Adaptive recognition and correction of baseline shifts from collocated GPS and accelerometer using two phases Kalman filter

Tu, Rui; Wang, Rongjiang; Walter, Thomas R.; Diao, Faqi

doi:10.1016/j.asr.2014.07.008

Cited by 12 publications

(4 citation statements)

References 29 publications

(43 reference statements)

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“…Assigning targets can increase controllability and thus reduce blindness of the baseline correction procedure. A consistent target set of time series for a signal can be obtained using the following approaches: (1) removing illegal trends from the uncorrected acceleration/velocity/displacement; (2) using the initial velocity and displacement values estimated by equations (10) and (11) or equations (13) and (14) to integrate the acceleration data; (3) retrieving data from equipment that can directly record the velocity (such as velographs) and displacement (such as displacement meters or Global Positioning System (GPS) (Tu et al., 2014)).…”

Section: Baseline Correction Algorithmsmentioning

confidence: 99%

Target-based algorithm for baseline correction of inconsistent vibration signals

Pan

Zhang

Luo

et al. 2017

Journal of Vibration and Control

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A target-based baseline correction algorithm that can directly assign acceleration/velocity/displacement values equal or close to preset target values is proposed in this study for correcting vibration acceleration signals with inconsistent initial velocities and displacements. Baseline shift or drift phenomena can arise for velocity and displacement values obtained by numerical integration of recorded acceleration signals using assumed initial values that are inconsistent with reality. Two indicators, the drift ratio and amplitude ratio, are also proposed to identify the degree of baseline drift and to evaluate the results of baseline correction. The traditional polynomial detrending algorithm has typically been used to remove unreasonable trends in time series, but insufficient attention has been paid to consistency between acceleration, velocity, and displacement, which is explicitly considered in the proposed algorithm. The target-based algorithm has two implementation schemes, that is, a precise scheme and a detrending scheme, which can be selected according to the degree of baseline drift. Three inconsistent vibration signals are considered to verify the validity of the proposed algorithm. The baseline shift or drift trends can be removed effectively using the proposed target-based algorithm with the drift ratio and amplitude ratio reduced to satisfactory ranges whereas the traditional method fails to correct these signals.

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Section: Baseline Correction Algorithmsmentioning

confidence: 99%

Target-based algorithm for baseline correction of inconsistent vibration signals

Pan

Zhang

Luo

et al. 2017

Journal of Vibration and Control

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show abstract

“…Alternatively, Bock et al (2011) applied a Kalman filter approach to the records of the collocated high-rate Global Navigation Satellite System and seismometer sites, and succeeded in estimating the displacement waveform. Lately, many papers expanded on the use of the Kalman filter approach with onshore records (e.g., Geng et al, 2013;Melgar et al, 2013;Niu & Xu, 2014;Tu et al, 2014;Zang et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Strong‐Motion Broadband Displacements From Collocated Ocean‐Bottom Pressure Gauges and Seismometers

Mizutani,

Melgar,

Yomogida

2024

Geophysical Research Letters

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Dense and broad‐coverage ocean‐bottom observation networks enable us to obtain near‐fault displacement records associated with an offshore earthquake. However, simple integration of ocean‐bottom strong‐motion acceleration records leads to physically unrealistic displacement records. Here we propose a new method using a Kalman filter to estimate coseismic displacement waveforms using the collocated ocean‐bottom seismometers and pressure gauges. First, we evaluate our method using synthetic records and then apply it to an offshore Mw 6.0 event that generated a small tsunami. In both the synthetic and real cases, our method successfully estimates reasonable displacement waveforms. Additionally, we show that the computed waveforms improve the results of the finite fault modeling process. In other words, the proposed method will be useful for estimating the details of the rupture mechanism of offshore earthquakes as a complement to onshore observations.

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“…Alternatively, Bock et al (2011) applied a Kalman filter approach to the records of the collocated high-rate Global Navigation Satellite System (HR-GNSS) and seismometer sites, and succeeded in estimating the displacement waveform. Lately, many papers expanded on the use of the Kalman filter approach with onshore records (e.g., Geng et al, 2013;Melgar et al, 2013;Niu & Xu, 2014;Tu et al, 2014;Zang et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Strong-motion Broadband Displacements from Collocated Ocean-bottom Pressure Gauges and Seismometers

Mizutani,

Melgar,

Yomogida

2023

Preprint

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Dense and broad-coverage ocean-bottom observation networks enable us to obtain near-fault displacement records associated with an offshore earthquake. However, simple integration of ocean-bottom strong-motion acceleration records leads to physically unrealistic displacement records. Here we propose a new method using a Kalman filter to estimate coseismic displacement waveforms using the collocated ocean-bottom seismometers and pressure gauges. First, we evaluate our method using synthetic records and then apply it to an offshore Mw 6.0 event that generated a small tsunami. In both the synthetic and real cases, our method successfully estimates reasonable displacement waveforms. Additionally, we show that the computed waveforms improve the results of the finite fault modeling process. In other words, the proposed method will be useful for estimating the details of the rupture mechanism of offshore earthquakes as a complement to onshore observations.

show abstract

Adaptive recognition and correction of baseline shifts from collocated GPS and accelerometer using two phases Kalman filter

Cited by 12 publications

References 29 publications

Target-based algorithm for baseline correction of inconsistent vibration signals

Target-based algorithm for baseline correction of inconsistent vibration signals

Strong‐Motion Broadband Displacements From Collocated Ocean‐Bottom Pressure Gauges and Seismometers

Strong-motion Broadband Displacements from Collocated Ocean-bottom Pressure Gauges and Seismometers

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