A processing approach for a correlating time-of-flight range sensor based on a least squares method

A novel processing approach for the output data of a correlating time-of-flight range sensor based on a least squares method is presented. Until now, the fast Fourier transform and a trigonometric approach have been widely used to derive the distance information from the output signal of the sensor. Compared to these methods, the presented approach does not suffer from a systematic phase-dependent error for ideal signals. Moreover, this method allows the detection of multipath propagation, i.e., it is possible to detect if light from different distances is received at the same time. Under certain circumstances, it is even possible to extract the distances of the different paths. Simulation results are presented, comparing the performance of this novel approach to the existing ones. Moreover, first measurement results prove the feasibility of this method and show a reduction of the phase-dependent error by 90% compared to the alternative approaches.