Abstract

This paper adapts Helmert’s simplified variance component estimation (VCE) algorithm for static and kinematic GPS single point positioning (SPP). First, the VCE algorithm for a static GPS SPP is formulated. Second, the concept of redundancy contribution of observations is developed in Kalman filtering so that the VCE algorithm is further delivered in Kalman filtering. The proposed VCE approach in Kalman filtering allows the variance components for individual measurement noises and individual independent process noises to be estimated. Some VCE numerical results from static and kinematic GPS datasets are presented and discussed.

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