Improved Multi-Path Interference Separation for Indirect 3D Time-of-Flight using Particle Swarm Optimization

The accuracy of indirect 3D Time-of-Flight (3D ToF) measurements is often limited by multi-path interferences (MPI) caused by multi-layer ToF conditions. Taking multiple measurements of the same scene at different modulation frequencies allows separating the interfering signal components of the individual paths according to several optimization methods described in literature. Orthogonal matching pursuit (OMP) optimization has been reported to achieve good path separation performance and superior results compared to particle swarm optimization (PSO). This work presents improved PSO performance for MPI separation based on new experimental data and refined PSO strategy. The current PSO approach achieves good distance separation in the setup used with low RMS distance errors in the order of 20 em in situations where the OMP approach shows RMS errors higher than 100 cm, The previously reported minimum distance difference limitation between two separate objects of 2.7m for the OMP algorithm could be reduced to roughly 0.75m for the PSO algorithm. The trade-off between image accuracy and computing effort is explored and presented with respect to PSO parameter settings.