波束域的信道传播特性,重点开展了无线信道测量实验与测量数据分析.首先,在典型城市场景下,开展了sub-6 GHz频段配置超大规模均匀线阵的视距(light-of-sight, LoS)和非视距(non-LoS, NLoS)信道测量实验;其次,划分若干子阵列,并分别使用高分辨率参数提取算法估计多径幅度、时延和角度;然后,根据不同的子阵列角度分辨率构建虚拟波束,将对应不同虚拟波束角度的多径进行分组及叠加.通过比较不同子阵列在相同角度对应的虚拟波束系数,发现传统天线域的空间非平稳特性在波束域表现不明显.通过分析不同虚拟波束的信道系数,可观察到波束域稀疏特性,并且LoS场景的稀疏特性更加明显.针对不同场景下各虚拟波束的多径数目、功率和均方根时延扩展进行拟合分析,可知分别服从高斯分布、高斯分布、均匀分布.此外,分析发现LoS场景下虚拟波束间相关性较低,而NLoS场景下虚拟波束间相关性随波束分辨率提高而增大.     

A Cooperative Localization Algorithm for UWB Indoor Sensor Networks

This paper deals with range-based localization in ultra wideband sensor networks, allowing for the possibility of large range measurement errors because of a failure to detect the direct paths between some nodes. A novel algorithm is proposed that uses only partial knowledge of the service area topology, particularly of the positions of objects which are capable of causing undetected direct path (UDP) propagation conditions. Although the spirit of the proposed approach, because of the lack of information on the range error statistics, is to remove measurements performed under UDP conditions from the computation of the location estimate, these measurements are used implicitly by the algorithm to contribute to the erroneous trial locations being discarded. A cooperative stage is included that allows the probability of localization of a target with an insufficient initial number of accurate range measurements to increase. The proposed algorithm outperforms a variety of alternative positioning techniques, and thus illustrates the capability of this topology knowledge to mitigate the UDP problem, even in the absence of any knowledge about the range error statistics.     

Two base station location techniques with adjusted measurements in circular scattering environments

In circular scattering environments, novel location techniques with only two base stations (BSs) are proposed in this paper. The proposed techniques estimate the true or line‐of‐sight ranges and angle based on non‐line‐of‐sight range and angle measurements. Three new variables are introduced when range measurements and angle measurement are available from two BSs and the serving BS, respectively. Bounds and relationships between the three variables are extracted from the geometry of the cell layout with the unknown and known scattering radius conditions, respectively. Our aim is to obtain the estimation of three new variables and then the hybrid line of position technique with the adjusted ranges, and angle is utilized to obtain the position estimation of a mobile station. In order to obtain the estimation of three new variables, a new nonlinear objective function is built to form the constrained nonlinear optimization and solved by the existing optimization algorithms. However, because of the nonconvex objective function, the optimization algorithm may converge to the local optimum and lead to bad performance. Thus, a heuristic search algorithm is proposed by averaging all the potential point. Simulation results show that the proposed techniques outperform conventional hybrid techniques. Copyright © 2015 John Wiley & Sons, Ltd.     

Non-line of Sight Error Mitigation in Ultra-wideband Ranging Systems Using Biased Kalman Filtering

In this paper, a non-line of sight (NLOS) error mitigation method based on biased Kalman filtering for ultra-wideband (UWB) ranging is proposed. The NLOS effect on the measures of signal arrival time is considered one of the major error sources in range estimation and time-based wireless location systems. An improved biased Kalman filtering system, incorporated with sliding-window data smoothing and hypothesis test, is used for NLOS identification and error mitigation. Based on the results of hypothesis test, the estimated ranges are either calculated by smoothing the measured range when line of sight (LOS) status is detected, or obtained by conducting error mitigation on the NLOS corrupted measured range when NLOS status is detected. The effectiveness of the proposed scheme in mitigating errors during the LOS-to-NLOS and NLOS-to-LOS transitions is discussed. Improved NLOS identification and mitigation during the NLOS/LOS variations of channel status are attained by an adaptive variance-adjusting scheme in the biased filter. Simulation results show that the UWB channel status and the transition between NLOS and LOS can be identified promptly by the proposed scheme. The estimated time-based location metrics can be used for achieving higher accuracy in location estimation and target tracking.     

一种CDMA蜂窝定位中减小NLOS误差的算法

随着下一代移动通信研究的热潮,移动定位技术的研究也方兴未艾。在移动定位方程的解算中,测量噪声和NLOS误差是主要误差源,尤其是NLOS已经成为影响定位精度的主要因素。本文研究了CDMA系统中的NLOS误差减小问题,基于残余函数概念提出了ARWA算法,在NLOS路径不能有效识别的条件下,有效地减小了NLOS误差;仿真结果显示这种算法的定位精度明显强于一般LS估计。     

基于Kalman滤波器的室内激光/INS融合定位方法

讨论未知多边形室内环境下微型飞行器(MAV)的定位问题。利用惯性测量单元(IMU)测量飞行器运动参数,并计算飞行器的位置、航向。二维激光测距仪测量飞行器相对于障碍的位置,用迭代搜索/最小二乘算法匹配扫描数据,获得2次扫描的相对位移和转动。然后分析激光扫描匹配和惯性导航系统(INS)的误差,建立相应误差模型,并以此设计间接反馈校正Kalman滤波器。仿真结果显示,该激光/INS融合定位方法相比纯INS定位和无融合激光扫描匹配定位的精确度更高,并能将误差限制在一个较小的范围内。     

基于虚拟参考站的同步三星时差定位系统广域差分校正算法

星历误差是导致同步三星时差定位系统定位误差的主要因素,该文针对传统差分校正算法在远离参考站区域对星历误差校正精度差的问题,提出一种基于虚拟参考站(VRS)的广域差分校正算法。首先证明两参考信号时差的差分残差近似为两参考站连线方向的线性函数;然后利用已有参考站的位置信息和参考信号的时差观测值,在目标辐射源位置处通过线性拟合构造一个VRS;最后将目标辐射源与VRS的时差观测值进行差分,从而实现对星历误差的高精度校正。仿真结果表明,相比传统差分校正算法,该方法可大范围消除星历误差对同步三星时差定位系统定位精度的影响,且定位精度可逼近CRLB。     

一种新的加权最小二乘测距定位方法

三站二维定位问题是最小定位问题，一般只利用几何关系就能获得定位估计，但由于未利用距离测量的统计信息，定位精度较差。该文先将点到点的距离测量转化为点到线的距离估计，再在此基础上推导出一种新的加权几休定位方法，其中加权的确定利用了距离测量的统计信息。仿真实验表明，在测距误差较小时新方法具有更高的定位精度。     

A new NLOS error mitigation algorithm in location estimation

In this paper, an effective technique is proposed for locating a mobile station's position when the range measurements are corrupted by non-line-of-sight (NLOS) errors. By linearizing the inequality of range models incorporating NLOS errors and adding loose variables, the method first acquires a preliminary estimation that relies on an initial value. After addressing the effect of linearization error and analyzing the preliminary estimation, a noniterative estimator that does not need an initial value is deduced. The method does not require knowledge of NLOS error statistics. Simulation results indicate that the proposed algorithm can restrain the NLOS errors and improve location accuracy.     

无线定位系统的误差分析

影响无线定位系统应用的关键因素是系统的误差源和误差抑制方法.本文针对TOA/TDOA(timeof arrival/time difference of arrival)定位算法,对定位系统的误差源:TOA参数估计误差、信号传播误差、基站误差、移动台误差、定位算法误差进行了详细的分析,对部分误差提出了抑制的方法,并且描述了相应误差的大小.     

On the Effect of Shadow Fading on Wireless Geolocation in Mixed LoS/NLoS Environments

This paper considers the wireless non-line-of-sight (NLoS) geolocation in mixed LoS/NLoS environments by using the information of time-of-arrival. We derive the Cramer-Rao bound (CRB) for a deterministic shadowing, the asymptotic CRB (ACRB) based on the statistical average of a random shadowing, a generalization of the modified CRB (MCRB) called a simplified Bayesian CRB (SBCRB), and the Bayesian CRB (BCRB) when the a priori knowledge of the shadowing probability density function is available. In the deterministic case, numerical examples show that for the effective bandwidth in the order of kHz, the CRB almost does not change with the additional length of the NLoS path except for a small interval of the length, in which the CRB changes dramatically. For the effective bandwidth in the order of MHz, the CRB decreases monotonously with the additional length of the NLoS path and finally converges to a constant as the additional length of the NLoS path approaches the infinity. In the random shadowing scenario, the shadowing exponent is modeled by sigmav = usigma, where u is a Gaussian random variable with zero mean and unit variance and sigma is another Gaussian random variable with mean mu_sigma and standard deviation sigma_sigma. When mu_sigma is large, the ACRB considerably increases with sigma_sigma, whereas the SBCRB gradually decreases with sigma_sigma. In addition, the SBCRB can well approximate the BCRB.     

基于分簇结构无线传感器网络的高效无源定位方法

针对基于节点通信能力和能量受限的无线传感器网络实现高精度无源定位的问题,首先,在分簇结构网络中,通过折中单个簇的TDOA定位精度和运算复杂度,确定了簇规模;其次,基于直达波环境中TDOA定位误差是按布站GDOP对测量误差放大的原理,提出第一轮定位先使用网内所有节点以RSSI定位方法粗估计目标辐射源位置,并根据各簇在该粗估计位置处的布站GDOP和测量误差估算TDOA定位标准差,第二轮定位选择具有较低TDOA定位估计标准差的部分簇参与TDOA定位,最后将这些簇的TDOA定位结果按估算的定位估计标准差加权平均,求得最终定位解。仿真结果证明该方法有效的去除了冗余节点,实现以半数节点接近使用全部节点的定位精度。      

无线传感网中NLoS环境下的ToA/AoA改进混合定位算法(英文)

An improved hybrid Time of Arrival (ToA)/ Angle of Arrival (AoA) location algorithm by adopting Gauss-Newton iterative algorithm is proposed. It is with the advantage of fast convergence and combining with the grid-search-based method to optimize the initial object coordinates of the iteration, meanwhile, under the condition of small measurement errors caused by noises of ToA and AoA, the algorithm performance can be improved effectively. In the Non-Line-of-Sight (NLoS) environments of the Wireless Sensor N...     

基于惯性鞋载传感器的人员自主定位粒子滤波方法

为了解决卫星导航信号被遮挡条件下定位问题,该文提出一种基于惯性鞋载传感器的高精度人员自主定位方法。该方法通过经典的拓展卡尔曼滤波辅助的零速更新(ZUPT-aided EKF)算法解算鞋尖惯性测量数据得到人员的初步运动轨迹,并创新性地提出一种粒子滤波框架下利用建筑物结构先验知识对轨迹进行修正的方法。根据大多数建筑物的结构,将行走平面划分为8个方向,包含4个主方向(走廊朝向)和4个辅助方向。根据粒子偏离8方向的程度按照高斯函数对粒子的权值进行更新,并用剩余重采样的方法避免了粒子的退化。实测数据验证了该文提出的方法,结果表明:该方法比轨迹修正前和传统轨迹修正的方法有更好的精度,在861 m的复杂轨迹下定位误差仅为2.7 m,定位精度优于0.5%;同时该方法有较好的一致性,不同楼层间的行走定位误差保持在2 m内, 可以进行稳定持续地定位。