Olivier Bilenne

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This study is concerned with the problem of static parameter estimation by robust sensor fusion in the context of applications requiring, for safety reasons, a high guarantee on the reliability of the results. The integrity certification process consists of providing confidence intervals for the unknown parameter with extremely low risks of error. The(More)
This paper deals with the state estimation of dynamic systems. A recursive linear MMSE estimator is presented as an alternative to Kalman filtering . This estimator has the ability to cope with asynchronous measurements, and to process the data by sets of undefined sizes. It is particularly suitable for fault detection, because the decisions can be based on(More)
This work is concerned with the design of sensor fusion methods using the fault-tolerant interval functions proposed by K. Marzullo and U. Schmid. A trade-off exists between the precision of the interval functions and their tolerance to invalid input intervals. The study shows how the performances of the interval functions in terms of expected length and(More)
This work deals with the problem of the fault-tolerant estimation of discrete-time stochastic processes. A random walk process is estimated from the fusion of measurement uncertainty intervals provided by a set of sensors. Two algorithms of interval propagation and contraction are proposed. For both algorithms, interval contraction is done using(More)
This paper is concerned with the lifetime maximisation of wireless sensor networks (WSNs) in the context of slow-fading communication channels. The problem is first formulated as a decomposable convex optimisation problem. Dual decomposition is presented as a way to decompose the problem into smaller subproblems that can be solved locally by the nodes.(More)
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