Multiple Reflection Cancellation Using High Order Statistics Adaptive Filter for Scattered Triangulation Laser Displacement Sensor

Abstract

AS for the analog front-end (AFE) with charged-coupled devices for the scattered triangulation laser displacement measurement sensors (LDMS), surface roughness of objective and reflective optical routine have synergistic effects for AFEs precision and linear. The multiple reflection property resulted from different surface roughness characteristics and probability distribution of multiply scattered light in the optical images, were analyzed. To improve analog-front-ends signal-noise ratio and reduce the non-Gaussian noise, windowed cumulates projection of noise insensitive mean square error criteria, which is the strongly consistent identification algorithms with three order cumulants, is applied to high order statistics recursive least square adaptive filter. Simulation and the test results of experiment platform illustrate the performance of the proposed algorithm and accomplish the aim of multiple reflection cancellation.