State Estimation of Pest Populations subject to Intermittent Measurements. Issue 32 (2022) - Rossello, Nicolas Bono; Rossini, Luca; Speranza, Stefano; Garone, Emanuele
Abstract: This paper introduces an observer-based scheme to estimate pest populations in agricultural fields. The proposed scheme describes the different stages of the life cycle of insects as a system of ODEs and it uses an Extended Kalman Filter with intermittent observations to provide a state estimation. This scheme aims at providing a general framework to formally combine physiologically-based models and field measurements, contrary to current best practices where both methodologies are used independently in parallel. The presented approach allows to apply this framework to a large number of species of agricultural interest and to take advantage from different counting systems. The improvement of the presented approach with respect to current best practices is demonstrated by means of numerical simulations based on the case of Drosophila suzukii.