PhD thesis: Constrained distributed moving horizon estimation for sensor networks with low-computation capabilities
Thesis abstract: In the general context of distributed state estimation and multi-agent systems, the practical problem of interest explored in this PhD is the one of area surveillance using a network of sensors. The problem consists in estimating online the trajectory of an intruder infiltrating the monitored area. Assuming that computation and communication capabilities are associated to each sensor (or subset of sensors), distributed state observers will be considered, in order to increase the resilience with respect to the loss of one or more sensor(s).
Duration: October 2022 – September 2025
Funding: AID & ONERA
– Supervisor : Cristina Stoica (L2S)
– Co-Supervisor : Sylvain Bertrand (ONERA-DTIS)
– International collaboration: Teodoro Alamo & Eduardo F. Camacho (Univ. of Seville, Spain)