Adaptive Grid Solution of Risk Sensitive Estimator Problems
Shovan Bhaumik, M. Srinivasan, S. Sadhu, Tapan Kumar Ghoshal · 2006
An on-going work proposing a novel method for numerical computation of risk sensitive state estimates for non-linear non-Gaussian problems is reported. The algorithm is based on point mass approximation also called the grid method and utilises a modified form of information state based recursive relation, proposed and proved as a theorem. The modified form is claimed to be more efficient for numerical evaluation of risk sensitive estimate, especially for aposteriori risk sensitive state estimation. Though grid based filters are known for low numerical efficiency, heuristics for adaptive choice of grid points has been proposed to alleviate the shortcoming. The performance of this filter is demonstrated with a linear Gaussian case. Salient features of this Adaptive Grid RSF is then contrasted against the recently proposed Risk Sensitive Filters using the particle approach.