Journal of Sensor Science and Technology (센서학회지)

The Korean Sensors Society (한국센서학회)
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Data-Driven Batch Processing for Parameter Calibration of a Sensor System

센서 시스템의 매개변수 교정을 위한 데이터 기반 일괄 처리 방법

  • Kyuman Lee (Department of Robot and Smart System Engineering, Kyungpook National University)
  • 이규만 (경북대학교 로봇 및 스마트시스템공학과)
  • Received : 2023.11.06
  • Accepted : 2023.11.28
  • Published : 2023.11.30
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Abstract

When modeling a sensor system mathematically, we assume that the sensor noise is Gaussian and white to simplify the model. If this assumption fails, the performance of the sensor model-based controller or estimator degrades due to incorrect modeling. In practice, non-Gaussian or non-white noise sources often arise in many digital sensor systems. Additionally, the noise parameters of the sensor model are not known in advance without additional noise statistical information. Moreover, disturbances or high nonlinearities often cause unknown sensor modeling errors. To estimate the uncertain noise and model parameters of a sensor system, this paper proposes an iterative batch calibration method using data-driven machine learning. Our simulation results validate the calibration performance of the proposed approach.

Keywords

Acknowledgement

이 성과는 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(No. 2021R1G1A1095335). 본 연구는 2021년도 정부(과학기술정보통신부)의 재원으로 정보통신기획평가원의 지원을 받아 연구되었음. (No.2021-0-00320, 실공간 대상 XR 생성 및 변형/증강 기술 개발). 본 연구는 과학기술정보통신부의 재원으로 한국연구재단, DNA+드론기술개발사업의 지원을 받아 수행되었음.(No. NRF-2020M3C1C2A01080819)

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