Reasoning under an uncertain thermal state

We propose a novel approach based on dual filtering techniques for the detection of possible variations of the thermal properties of the spacecraft that result from variations of its physical properties and for determining a complete thermal mapping of the system. System and sensor uncertainties are taken into account in the lumped parameter modeling of the thermal system and a dual filter is run on the stochastic model in an alternating optimization fashion to estimate the thermal state and coefficients of the resulting thermal network from the readings of few, strategically placed, thermal sensors.