Optimization of Ultrasonic Positioning Accuracy by Hybrid Algorithm of Time Compensation Factor and Kalman Filter
Liang-Jiang International College, Chongqing University of Technology, Chongqing 401135, China
| Abstract: | In the ultrasonic positioning system, the positioning system has a certain delay due to the sequential ranging at the ultrasonic receiver, the system's decoding time and the signal transmission time, which has a great impact on the positioning accuracy. The solution is to set a time compensation factor for the speed of the object to be positioned and the positioning time of the system unit to compensate for the error, so as to achieve the same positioning accuracy when the object to be positioned is stationary; then the Kalman filter algorithm is used to correct the positioning results at different speeds, so that the positioning accuracy of the ultrasonic positioning system can be further improved. The simulation results show that the positioning accuracy can be stabilized within 2cm at a certain speed, which is able to move and position the object to be positioned at a certain speed; finally, the experiments are conducted using the Arduino Uno as the core positioning system, and the experimental results verify the simulation results and show that the solution can The experimental results verify the simulation results and show that the solution is able to improve the positioning accuracy of moving objects, especially when the object to be positioned moves at a constant speed, the positioning accuracy tends to be stable, and the object to be positioned with a certain speed can be positioned well. |
| Keywords: | Error Compensation; TOA Algorithm; Kalman Filtering Algorithm |
| DOI: | 10.57237/j.se.2022.01.002 |
View:
Downloads:
Received: 9 September 2022
Accepted: 10 October 2022
Published Online: 1 November 2022
Funding
| 1. | 国家自然科学基金资助项目 (51875069) |
| 2. | 重庆理工大学研究生创新项目 (gzlcx20223131) |
References
| [1] | 蔡志猛. 5G 移动通信发展趋势与若干关键技术 [J]. 数字技术与应用, 2015 (02): 41-41. |
| [2] | Saez-Mingorance B, Mendez-Gomez J, Mauro G, et al. Air-Writing Character Recognition with Ultrasonic Transceivers [J]. Sensors, 2021, 21 (20): 6700. |
| [3] | Chen M, AlRegib G, Juang B H. Air-writing recognition—Part I: Modeling and recognition of characters, words, and connecting motions [J]. IEEE Transactions on Human-Machine Systems, 2015, 46 (3): 403-413. |
| [4] | Chen M, AlRegib G, Juang B H. Air-writing recognition—Part II: Detection and recognition of writing activity in continuous stream of motion data [J]. IEEE Transactions on Human-Machine Systems, 2015, 46 (3): 436-444. |
| [5] | 王君, 谢之光, 吕东航,等. 基于超声波定位的舞台自动追光灯设计 [J]. 电子设计工程, 2016, 24 (4): 3. |
| [6] | 佘昌佳, 郑建勇, 何嘉弘, 等. 时差筛选和ABC二次寻优的变压器局放超声定位方法 [J]. 高电压技术, 2021, 47 (8): 8. |
| [7] | 律方成, 李海德, 王子建,等. 基于TEV与超声波的开关柜局部放电检测及定位研究 [J]. 电测与仪表, 2013, 50 (11): 6. |
| [8] | 孙红新, 叶小岭, 胡凯. 基于超声波的移动机器人的同时定位和地图构建 [J]. 计算机测量与控制, 2011, 19 (11): 3. |
| [9] | 丁兵, 黄燕琳, 徐鸽,等. 管材纵向焊缝超声波检测缺陷定位方法研究 [J]. 造船技术, 2014 (3): 4. |
| [10] | Zhuang Y, Hua L, Qi L, et al. A survey of positioning systems using visible LED lights [J]. IEEE Communications Surveys & Tutorials, 2018, 20 (3): 1963-1988. |
| [11] | Ohtani K, Baba M, Tanii Y. An ultrasonic local positioning system using four base stations [C] // SICE Annual Conference 2011. IEEE, 2011: 1-5. |
| [12] | 王昕, 王宗欣, 刘石. 一种考虑非视线传播影响的TOA 定位算法[J]. 通信学报, 2001, 22 (3): 1-8. |
| [13] | 李广羽. 基于TOA 无锚定位算法的无线传感器节点硬件平台研究 [J]. 煤炭技术, 2011, 30 (012): 169-170. |
| [14] | 张兴红, 陈然, 张志忠, 孙冰曼, 徐翊. 基于TOA算法的超声波定位节点布局研究 [J/OL]. 重庆理工大学学报 (自然科学): 1-8 [2022-05-06]. |
| [15] | 陈燕. 基于UWB的高精度室内三维定位技术研究 [D]. 电子科技大学, 2018. |
| [16] | 张文勇. 机器人装配应用中的视觉引导关键技术研究 [D]. 安徽工业大学, 2019. |
| [17] | An Introduction to the Kalman Filter[M]. University of North Carolina at Chapel Hill, 1995. |
| [18] | Faragher R. Understanding the Basis of the Kalman Filter Via a Simple and Intuitive Derivation [Lecture Notes] [J]. IEEE Signal Processing Magazine, 2012, 29 (5): 128-132. |
| [19] | Lacey T. Tutorial: The Kalman Filter [J]. Georgia Institute of Technology, 1998. |
| [20] | 王旭哲. 基于大规模天线阵列波束定位跟踪策略研究 [D]. 东南大学, 2019. |
| [21] | 李爱双, 夏宁. 基于粒子滤波和卡尔曼滤波的室内定位方法研究 [J]. 资源信息与工程, 2019, 34 (03): 163-164. |
| [22] | 邰明. 基于无线传感网的智能小车室内定位方法的研究[D]. 新疆大学, 2018. |
| [23] | 薛伟成. FM指纹定位的技术研究 [D]. 中国科学院大学(中国科学院国家授时中心), 2020. DOI: 10.27547/d.cnki.gkgsc.2020.000021. |
Join the Editorial Board
We invite active, qualified and high profile scientists and researchers to join as Editorial Board Members.
Join UsBecome a Reviewer
Scholars with a strong interest in reviewing are invited to join the reviewer panel to ensure the quality of the research to be published.
Join Us