Study on noise removal from gravity measurement data obtained on a moving carrier using statistial independence of signals

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  • 信号の統計的独立性に着目した移動体上での重力観測データからのノイズ除去の試み
  • シンゴウ ノ トウケイテキ ドクリツセイ ニ チャクモク シタ イドウタイ ジョウ デ ノ ジュウリョク カンソク データ カラ ノ ノイズ ジョキョ ノ ココロミ

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Abstract

 A compact gravity observation system using a force-balance accelerometer, which enables efficient measurement of gravity on moving carriers, is under development (Matsuo et al., 2012). The observation records obtained by the device are contaminated by various noises, including those whose sources are not identified. A low-pass filter was not able to remove all of such noises and efficient noise removal methods are needed.<br>  This paper proposes to use methods which remove noises exploiting statistical independence of noise signals and gravity observation data. We discuss applicability of Second Order Blind Identification (SOBI) and Thin-Independent Component Analysis (Thin-ICA). They are originally developed for Blind Signal Separation (BSS), which identifies original signals from the time series data that is a mixture of several original signals.<br>  The gravity measurements using a ship were carried out in the Toyama Bay and the observation records were processed by those two methods. The gravity signal obtained under appropriate conditions showed a good agreement with the high quality data obtained by AIST (National Institute of Advanced Industrial Science and Technology), indicating that methods using statistical independence can be promising noise removal methods. They did not work efficiently under poor conditions, and it is necessary to clarify the required conditions for the observation.<br>

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