D Kalman Filtering for Non-Minimal Measurement Models

Abstract

This appendix contains the proof that the Kalman Filter (KF) is robust against non-minimal measurement equations. The KF algorithm uses the inverse of the innovation covariance matrix S _k . For non-minimal measurement equations, this matrix is singular. This appendix contains the proof that the results of the Kalman Filter (KF) using non-minimal measurement equations are the same as the results of the KF using a minimal set of measurement equations, whatever generalised inverse S^# _k we choose.