Quadratic Estimators from Interrupted Observations Transmitted by Different Sensors
R. Caballero, A. Hermoso‐Carazo, J. Linares‐Pérez · 2011
The least-squares quadratic estimation problem of discrete-time signals from uncertain noisy observations coming from multiple sensors is addressed. The uncertainty about the signal being present or missing in the observation of each sensor is modelled by a set of Bernoulli random variables whose probabilities are not necessarily the same for all the sensors. It is assumed that only information on the moments (up to the fourth-order ones) of the signal and observation noise is available. The recursive quadratic estimation algorithm is derived from a linear estimation algorithm for a suitably defined augmented system. Mathematics Subject Classification: 62M20, 60G35