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FPGA implementation of adaptive time delay estimation for real‐time near‐field electromagnetic ranging
Author(s) -
Wang Peng,
Zhang Xiaotong,
Liu Zhiyang,
Xu Liyuan,
He Jie,
Xu Jinwu
Publication year - 2018
Publication title -
international journal of circuit theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 52
eISSN - 1097-007X
pISSN - 0098-9886
DOI - 10.1002/cta.2513
Subject(s) - ranging , estimator , computer science , detector , signal (programming language) , field programmable gate array , electronic engineering , noise (video) , group delay and phase delay , gate array , algorithm , control theory (sociology) , engineering , telecommunications , mathematics , computer hardware , bandwidth (computing) , statistics , control (management) , artificial intelligence , image (mathematics) , programming language
Summary The near‐field electromagnetic ranging systems exploit the near‐field phase behavior of low frequency signals for indoor real‐time ranging. Conventionally, phase detector is used to determine the phase of electric and magnetic fields. Subsequently, the phase difference is used to estimate a distance value. In adaptive time delay estimation approach, the time delay between electric and magnetic signals is used instead of phase difference for an estimation. This method does not require a priori knowledge of the transmitting signals and can obtain better performance in low signal‐to‐noise ratio environment. In this paper, we propose a digital near‐field electromagnetic ranging system design and implement it on field‐programmable gate array. This system is composed of time delay estimator, frequency estimator, and received signal strength indicator. A maximum correntropy criterion–based explicit time delay estimation algorithm with a delay in the coefficient update is implemented to estimate the time delay in real time. The fast Fourier transform and received signal strength indicator modules determine the signal frequency and the signal strength received, respectively. Our experimental results indicate that the delayed maximum correntropy criterion–based explicit time delay estimation algorithm has fast convergence rate and good steady‐state performance in an impulsive noise environment.