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J Sanjuán

Researcher at Institut de Ciències de l'Espai

Publications -  39
Citations -  831

J Sanjuán is an academic researcher from Institut de Ciències de l'Espai. The author has contributed to research in topics: Engineering & Computer science. The author has an hindex of 8, co-authored 24 publications receiving 664 citations. Previous affiliations of J Sanjuán include University of Florida.

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Measurement of stray electric fields in a capacitive inertial sensor using contactless test-mass charge modulation

TL;DR: In this paper , a new technique for measuring the stray electric field in precision space inertial sensors by modulating the electric charge of a free-falling test mass and measuring the resulting coherent Coulomb force is presented.
Posted Content

Theoretical foundations for on-ground tests of LISA PathFinder thermal diagnostics

TL;DR: In this paper, the authors report on the methods and results of a theoretical analysis to design an insulator which must provide a thermally quiet environment to test on ground delicate temperature sensors and associated electronics.
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Extension of the LTP temperature diagnostics to the LISA band: first results

TL;DR: In this paper, the performance of temperature sensors and the associated electronics at frequencies around 0.1 mHz and amplitude levels of 10 uK/sqrt(Hz were investigated.
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Design and performance characterization of a new LISA-like (laser interferometer space antenna-like) gravitational reference sensor and torsion pendulum testbed.

TL;DR: In this paper , the design and performance of the upgraded University of Florida torsion pendulum facility for testing inertial sensor technology related to space-based gravitational wave observatories and geodesy missions are presented.
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Gyro-Free Inertial Navigation Systems Based on Linear Opto-Mechanical Accelerometers

TL;DR: In this paper , the performance of a gyro-free inertial navigation system with six accelerometers with different sensitivities and bandwidths was analyzed using the colored noise from experimental data.