文章基本信息

标题：Improvement of Ultrasound-Based Localization System Using Sine Wave Detector and CAN Network
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作者：Tan-Sy Nguyen ; Trong-Nghia Nguyen
期刊名称：Journal of Sensor and Actuator Networks
电子版ISSN：2224-2708
出版年度：2017
卷号：6
期号：3
页码：12
DOI：10.3390/jsan6030012
语种：English
出版社：MDPI Publishing
摘要：This paper presents an improved indoor localization system based on radio frequency (RF) and ultrasonic signals, which we named the SNSH system. This system is composed of a transmitter mounted in a mobile target and a series of receiver nodes that are managed by a coordinator. By measuring the Time Delay of Arrival (TDoA) of RF and ultrasonic signals from the transmitter, the distance from the target to each receiver node is calculated and sent to the coordinator through the CAN network, then all the information is gathered in a PC to estimate the 3D position of the target. A sine wave detector and dynamic threshold filter are applied to provide excellent accuracy in measuring the range from the TDoA results before multilateration algorithms are realized to optimize the accuracy of coordinate determination. Specifically, Linear Least Square (LLS) and Nonlinear Least Square (NLS) techniques are implemented to contrast their performances in target coordinate estimation. RF signal encoding/decoding time, time delay in CAN network and math calculation time are carefully considered to ensure optimal system performance and prepare for field application. Experiments show that the sine wave detector algorithm has greatly improved the accuracy of range measurement, with a mean error of 2.2 mm and maximum error of 6.7 mm for distances below 5 m. In addition, 3D position accuracy is greatly enhanced by multilateration methods, with the mean error in position remaining under 15 mm. Furthermore, there are 90% confidence error values of 23 mm for LLS and 20 mm for NLS. The update in the overall system has been verified in real system operations, with a maximum rate of 25 ms, which is a better result than many other existing studies.
关键词：indoor localization; multilateration; sine wave detector; time different of arrival; CAN network; Least Squares method indoor localization ; multilateration ; sine wave detector ; time different of arrival ; CAN network ; Least Squares method