Sequential Monte Carlo approach to inverse problems in heat transfer of satellite

The inverse problem in heat transfer of satellite is to reconstruct the orbit out heat flux depending on the given temperature observations in this paper. To identify dynamically the out heat flux and predict the temperature of satellite more easily and correctly, a Sequential Monte Carlo (SMC) approach was proposed, together with a double layer lumped parameter model. In the SMC approach, one attempts to construct the Posterior Probability Density Function (PPDF) of the state, this improves the perfoemace of out heat flux identification and temperature prediction. A simulation example of inverse problems in heat transfer of Satellite was presented. Simulation results demonstrate the performance of dynamical identification and precision of estimation were improved with the SMC, and the great potential of applying the SMC to identification problem of satellite.