Correcting INS Drift in Terrain Surface Measurements

Abstract

Modern terrain measurement systems use an inertial navigation system (INS) to measure and remove vehicle movement from laser measurements of the terrain surface. Instrumental and environmental biases inherent in the INS produce noise and drift errors in these measurements. The evolution and implications of terrain surface measurement techniques and existing methods for correcting INS drift are reviewed as a framework for a new compensation method for INS drift in terrain surface measurements. Each measurement is considered a combination of the true surface and the error surface, defined on a Hilbert vector space, in which the error is decomposed into drift (global error) and noise (local error). The global and local subspaces are constructed such that the drift is modeled as a random walk process and the noise is a zero-mean process. This theoretical development is coupled with careful experimental design to identify the drift component of error and discriminate it from true terrain surface features, thereby correcting the INS drift. It is shown through an example that this new compensation method dramatically reduces the variation in the measured surfaces to within the resolution of the measurement system itself.