COVARIANCE PROJECTION METHODS FOR FILTERS AND SMOOTHERS

The covariance projection equations (error budgets), which express the error covariance as the sum of covariances due to different error sou rces, are derived from the sensitivity analysis equations of optimal e stimators for batch processors, filters, and smoothers for discrete an d continuous problems, The sensitivity analysis of optimal estimation covariances are shown to be the same as previously derived suboptimal estimation sensitivities, which characterize the loss of estimator per formance due to the use of nonoptimal values for error covariances. Pr ojection equations for steady-state filter and smoother values are obt ained, Some steady-state filter examples are considered.