Blind Calibration of Mobile Sensors Using Informed Nonnegative Matrix Factorization

Abstract

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Outlier-robust calibration method for sensor networks

“…This work opens many perspectives. We recently proposed some mobile sensor calibration techniques based on informed matrix factorization [12], [13], [14]. In future work, we will investigate some outlier-robust extensions of these approaches, using a similar low-rank modeling.…”

“…When the sensors are mobile, they can be in rendezvous, i.e., they are in the same spatio-temporal neighborhood, thus sensing the same phenomenon [6]. Such an assumption was recently used 1 in both micro- [8], [9], [10] and macro-calibration 2 [12], [13], [14]. However, in the case of fixed sensors, other assumptions are needed.…”

Blind mobile sensor calibration using an informed nonnegative matrix factorization with a relaxed rendezvous model

“…Such a multi-hop calibration procedure might suffer from calibration error propagation. On the contrary, in our previous work [12], we revisited BMSC as an informed matrix This work was funded by the "OSCAR" project within the Région Nord Pas de Calais "Chercheurs Citoyens" Program. 1 It should be noticed that calibration may refer to several different-while sometimes linked-problems and have been tackled, e.g., for fixed sensor gain calibration [2,3], gain/offset calibration [4] or gain/phase calibration [5][6][7][8].…”

“…In crowdsensing applications, most sensors-which are usually embedded in mobile devices-are low cost and must be remotely calibrated, as it may not be possible to request these devices to regularly go to a laboratory in order to perform sensor calibration. As a consequence, specific Blind Mobile Sensor Calibration (BMSC) methods 1 have been proposed in, e.g., [9][10][11][12]. All these methods are exploiting the rendezvous model [13] which assumes that sensors in the same spatio-temporal vicinity should acquire the same data.…”

“…All these methods are exploiting the rendezvous model [13] which assumes that sensors in the same spatio-temporal vicinity should acquire the same data. Contrary to [9], the authors in [10][11][12] consider that some of the available sensors are calibrated. In particular, the methods in [10,11] use a multi-hop calibration structure: calibrated sensors are used to calibrate uncalibrated ones which lie in the same vicinity.…”