TOA-Based NLOS Error Mitigation Algorithm for 3D Indoor Localization

In the process of indoor localization,the existence of the non-line of sight(NLOS)error will greatly reduce the localization accuracy.To reduce the impact of this error,a 3 dimensional(3D)indoor localization algorithm named LMR(LLS-Minimum-Residual)is proposed in this paper.We first estimate the NLOS error and use it to correct the measurement distances,and then calculate the target location with linear least squares(LLS)solution.The final nodes location can be obtained accurately by NLOS error mitigation.Our algorithm can work efficiently in both indoor 2D and 3D environments.The simulation results show that the proposed algorithm has better performance than traditional algorithms and it can significantly improve the localization accuracy.

An Indoor Localization Approach Based on Fingerprint and Time-Difference of Arrival Fusion

In this paper,an effective target locating approach based on the fingerprint fusion posi-tioning(FFP)method is proposed which integrates the time-difference of arrival(TDOA)and the received signal strength according to the statistical variance of target position in the stationary 3D scenarios.The FFP method fuses the pedestrian dead reckoning(PDR)estimation to solve the moving target localization problem.We also introduce auxiliary parameters to estimate the target motion state.Subsequently,we can locate the static pedestrians and track the the moving target.For the case study,eight access stationary points are placed on a bookshelf and hypermarket;one target node is moving inside hypermarkets in 2D and 3D scenarios or stationary on the bookshelf.We compare the performance of our proposed method with existing localization algorithms such as k-nearest neighbor,weighted k-nearest neighbor,pure TDOA and fingerprinting combining Bayesian frameworks including the extended Kalman filter,unscented Kalman filter and particle fil-ter(PF).The proposed approach outperforms obviously the counterpart methodologies in terms of the root mean square error and the cumulative distribution function of localization errors,espe-cially in the 3D scenarios.Simulation results corroborate the effectiveness of our proposed approach.

STABILITY OF 3-D DISTURBANCE WAVES ON BOUNDARY LAYER WITH DISTRIBUTED LOCAL ROUGHNESS

The numerical solution of the stable basic flow on a 3-D boundary layer is obtained by using local ejection, local suction, and combination of local ejection and suction to simulate the local rough wall. The evolution of 3-D disturbance T-S wave is studied in the spatial processes, and the effects of form and distribution structure of local roughness on the growth rate of the 3-D disturbance wave and the flow stability are discussed. Numerical results show that the growth of the disturbance wave and the form of vortices are accelerated by the 3-D local roughness. The modification of basic flow owing to the evolvement of the finite amplitude disturbance wave and the existence of spanwise velocity induced by the 3-D local roughness affects the stability of boundary layer. Propagation direction and phase of the disturbance wave shift obviously for the 3-D local roughness of the wall. The flow stability characteristics change if the form of the 2-D local roughness varies.

3-D Reconstruction and Visualization of Laser-Scanned Trees by Weighted Locally Optimal Projection and Accurate Modeling Method

This paper presents a method to reconstruct 3-D models of trees from terrestrial laser scan(TLS)point clouds.This method uses the weighted locally optimal projection(WLOP)and the AdTree method to reconstruct detailed 3-D tree models.To improve its representation accuracy,the WLOP algorithm is introduced to consolidate the point cloud.Its reconstruction accuracy is tested using a dataset of ten trees,and the one-sided Hausdorff distances between the input point clouds and the resulting 3-D models are measured.The experimental results show that the optimal projection modeling method has an average one-sided Hausdorff distance(mean)lower by 30.74%and 6.43%compared with AdTree and AdQSM methods,respectively.Furthermore,it has an average one-sided Hausdorff distance(RMS)lower by 29.95%and 12.28%compared with AdTree and AdQSM methods.Results show that the 3-D model generated fits closely to the input point cloud data and ensures a high geometrical accuracy.

THREE-DIMENSIONAL CONFORMAL RADIATION THERAPY FOR LOCALLY RECURRENT NASOPHARYNGEAL CARCINOMA

Objective: To investigate the safety and effectiveness of three-dimensional conformal radiation therapy (3-D CRT) for locally recurrent nasopharyngeal carcinoma (NPC). Methods: From April 1998 to March 2000, 34 patients who had undergone previous external beam radiation therapy were retreated with 3-D CRT for locally recurrent NPC (33 poorly differentiated squamous cell carcinomas, 1 adenoma). The patients were re-staged according to Huaqing staging system with the following distribution: T1N0M0 in 5 cases, T2N0M0 in 11 cases, T3N0M0 in 12 cases, T4N0M0 in 6 cases. The maximal dimension of the gross tumor volume (GTV) ranged from 1.0 cm to 5.0 cm (median: 2.9 cm). CT simulation and 3-D planning were used to ensure full and conformal coverage of the planning target volume (PTV) by treated volume, while minimizing the absorbed dose of the adjacent normal tissue. 5–7 static conformal coplanar or noncoplanar portals were delivered for each fraction irradiation. The total dose delivered ranged from 65–70 Gy, with 2.5 Gy per fractionation, one fractionation per day, 5 days a week. Median follow-up time from 3-D CRT was 25 months (range: 12–36 months). Results: Over the follow-up period, local recurrence was observed in 3 patients, regional failure in 3, distant metastasis in 3, and six patients died; 88.2% (30/34) of the patient maintained local control, 82.4% (28/34) survived, and 76.5% (26/34) survived with no evidence of tumor. Acute complications were minor and few. The overall incidence of late complication was 20.6% (7/34), and severe complication was 14.7% (5/34), after re-irradiation with 3-D CRT. Conclusion: 3-D CRT is safety and effectiveness for most of the patients with locally recurrent NPC. Our preliminary results indicate a high local control rate and a low complication rate. The long-term curative effect and sequelae await further study.

基于3DCNN的CSI-cluster室内指纹定位算法

针对室内环境中复杂的多径效应影响定位精度问题,提出一种基于3维卷积神经网络(3 dimensional convolutional neural network,3DCNN)多径程度划分的自校准指纹定位算法。该算法利用MeanShift方法分析定位区域内每一个采样点的信道状态信息数据分布特性,得到其可代表多径效应程度的簇类数量,结合阈值原则将指纹库划分为2种不同多径程度的子库,从而减少多径程度差异较大的指纹点对后续定位影响利用3DCNN深度学习2类指纹子库。在定位阶段,根据校准算法判断待测数据所属子库,并采用相应的3DCNN模型估计位置。通过仿真实验验证,该方法在保证指纹库构建合理性和高效性的同时,在定位精度方面实现了明显的提升,优于与之对比的相关算法。

Exponential Convergence Theory of the Multipole and Local Expansions for the 3-D Laplace Equation in Layered Media

In this paper,we establish the exponential convergence theory for the multipole and local expansions,shifting and translation operators for the Green's function of 3-dimensional Laplace equation in layered media.An immediate application of the theory is to ensure the exponential convergence of the FMM which has been shown by the numerical results reported in[27].As the Green's function in layered media consists of free space and reaction field components and the theory for the free space components is well known,this paper will focus on the analysis for the reaction components.We first prove that the density functions in the integral representations of the reaction components are analytic and bounded in the right half complex wave number plane.Then,by using the Cagniard-de Hoop transform and contour deformations,estimates for the remainder terms of the truncated expansions are given,and,as a result,the exponential convergence for the expansions and translation operators is proven.

Camera localization for augmented reality and indoor positioning:a vision-based 3D feature database approach

The recent fast development in computer vision and mobile sensor technology such as mobile LiDAR and RGB-D cameras is pushing the boundary of the technology to suit the need of real-life applications in the fields of Augmented Reality(AR),robotics,indoor GIS and self-driving.Camera localization is often a key and enabling technology among these applications.In this paper,we developed a novel camera localization workflow based on a highly accurate 3D prior map optimized by our RGBD SLAM method in conjunction with a deep learning routine trained using consecutive video frames labeled with high precision camera pose.Furthermore,an AR registration method tightly coupled with a game engine is proposed,which incorporates the proposed localization algorithm and aligns the real Kinetic camera with a virtual camera of the game engine to facilitate AR application development in an integrated manner.The experimental results show that the localization accuracy can achieve an average error of 35 cm based on a fine-tuned prior 3D feature database at 3 cm accuracy compared against the ground-truth 3D LiDAR map.The influence of the localization accuracy on the visual effect of AR overlay is also demonstrated and the alignment of the real and virtual camera streamlines the implementation of AR fire emergency response demo in a Virtual Geographic Environment.

Atmospheric Pressure-Aware Seamless 3-D Localization and Navigation for Mobile Internet Devices

This paper describes a seamless three-dimensional （3-D） localization and navigation system for smartphones. The smartphone includes an atmospheric pressure sensor to measure the user＇s altitude that is combined with the outdoor Global Positioning System （GPS） and indoor WiFi-APs localization systems in a seamless 3-D localization system. The smartphone software also provides seamless navigation services by updating map information for both indoor and outdoor locations through the mobile Internet. The indoor floor information calculated from the altitude information is used to project localization anchor nodes, e.g., WiFi-AP, on different floors onto the user＇s floor with an indoor 3-D localization algorithm using projection distances based on a Received Signal Strength （RSS） algorithm. Tests show that the 3-D method reduces systematic errors and achieves much higher accuracy than the traditional two-dimensional localization method.

仓储场景中基于无线标签的三维定位方法

仓储行业在面向智能化发展中面临因无法获取物资的室内位置信息而导致出库、入库难等问题,为实现对物资准确定位,该文提出一种基于无线标签的目标3维定位方法。设计的无线标签安置在待定位物资上,将来自发射机正交频分复用(OFDM)信号反射到具有均匀面阵(UPA)天线阵列的接收机,进行多通道的信道估计后,利用分步的稀疏恢复算法实现高维无线信道参数估计,并结合发射机、标签和接收机的空间几何位置,建立标签位置的优化问题,最后采用群智能算法搜索得到目标准确的3维位置。为验证系统,实现了标签及收发机原型,实测结果表明,目标的中值3维定位精度达到0.53 m。

A survey on indoor 3D modeling and applications via RGB-D devices

With the fast development of consumer-level RGB-D cameras, real-world indoor three-dimensional(3 D) scene modeling and robotic applications are gaining more attention. However, indoor 3 D scene modeling is still challenging because the structure of interior objects may be complex and the RGB-D data acquired by consumer-level sensors may have poor quality. There is a lot of research in this area. In this survey, we provide an overview of recent advances in indoor scene modeling methods, public indoor datasets and libraries which can facilitate experiments and evaluations, and some typical applications using RGB-D devices including indoor localization and emergency evacuation.

A new navigation approach of terrain contour matching based on 3-D terrain reconstruction from onboard image sequence

This article presents a passive navigation method of terrain contour matching by reconstructing the 3-D terrain from the image sequence(acquired by the onboard camera).To achieve automation and simultaneity of the image sequence processing for navigation,a correspondence registration method based on control points tracking is proposed which tracks the sparse control points through the whole image sequence and uses them as correspondence in the relation geometry solution.Besides,a key frame selection method based on the images overlapping ratio and intersecting angles is explored,thereafter the requirement for the camera system configuration is provided.The proposed method also includes an optimal local homography estimating algorithm according to the control points,which helps correctly predict points to be matched and their speed corresponding.Consequently,the real-time 3-D terrain of the trajectory thus reconstructed is matched with the referenced terrain map,and the result of which provides navigating information.The digital simulation experiment and the real image based experiment have verified the proposed method.

Indoor scene texturing based on single mobile phone images and 3D model fusion

Realistic texture mapping and coherent up-to-date rendering is one of the most important issues in indoor 3-D modelling.However,existing texturing approaches are usually performed manually during the modelling process,and cannot accommodate changes in indoor environments occurring after the model was created,resulting in outdated and misleading texture rendering.In this study,a structured learning-based texture mapping method is proposed for automatic mapping a single still photo from a mobile phone onto an alreadyconstructed indoor 3-D model.The up-to-date texture is captured using a smart phone,and the indoor structural layout is extracted by incorporating per-pixel segmentation in the FCN algorithm and the line constraints into a structured learning algorithm.This enables real-time texture mapping according to parts of the model,based on the structural layout.Furthermore,the rough camera pose is estimated by pedestrian dead reckoning(PDR)and map information to determine where to map the texture.The experimental results presented in this paper demonstrate that our approach can achieve accurate fusion of 3-D triangular meshes with 2-D single images,achieving low-cost and automatic indoor texture updating.Based on this fusion approach,users can have a better experience in virtual indoor3-D applications.

室内动态通风环境中时变源的多机器人三维溯源实验研究

快速、准确地定位室内气体污染源/危险源对保证室内空气质量和环境安全具有重要意义。前期针对室内机械通风环境中污染源定位的研究主要是机器人二维溯源,即假设源高度已知,且机器人所携带的传感器高度固定不变。然而,二维溯源可能难以在实际应用中有效应对源高度未知和不确定的场景。本文设计搭建了3台可实现传感器在高度(0.5~1.5 m)上受控移动的三维溯源机器人,将前期开发的基于粒子群算法的改进粒子群方法(IPSO)运用于三维溯源。本文在某实训中心开展实验,机器人的活动范围为7.65 m×4.1 m。实验中通过柜式空调送风百叶的周期性摆动来营造典型的动态环境,在下风区的0.75 m和1.05 m高度设置周期性源。每种源定位工况均开展了15组实验。当源位于二维溯源中传感器的高度时(1.05 m),二维溯源和三维溯均成功了11组,成功率均为73.3%;当源低于二维溯源中传感器的高度时(0.75 m),二维溯源和三维溯源分别成功了3组和10组,成功率分别为20%和66.7%。研究结果表明,在本文的实验环境中,二维溯源在源高度为1.05 m时溯源的成功率较高,但在源高度为0.75 m时的成功率显著下降,已无法满足实际应用的需求。三维溯源在两种情况下均具有较高的成功率,且在源高度为0.75 m时溯源的成功率明显高于二维溯源。