Abstract
In a precise positioning system, weak signal errors caused by the influence of a human body on signal transmission in complex environments are a main cause of the reduced reliability of communication and positioning accuracy. Therefore, eliminating the influence of interference from human crawling waves on signal transmissions in complex environments is an important task in improving positioning systems. To conclude, an experimental environment is designed in this paper and a method using the Ultra-Wideband (UWB) Local Positioning System II (UWB LPS), called Bayesian Compressed Sensing-Crawling Waves (BCS-CW), is proposed to eliminate the impact of crawling waves using Bayesian compressive sensing. First, analyse the transmission law for crawling waves on the human body. Second, Bayesian compressive sensing is used to recover the UWB crawling wave signal. Then, the algorithm is combined with the maximum likelihood estimation and iterative approximation algorithms to determine the label position. Finally, through experimental verification, the positioning accuracy of this method is shown to be greatly improved compared to that of other algorithms.
Highlights
With the continuous improvement of wireless technologies such as Bluetooth, ZigBee, and Wi-Fi and the rapid development of ad hoc networks and the Internet of Things, wireless networks have attracted increasing attention from academic circles
In a precise positioning system, weak signal errors caused by the influence of a human body on signal transmission in complex environments are a main cause of the reduced reliability of communication and positioning accuracy
Eliminating the influence of interference from human crawling waves on signal transmissions in complex environments is an important task in improving positioning systems
Summary
In a precise positioning system, weak signal errors caused by the influence of a human body on signal transmission in complex environments are a main cause of the reduced reliability of communication and positioning accuracy. Eliminating the influence of interference from human crawling waves on signal transmissions in complex environments is an important task in improving positioning systems. An experimental environment is designed in this paper and a method using the UltraWideband (UWB) Local Positioning System II (UWB LPS), called Bayesian Compressed Sensing-Crawling Waves (BCS-CW), is proposed to eliminate the impact of crawling waves using Bayesian compressive sensing. Analyse the transmission law for crawling waves on the human body. Through experimental verification, the positioning accuracy of this method is shown to be greatly improved compared to that of other algorithms
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