Engineering Commons^™

State Estimation Using Parallel Extended Kalman Filters Of Nonlinear Measurements, Thomas Carlyle Sheives

Electrical and Computer Engineering ETDs

The extended Kalman filter applied to state estimation using nonlinear measurements has demonstrated divergence in many applications involving large initial uncertainties because of "invalid" linearizations performed by the filter on the nonlinear measurement functions. No quantitative results can be found as to how invalid these linearizations must be before divergence occurs. This report attempts to fill this void by deriving the extended Kalman filter as an approximate nonlinear least squares estimator, through the minimization of a measurement squared error function. The convergence of the extended Kalman filter is then determined by examining the squared error function and verifying the usefulness …