Internal Calibration Process Using Chirp Pulses with Application of the Adam Learning Algorithm

Fuente: arXiv
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Main Authors: Kweon, Junho, Jung, Chan-Yong, Bae, Kyung-Bin, Park, Seong-Ook
Format: Preprint
Published: 2020
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author Kweon, Junho
Jung, Chan-Yong
Bae, Kyung-Bin
Park, Seong-Ook
author_facet Kweon, Junho
Jung, Chan-Yong
Bae, Kyung-Bin
Park, Seong-Ook
contents We propose a new internal calibration process using chirp pulses. Our method is utilized to mitigate thermal drift, which is unwanted changes and usually occurs in active elements such as a high power amplifier and low noise amplifier. The proposed method has advantages from two distinct aspects: calibration signal and algorithm. In respect to the calibration signal, our method does not contain an additional signal source because chirp pulses, which are normally used for remote sensing, are used as calibration signals. Moreover, our methods solve the ambiguity problem of analyzing a phase shift which occurs when sinusoidal signals are used as calibration signals. In regards to the algorithm, the Adam learning algorithm avoids learning in the wrong direction, unlike the conventional gradient descent. Using our method, mathematical forms of received signals are acquired successfully. Our method shows better effectivity compared to the conventional gradient descent algorithm. After compensation, the maximum differences of gain and phase become 0.06 dB and 2.42 degrees, respectively.
format Preprint
id arxiv_https___arxiv_org_abs_2012_01919
institution arXiv
publishDate 2020
record_format arxiv
spellingShingle Internal Calibration Process Using Chirp Pulses with Application of the Adam Learning Algorithm
Kweon, Junho
Jung, Chan-Yong
Bae, Kyung-Bin
Park, Seong-Ook
Signal Processing
We propose a new internal calibration process using chirp pulses. Our method is utilized to mitigate thermal drift, which is unwanted changes and usually occurs in active elements such as a high power amplifier and low noise amplifier. The proposed method has advantages from two distinct aspects: calibration signal and algorithm. In respect to the calibration signal, our method does not contain an additional signal source because chirp pulses, which are normally used for remote sensing, are used as calibration signals. Moreover, our methods solve the ambiguity problem of analyzing a phase shift which occurs when sinusoidal signals are used as calibration signals. In regards to the algorithm, the Adam learning algorithm avoids learning in the wrong direction, unlike the conventional gradient descent. Using our method, mathematical forms of received signals are acquired successfully. Our method shows better effectivity compared to the conventional gradient descent algorithm. After compensation, the maximum differences of gain and phase become 0.06 dB and 2.42 degrees, respectively.
title Internal Calibration Process Using Chirp Pulses with Application of the Adam Learning Algorithm
topic Signal Processing
url https://arxiv.org/abs/2012.01919