Large and small scale sensitivity analysis of optimum estimation algorithms

This paper presents the derivation and evaluation of algorithms for error analysis, large and small scale sensitivity of optimum filtering and fixed interval smoothing solutions to linear estimation problems. Model errors as well as ignorance of plant and measurement noise covariance matrices are considered. Results are presented for a simple scalar problem and for the problem of state estimation in an inertial navigation system operating in the free inertial mode.