Automatic anomaly detection for swarm observations

BI Yaxin; CHRISTODOULOU Vyron; WILKIe George; ZHAO Guoze; NICHOLL Perter; HAN Bin; TANG Ji

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Automatic anomaly detection for swarm observations
Vol. 24, Issue S1, Pages: 173-182(2020)
Published：07 June 2020
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DOI：

Bi Y X, Christodoulou V, Wilkie G, Zhao G Z, Nicholl P, Han B and Tang J. 2020. Automatic anomaly detection for swarm observations. Journal of Remote Sensing(Chinese). 24(S1): 173-182 DOI：

摘要

Abstract

The Swarm satellite mission was lunched on November 22

2013

it is the first European Space Agency's constellation of three satellites

dedicated to monitoring geomagnetic field changes. The measurements delivered by the three satellite are very valuable for a range of applications

including earthquake prediction study. However

for more than 5 years

relatively little advancement has been achieved on establishing a systematic approach for detecting anomalies from the satellite measurements for predicting earthquakes. This paper presents the challenges of developing a pragmatic framework for automatic anomaly detection and highlights innovative features of functional components developed. Through a case study we demonstrate a functionality pipeline of the system in detecting anomalies

and present our solutions to coping with data sparsity and parameter tuning as well as insights into the differences between discovering seismic anomalies from periodic and non-periodic data observed by the Swarm satellites.

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references

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