Implementation of Kalman Filtering Techniques for Filtering CPT Cone Tip Measurements

Cone penetration testing (CPT) is a popular and cost effective tool for geotechnical site characterization. CPT consists of pushing at a constant rate an electronic penetrometer into penetrable soils and recording cone bearing (qm), sleeve friction (fs) and dynamic pore pressure (u) with depth. The measured qm, fs and u values are utilized to estimate soil type and associated properties based predominantly on empirical correlations. The cone bearing measurements are highly susceptible to additive measurement noise for sandy, silty and gravelly soils. This measurement noise results in high peaks due to interbedded gravels and stones and low peaks due to softer materials or local pore pressure build-up. To date there has been little progress in filtering this additive noise aside from ad hoc techniques, which include discarding qm measurements and smoothing/averaging qm measurements. This paper outlines a qm filtering technique which attempts to put structure into the estimation problem. In this case, the dynamics of the cone bearing measurements are modelled within a state-space mathematical formulation and a Kalman filter (KF) is then utilized to obtain optimal estimates of qm. The mathematical details of the qm KF algorithm are outlined in this paper along with the results from a challenging test bed simulation.