Nonlinear mobile sensor calibration using informed semi-nonnegative matrix factorization with a Vandermonde factor

Clément Dorffer (1) , Matthieu Puigt (1) , Gilles Delmaire (1) , Gilles Roussel (1)

1 LISIC - Laboratoire d'Informatique Signal et Image de la Côte d'Opale

In this paper we aim to blindly calibrate a mobile sensor network whose sensor outputs and the sensed phenomenon are linked by a polynomial relationship. The proposed approach is based on a novel informed semi-nonnegative matrix factorization with a Vandermonde factor matrix. The proposed approach outperforms a matrix-completion-based method in a crowdsensing-like simulation of particulate matter sensing.

Mots clés: nonlinear sensor calibration; informed semi-NMF; structured matrix factorization

Domaines: Traitement du signal et de l'image [eess.SP]

Clément Dorffer, Matthieu Puigt, Gilles Delmaire, Gilles Roussel. Nonlinear mobile sensor calibration using informed semi-nonnegative matrix factorization with a Vandermonde factor. 9th IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2016), Jul 2016, Rio de Janeiro, Brazil. ⟨10.1109/SAM.2016.7569735⟩. ⟨hal-01371239⟩