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8th International Conference on Data Science in Cyberspace, DSC 2023

作者： Xiao, Kun Hao, Fuzhong Zhang, Weijian Li, Nuannuan Zhi, Haiyan Wang, Yintao University of Electronic Science and Technology Chengdu China State Grid Henan Electric Power Company Zhengzhou China

ISBN: (纸本)9798350331035

With the continuous updates, iterations, and promotion of Bluetooth standard specifications, Bluetooth has filled many gaps in existing indoor positioning technologies with its comprehensive technical specifications, rich application ecosystem, and a series of advantages such as low power consumption and low cost in hardware. Especially after the introduction of ADA/AOD direction finding technology in the Bluetooth 5.1 protocol specification, Bluetooth positioning can achieve high accuracy at the sub-meter level. Therefore, Bluetooth-based indoor positioning has become a current research hotspot and an important future development trend. However, there is currently relatively limited research and application of positioning algorithms and positioning systems based on Bluetooth, and there is no standardized set of positioning algorithms and positioning systems. Therefore, this paper proposes research and design on Bluetooth AOA positioning algorithm and Bluetooth AOA indoor positioning system. Through testing in actual indoor scenarios, the algorithm has been validated to achieve sub-meter positioning accuracy, and the entire positioning system has successfully completed the entire process from deployment to application demonstration. © 2023 IEEE.

关键词： bluetooth AOA (Angle of Arrival) indoor positioning positioning algorithm positioning system

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Performance comparison in Ultra Wide Band positioning in sensor networks: least square minimization versus grid search approach 6

Performance comparison in Ultra Wide Band positioning in sen...

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IEEE International Symposium on Measurements and Networking (M&N)

作者： Ferrigno, L. Milano, F. Pingerna, V. Cerro, G. Laracca, M. Univ Cassino & Southern Lazio Dept Elect & Informat Engn Cassino Italy Univ Molise Dept Med & Hlth Sci V Tiberio Campobasso Italy Sapienza Univ Rome Dept Astronaut Elect & Energy Engn Rome Italy

ISBN: (数字)9781665483629

ISBN: (纸本)9781665483629

The localization task in sensor networks is particularly critical whenever the sensor measurements are positionrelated, as in case of thermal and electromagnetic quantities. The deployment of a sensor network often requires the usage of low-cost devices able to achieve acceptable measurement accuracy and having the need to retrieve fast and accurate positioning information. In such networks, the localization task is generally performed by a special node coordinating the network. Nevertheless, its computing power is often limited. To this aim, in this paper we compare two different positioning techniques (least square minimization, grid search), to be applied in Ultra-WideBand positioning scheme, from the accuracy point of view and computing time required for accomplishing the task. They differ in working principle, needed a priori information, localization resolution and time to completion parameter. According to the available resources, the adoption of one of them should be preferable to the other one. Obtained results prove the goodness of both methods, specifically ranking them by application purposes. The paper is intended to give the designers an extensive analysis to evaluate pros and cons to adopt a completely blind positioning technique, namely the least square minimization, versus a more informed and constrained system, as the grid search case.

关键词： Indoor localization positioning algorithm Ultra Wide Band technology

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Multipath Suppressing Method Based on Pseudorange Model Using Modified Teaching-Learning Based Optimization algorithm

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Chinese Journal of Electronics 2022年第5期31卷 821-831页

作者： CHENG Lan ZHANG Jing NI Zihang YAN Gaowei Taiyuan University of Technology Xi'an Branch of China Telecom Co.Ltd.

Satellites based positioning has been widely applied to many areas in our daily lives and thus become indispensable, which also leads to increasing demand for high-positioning accuracy. In some complex environments(such as dense urban, valley), multipath interference is one of the main error sources deteriorating positioning accuracy, and it is difficult to eliminate via differential techniques due to its uncertainty of occurrence and irrelevance in different instants. To address this problem,we propose a positioning method for global navigation satellite systems(GNSS) by adopting a modified teachinglearning based optimization(TLBO) algorithm after the positioning problem is formulated as an optimization problem. Experiments are conducted by using actual satellite data. The results show that the proposed positioning algorithm outperforms other algorithms, such as particle swarm optimization based positioning algorithm,differential evolution based positioning algorithm, variable projection method, and TLBO algorithm, in terms of accuracy and stability.

关键词： global navigation satellite systems satellite navigation particle swarm optimisation optimization problem Global positioning System pseudorange model optimisation modified teaching-learning based optimization algorithm high-positioning accuracy positioning method particle swarm optimization position control evolutionary computation actual satellite data satellites based positioning dense urban valley variable projection method main error sources positioning problem positioning algorithm TLBO algorithm

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An Improved Position Determination algorithm Based on Nonlinear Compensation for Ground-Based positioning Systems

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IEEE ACCESS 2019年 7卷 23675-23689页

作者： Su, Jingxuan Yao, Zheng Lu, Mingquan Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

In the absence of GNSS or when signals from satellites are blocked in harsh environments, a ground-based positioning system can be used to estimate the position of users and receivers. Nevertheless, ground-based systems suffer dramatic nonlinear error resulting from the linearization used in typical positioning algorithms. Robust positioning algorithms that are capable of handling strong nonlinearity cases are therefore of great value. In this paper, we propose an algorithm termed promoted iterative least-squares based on nonlinear-compensation (PILSBON) to effectively alleviate the influence of nonlinear effects. This algorithm is based on the accurate expression of the nonlinear error terms in the double-differenced pseudorange measurement model. In order to eliminate the effects of nonlinearity for targeted solutions, the PILSBON uses iterative numerical estimation to compensate for nonlinear error so that the nonlinear position determination is transformed into a linear model, which can then be estimated with a linear estimation algorithm. In this paper, we analyze the properties of the PILSBON and compare it to conventional solutions. Because of its specific strategy for nonlinearity, our results show that the PILSBON improves the overall accuracy by approximately 30% compared with conventional solutions according to statistic RMSE data from over 500 experiments and positions. Moreover, by deploying a practical ground-based positioning system with six transmitters on the rooftop of our laboratory building, we demonstrate that the PILSBON algorithm can be efficiently employed in real-world experiments.

关键词： Nonlinear compensation ground-based positioning system positioning algorithm differential pseudorange least-squares estimation

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Construction of Probability Graph Optimization Model on Basis of Localization algorithm

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Procedia Computer Science 2024年 243卷 156-162页

作者： Song Li Qiuming Jiang Hubei Industrial Polytechic Shiyan Hubei China

Accurate positioning is crucial in fields such as indoor positioning, autonomous driving, and robot navigation. However, traditional base station positioning algorithms are often affected by factors such as sensor errors, environmental noise, and uncertainty, resulting in certain errors in the positioning results. The article constructed a probability graph model using Radio Frequency Identification (RFID) by using position estimation results as variables. In this model, each position estimation result was represented as a node, and the dependency relationship between positions was represented as an edge. This article observed sensor data and uses Bayesian inference methods to update the probability distribution of each node. The experimental results showed that compared to traditional base station positioning algorithms, the probability graph optimization model based on radio frequency identification can significantly improve the accuracy and reliability of positioning. The highest values for both reached 0.989 and 0.95, respectively. This model has significant advantages in positioning tasks and provides an effective solution for practical applications.

关键词： probability graph positioning algorithm optimization model bayesian inference radio frequency identification

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A Comparative Study of UWB-based True-Range positioning algorithms using Experimental Data 16

A Comparative Study of UWB-based True-Range Positioning Algo...

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16th Workshop on positioning, Navigation and Communications (WPNC)

作者： Sang, Cung Lian Adams, Michael Hesse, Marc Hoermann, Timm Korthals, Timo Rueckert, Ulrich Bielefeld Univ CITEC Cognitron & Sensor Syst Grp Bielefeld Germany

ISBN: (纸本)9781728120829

In this paper, we analyze five true-range positioning algorithms for UWB-based localization systems. The evaluated algorithms are: (i) trilateration using a geometric method, (ii) a closed-form multilateration solution using least squares, (iii) an iterative approach using first-order Taylor series, a recursive solution based on (iv) the Extended Kalman Filter (EKF), and (v) the Unscented Kalman Filter (UKF). In contrast to the existing comparative studies in literature, which are solely based on simulation results, our analysis is based on experimental evaluations. The evaluated algorithms are strictly chosen for a scenario, where a true-range multilateration method is applicable. True-range means the accuracy of the measured ranges is not influenced by the clock drift errors. The performance comparison of the five algorithms is examined and discussed in the paper.

关键词： comparative study comparative review true-range positioning algorithm performance comparison UWB trilateration multilateration Taylor series EKF UKF Kalman

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A precise localization algorithm for unmanned aerial vehicles integrating visual-internal odometry and cartographer

JOURNAL OF MEASUREMENTS IN ENGINEERING

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JOURNAL OF MEASUREMENTS IN ENGINEERING 2024年第2期12卷 284-297页

作者： Xu, Jiaqi Chen, Zhou Chen, Jie Zhou, Jingyan Du, Xiaofei Nanjing Inst Technol Sch Mech Engn Nanjing 211167 Peoples R China

Accurate positioning in space is an important foundation for ensuring the stability of autonomous flight and successful mapping and navigation of unmanned aerial vehicles (UAVs). At present, the SLAM algorithm based on the Cartographer algorithm for real -time positioning and mapping is widely used in fields such as robot navigation and autonomous driving. However, in the context of UAV applications, this algorithm has a high dependence on the amount of point cloud information in the surrounding environment, and cannot achieve precise positioning in open spaces with insufficient lighting and fewer feature points, resulting in significant mapping errors. In order to solve the problem of low positioning estimation accuracy in the Cartographer algorithm in above environment, this paper proposes a precise positioning algorithm for UAVs that integrates VIO and Cartographer. This algorithm can continuously output more accurate position estimation information during UAV flight, compensating for the problem of inaccurate position estimation caused by partial feature loss or coordinate system drift in point clouds. In addition, this algorithm ensures navigation obstacle avoidance in narrow spaces by improving positioning accuracy and mapping accuracy, making it more applicable in the field of UAVs. Finally, the effectiveness of the proposed positioning algorithm was verified through experimental analysis of the Cartographer dataset and practical testing of UAVs in real scenarios.

关键词： unmanned aerial vehicles positioning algorithm cartographer VIO Kalman filter

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Implementation of Least Squares algorithm Based on Dynamic Threshold in Beidou Satellite positioning

Implementation of Least Squares Algorithm Based on Dynamic T...

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Image Processing, Electronics and Computers (IPEC), Asia-Pacific Conference on

作者： Guoping Lei Xiuying Luo Zhiyuan Liu Minlu Dai School of Electronic & information Engineering Chongqing Three Gorges University Chongqing Wanzhou China

ISBN: (数字)9781728160672

ISBN: (纸本)9781728160689

At present, China's Beidou Navigation Satellite System (BDS) has been successfully applied in all walks of life, entering a period of rapid development. The least squares algorithm is often used to solve problems in the application of BDS, while the quaternary nonlinear equation set is used for solving the positioning and timing issues. The application of least square algorithm in the PVT solution of Beidou satellite navigation is to solve a set of quaternion nonlinear equations. The solution of the least squares is an iterative process, but if the convergence threshold is too small in the iterative process, it may lead to iteration without convergence. In order to improve the failure of convergence caused by too small convergence threshold in the original algorithm, a least squares algorithm based on dynamic threshold was proposed in this paper. The proposed algorithm could continue iteration until convergence by increasing the system's dynamic threshold. At the same time, the proposed algorithm could also change the satellite combination in time, so as to conduct the positioning and calculation again over the threshold value that increases to a fixed value but fails to converge. And the simulation results show that if the threshold is set too small, it can converge well. As a result, the algorithm not only effectively prevents the program failure in Beidou satellite positioning caused by the convergence failure of algorithm iteration, but also greatly improves the stability and reliability of the system program operation.

关键词： eidou satellite positioning algorithm least squares algorithm dynamic threshold convergence Converge least squares algorithm iterative methods Iterative Process algorithms Patient positioning System of equations Least squares method

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Real-time positioning algorithm for variable-geometry air-assisted orchard sprayer

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COMPUTERS AND ELECTRONICS IN AGRICULTURE 2013年 98卷 175-182页

作者： Osterman, Aljaz Godesa, Tone Hocevar, Marko Sirok, Brane Stopar, Matej Univ Ljubljana Fac Mech Engn Ljubljana 1000 Slovenia Agr Inst Slovenia Ljubljana 1000 Slovenia

An algorithm for positioning of spraying arms based on laser scanner measurements for a variable-geometry air-assisted orchard sprayer is proposed. Functioning of the algorithm is presented for a real sprayer intended for experimental spraying in orchards, which has three hydraulically movable spraying arms that cover one side of a row of trees. The developed algorithm is based on realtime measurements of tree canopies from a laser scanner mounted on the sprayer. According to the measured canopies of trees the spraying arms move linearly and angularly in a plane perpendicular to the row so that spraying nozzles which are located at the ends of the arms are optimally positioned. The algorithm calculates the optimal position for each of the three height segments of a tree (each covered by one arm) based on a simplified contour of the measured canopy of the corresponding row section. Inside the height segments the contour is simplified with a linear approximation using the least-squares method. The optimal position for each arm is then calculated so that the nozzle is directed normally to the linear fit of the contour at a distance for which full coverage of the tree height segment is achieved. The coverage is calculated with consideration of the spray angle. Due to sometimes great displacements between positions in consecutive time steps, calculated positions in each time step may not always be reachable in a real operation of the sprayer. Such great displacements are mainly a result of variable growth of trees and angular sensitivity of the algorithm. The latter is expressed when a change in the contour shape causes a changed direction of a normal which further on causes a change in the position of the arm. This change of position can be interpreted in relation to the change of the contour shape as amplified proportionally to the distance between the arm and the linear fit. To obtain physically feasible displacements, calculated positions were smoothed using the unwe

关键词： Laser scanner LIDAR positioning algorithm Orchard spraying Variable-geometry sprayer Canopy contour

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Investigation of positioning algorithm and method for increasing the linear measurement range for four-quadrant detector

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OPTIK 2013年第24期124卷 6806-6809页

作者： Chen, Mengwei Yang, Yingping Jia, Xinting Gao, Hongyun Wuhan Univ Technol Sch Sci Wuhan 430070 Peoples R China

The paper studied the relationship between the light spot position and the output voltage in the case of laser spot which is in the four-quadrant (4Q) detector whose shape is circle or elliptic, energy distribution uniform or Gaussian. The study is based on add-subtract algorithm, diagonal algorithm and difference over sum (Delta/Sigma) algorithm. By using methods of polynomial fitting it can get a simple polynomial expression to enhance measuring speed and the simulation error is given. A method of using Binary Optics Elements (BOE) to shape the laser beam in the 4Q detector to square light spot with uniform intensity distribution is proposed to expand linear measurement range. The simulation result is verified for a circular spot with Gaussian energy distribution. (C) 2013 Elsevier GmbH. All rights reserved.

关键词： Four-quadrant detector positioning algorithm Spot properties Beam shaping Linear measurement range

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