Optimal Design of Multiparameter Multisensor Systems

This paper addresses the optimal design of multiparameter multisensor systems with suboptimal estimators. For error propagation, the approach makes use of the so-called unscented transformation, which is an efficient way to determine the mean and variance of random distributions that undergo nonlinear transformations. It is demonstrated that a performance improvement can be achieved compared to the designs based on the Fisher information.