Abstract
The 60 GHz pulse is more practical for the indoor localisation system due to its better time resolution. Usually, time-of-arrival (TOA) estimation with higher accuracy is critical to the indoor localisation. To acquire precise TOA estimations, a novel threshold crossing technique using neural network (NN) is discussed via analysing the characteristics of the received pulses based on the energy detection receiver. The relationship between the optimum thresholds and the signal-to-noise ratios (SNRs) are researched. Meanwhile, the influences caused by changing integration periods and channel models are examined. Results show that the proposed NN method can provide better accuracy and robustness to the lower SNR in the models designed by TG 3c.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
