In situ calibration of cross-sensitive sensors in mobile sensor arrays using fast informed non-negative matrix factorization

Olivier Vu Thanh (1, 2) , Matthieu Puigt (1) , Farouk Yahaya (1) , Gilles Delmaire (1) , Gilles Roussel (1)

1 LISIC - Laboratoire d'Informatique Signal et Image de la Côte d'Opale
2 UMons - Université de Mons

In this paper, we assume a set of mobile geolocalized sensor arrays observing an area over time. Each of these arrays consists of heterogeneous and cross-sensitive sensors, i.e., the sensor readings provided by one of such sensors also depends on the readings of the other sensors in the array. We further assume that such arrays are possibly-uncalibrated and we aim to propose an in situ calibration method---i.e., a data-driven technique---for such arrays. The novelty of this paper is twofold: we first revisit in situ calibration of mobile cross-sensitive sensors as an informed factorization of a partially observed non-negative matrix. A fast informed (semi-)NMF approach is then proposed and found to be well-suited for the considered problem.

Mots clés: Sensor calibration; Mobile sensor array net- work; Informed non-negative matrix factorization; Missing values; Expectation maximization; Nesterov accelerated gradient

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

Olivier Vu Thanh, Matthieu Puigt, Farouk Yahaya, Gilles Delmaire, Gilles Roussel. In situ calibration of cross-sensitive sensors in mobile sensor arrays using fast informed non-negative matrix factorization. 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Jun 2021, Toronto, Canada. pp.3515-3519, ⟨10.1109/ICASSP39728.2021.9414742⟩. ⟨hal-03126481⟩