Approximate Gauss‐Newton Method for Robust Parameter Estimation

Abstract

We consider robust parameter estimation problems in which either the l1 norm or the Huber function of a measurement error vector used as cost functionals. In order to avoid high computational effort of computing exact derivatives needed for the solution of these problems with the Gauss‐Newton method, we suggest to use approximations of the derivatives in the occurring linearized subproblems. We show how the error introduced by using only approximated derivatives can be compensated by adding a correction term to the objective function of the linearized problems. (© 2010 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)