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Full-band signal extraction from sensors in extreme environments: the NASA InSight microseismometer

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Title: Full-band signal extraction from sensors in extreme environments: the NASA InSight microseismometer
Authors: Stott, AE
Charalambous, C
Warren, TJ
Pike, WT
Item Type: Journal Article
Abstract: Physically meaningful signal extraction from sensors deployed in extreme environments requires a combination of attenuation of confounding inputs and the removal of their residual using decorrelation techniques. In space applications where the resources for physical attenuation are limited, there is a necessity to apply the most effective post-processing analysis available. This paper describes the extraction of the seismic signal from an MEMS microseismometer to be deployed on the surface of Mars. The signal processing, which covers the full bandwidth 1 × 10 -5 Hz to 40 Hz, uses a novel application of sensor fusion through an indirect Kalman Filter in combination with a thermal model of the microseismometer to remove the aseismic contribution of temperature over the frequency range. Owing to the full-band decorrelation, the analysis (based on pre-landing testing in analogous scenarios) produces both a characterization of the microseismomter and a signal processing approach for information retrieval on Mars, along with other planetary and terrestrial planetary deployments.
Issue Date: 15-Nov-2018
Date of Acceptance: 5-Sep-2018
URI: http://hdl.handle.net/10044/1/69507
DOI: 10.1109/JSEN.2018.2871342
ISSN: 1530-437X
Publisher: Institute of Electrical and Electronics Engineers
Start Page: 9382
End Page: 9392
Journal / Book Title: IEEE Sensors Journal
Volume: 18
Issue: 22
Copyright Statement: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor/Funder: Science & Technology Facilities Council
Funder's Grant Number: ST/R002231/1
Keywords: Science & Technology
Technology
Physical Sciences
Engineering, Electrical & Electronic
Instruments & Instrumentation
Physics, Applied
Engineering
Physics
Sensor fusion
MEMS seismometer
instrument response correction
Kalman filter
space applications
temperature dependence
NOISE
SEISMOMETER
Science & Technology
Technology
Physical Sciences
Engineering, Electrical & Electronic
Instruments & Instrumentation
Physics, Applied
Engineering
Physics
Sensor fusion
MEMS seismometer
instrument response correction
Kalman filter
space applications
temperature dependence
NOISE
SEISMOMETER
Analytical Chemistry
0205 Optical Physics
0906 Electrical and Electronic Engineering
0913 Mechanical Engineering
Publication Status: Published
Online Publication Date: 2018-09-19
Appears in Collections:Electrical and Electronic Engineering
Faculty of Engineering